Figma vs Penpot

Agent ops

1. ai-native userAn agent can create or modify designs programmatically — through a write-capable API, plugin surface, or MCP tools — not just read them

   weight 2 · round to Figma
   Figma✓fullprobed9/10

   Figma's official MCP server explicitly documents write-capable tools ("Write to the canvas: Create and modify native Figma content directly from your MCP client", "enabling agents to write native Figma content back to the canvas"), plus the Plugin API supports full read/write access to create and modify file contents, and the REST API includes create/update/delete endpoints (e.g., Variables API). This is corroborated by multiple first-party docs and a dedicated probe confirming the MCP server's existence. Missing for 10: no independent hands-on report specifically validating write-via-MCP in production use.

   • [claimed-docs] “Write to the canvas: Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “enabling agents to write native Figma content back to the canvas”
   • [claimed-docs] “provides tools for reading designs out of Figma, writing designs into Figma, connecting designs to your codebase, and building generative pl…”
   • [claimed-docs] “The Plugin API supports both read and write access to Figma's editors, allowing developers to view, create, and modify the contents of files…”
   • [claimed-docs] “The Plugin API supports both **read** and **write** access to Figma's editors, allowing developers to view, create, and modify the contents …”
   • [claimed-docs] “The Variables REST API includes endpoints for querying, creating, updating, and deleting variables.”
   • [probe] “official MCP server documented at https://developers.figma.com/docs/figma-mcp-server/”

   proof ↗⚑ flag

   Penpot~partialprobed6/10

   Penpot has a documented MCP server explicitly for connecting AI agents/LLMs to design files, plus a plugin API and integrations API with access to objects/properties, suggesting agents can both read and modify designs programmatically. However, MCP docs emphasize agents 'reading and interacting with' design files for high-fidelity artifacts, and no independent/hands-on evidence confirms write operations via MCP or API actually work reliably, and openapi/spec probes 404'd. Missing for 10: concrete documented write/create examples via MCP or API, independent verification of agent-driven design edits, and a working OpenAPI spec.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Connect Penpot MCP server to your trusted AI agent. Customize your models and design infrastructure however works best for your team.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

2. ai-native userAn agent can render and export designs — screenshots, images, or production formats — through a documented programmatic surface

   weight 2 · round to Figma
   Figma~partialprobed6/10

   Figma's docs show agents can extract design data and generate code from frames via the MCP server and REST API (figma-docs-39, figma-docs-40, figma-docs-59, figma-docs-49), and the REST API is documented as a programmatic surface for pulling objects/layers. However, the evidence pack never explicitly documents an image/screenshot rendering or production-format export endpoint (e.g., PNG/SVG/PDF render API) for agent use — most citations focus on writing to canvas, code generation, and diagram creation rather than visual export. Missing for 10: explicit documentation of an image-rendering/export endpoint or MCP tool for screenshots/production image formats, and independent/hands-on confirmation of such export working via the programmatic surface.

   • [claimed-docs] “Select a Figma frame and turn it into code. Great for product teams building new flows or iterating on app features.”
   • [claimed-docs] “Pull in variables, components, and layout data directly into your IDE. This is especially useful for design systems and component-based work…”
   • [claimed-docs] “provides tools for reading designs out of Figma, writing designs into Figma, connecting designs to your codebase, and building generative pl…”
   • [claimed-docs] “view and extract any objects or layers, and their properties from files”
   • [claimed-docs] “This gives you the ability to do things such as view and extract any objects or layers, and their properties from files, get usage data, or …”
   • [probe] “official MCP server documented at https://developers.figma.com/docs/figma-mcp-server/”

   proof ↗⚑ flag

   Penpot~partialprobed5/10

   Penpot documents an MCP server and plugin/integrations API that give agents structured access to design objects and mentions 'external rendering' as a use case (penpot-docs-3, penpot-docs-32), and design data can be exported to open formats like SVG/CSS/HTML (penpot-docs-21). However, there is no concrete documented endpoint or workflow for producing screenshots/images/production export files programmatically, no OpenAPI spec was found (404s in penpot-probe-2), and one community report describes limited export options (single-layer only) in hands-on use (penpot-comm-5). missing for 10: an explicit documented render/export API or endpoint (PNG/PDF/JPG) usable by an agent, a working OpenAPI/schema reference, and independent confirmation that MCP/plugin API can actually produce exported artifacts.

   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON as well as Penpot's open file for…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”
   • [community] “Maybe I'm using it wrong... when I tried Penpot about a year ago, I had no way to export the diagram as one file like PDF or JPG. I could on…”

   proof ↗⚑ flag

3. ai-native userMy coding agent can pull real design context — frames, variables, screenshots, component mappings — through an MCP server or API to implement the design

   weight 3 · round to Figma
   Figma✓fullprobed9/10

   Figma ships a first-party MCP server (local and remote) with documented tools for extracting variables, components, layout data, generating code from frames, and writing back to canvas, plus REST API endpoints for variables, layers, and Code Connect for component-to-code mapping — directly matching the story. Evidence spans official docs, GitHub repo, and a probe confirming the live MCP server endpoint. Missing for 10: independent hands-on developer report specifically validating MCP-based design-to-code extraction (community evidence covers general Figma-to-code pain points but not the MCP server itself).

   • [claimed-docs] “Extract design context: Pull in variables, components, and layout data directly into your IDE.”
   • [claimed-docs] “Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “Select a Figma frame and turn it into code. Great for product teams building new flows or iterating on app features.”
   • [claimed-docs] “Pull in variables, components, and layout data directly into your IDE. This is especially useful for design systems and component-based work…”
   • [claimed-docs] “provides tools for reading designs out of Figma, writing designs into Figma, connecting designs to your codebase, and building generative pl…”
   • [claimed-docs] “`get_variable_defs` extracts the **variables and styles** used in your selection (color, spacing, typography, etc).”
   • [claimed-docs] “enabling agents to write native Figma content back to the canvas”
   • [github] “Code Connect is a tool for connecting your design system components in code with your design system in Figma.”
   • [claimed-docs] “Sync design system source of truth to and from Figma”
   • [claimed-docs] “The Variables REST API includes endpoints for querying, creating, updating, and deleting variables.”
   • [probe] “official MCP server documented at https://developers.figma.com/docs/figma-mcp-server/”
   • [claimed-docs] “Figma's remote MCP server makes it possible to connect directly to your Figma files without needing to install Figma's desktop app.”

   proof ↗⚑ flag

   Penpot~partialprobed6/10

   Penpot documents an official MCP server that lets any AI agent connect to design files, described as exposing design as code so agents can 'read and interact with your design files' and access objects/properties for external rendering, plus separate docs on components, design tokens, and design-system alignment (penpot-docs-1,18,27,31,32,3,33,11). However, no evidence explicitly confirms screenshot export or an explicit frame/variable/component mapping schema via the MCP itself, and there is no independent/hands-on report validating the MCP server's real-world behavior (only first-party docs, plus unrelated community comments about general app performance). Missing for 10: independent verification of MCP server functioning as described, explicit mention of screenshot/visual context retrieval, and concrete component-mapping API examples.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “A component is a layer or group of layers that can be reused multiple times across files. This can help you maintain consistency across a gr…”
   • [claimed-docs] “Design Tokens - Make design decisions that align designers and developers' workflows.”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

Agent access

1. ai-native userPoint an agent at llms.txt or agent-oriented docs

   weight 2 · round drawn
   Figma✓fullprobed8/10

   A probe confirms a live llms.txt file at https://developers.figma.com/llms.txt returning HTTP 200 with a structured description of Figma's developer platform docs, directly enabling an agent to be pointed at it. Missing for 10: independent/community confirmation of an agent successfully consuming the file, and no evidence of additional agent-oriented doc formats (e.g., openapi.json, which 404s).

   • [probe] “PROBE llms.txt: HTTP 200 at https://developers.figma.com/llms.txt # Figma Developer Documentation > Documentation for building on Figma's d…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://developers.figma.com/openapi.json, https://developers.figma.com/swagger.json, https://develo…”

   proof ↗⚑ flag

   Penpot✓fullprobed8/10

   Penpot publishes an actual llms.txt at penpot.app/llms.txt with structured content (design tokens, plugin marketplace stats, Figma comparison) as cited in penpot-docs-16 and penpot-docs-24, plus extensive agent-oriented docs for its MCP server (penpot-docs-1, 18, 19, 27, 31, 32, 39) explicitly aimed at AI agents. missing for 10: an independent probe directly confirming penpot.app/llms.txt resolves (the probe only tested the unrelated help.penpot.app subdomain and got 404), and no third-party corroboration that agents successfully consume this file.

   • [claimed-docs] “Penpot vs Figma: Open-source alternative with self-hosting, unlimited files, native design tokens.”
   • [claimed-docs] “Plugins (113+): Community plugin marketplace with accessibility, code, AI, and design system tools.”
   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”
   • [probe] “PROBE llms.txt: HTTP 404 at https://help.penpot.app/llms.txt”

   proof ↗⚑ flag

2. ai-native userRun the product headlessly / in CI for automation

   weight 2 · round drawn
   Figma~partialclaimed5/10

   Figma's REST API explicitly supports CI/CD-style automation for variables sync ('Integrate Figma directly with continuous integration (CI) systems', 'useful for needs like CI/CD implementations... webhooks... service accounts') and webhooks/plan tokens allow non-interactive, user-agnostic access, which is real evidence of headless automation capability. However this is scoped mainly to variables/webhooks/library-analytics rather than full design-file manipulation or MCP server operation, and there's no evidence of a general-purpose CLI or headless rendering/export pipeline for arbitrary Figma actions. missing for 10: evidence of a full headless CLI or automation runner covering arbitrary design operations (not just variables/webhooks), independent/hands-on confirmation of CI usage, and headless operation of the MCP server itself.

   • [claimed-docs] “useful for needs like CI/CD implementations, logging, creating user-agnostic webhooks, and other tasks that you normally wouldn't want gated…”
   • [claimed-docs] “Integrate Figma directly with continuous integration (CI) systems.”
   • [claimed-docs] “The Variables REST API includes endpoints for querying, creating, updating, and deleting variables.”
   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files. For example: a collaborator comments on a file, or you add a new version…”
   • [claimed-docs] “you can make requests on behalf of other users, and the requests themselves aren’t made using your personal Figma account.”

   proof ↗⚑ flag

   Penpot~partialclaimed5/10

   Penpot ships self-host/Docker/Kubernetes deployment, access-token API auth, outbound webhooks, and a self-hostable MCP server, all of which could underpin automated/CI-driven workflows, but there is no explicit documentation of a headless mode, CLI, or CI pipeline usage. missing for 10: explicit headless/CI-mode documentation, CLI tooling, independent evidence of running Penpot in a CI pipeline.

   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”
   • [claimed-docs] “Deploy with docker compose... Use Kubernetes in its different flavors: Deploy the official Helm Chart”
   • [claimed-docs] “Use access tokens as an alternative login authentication. They can allow an app to access Penpot's API.”
   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “you can set up an instance of Penpot in just 3 minutes!”

   proof ↗⚑ flag

3. ai-native userPlug MCP servers into this product so it can use their tools

   weight 3 · round to Penpot
   Figma—none0/10

   All MCP-related evidence describes Figma exposing its own MCP server for external clients (e.g., IDEs, coding agents) to consume Figma's tools — the opposite direction of this story, which asks whether Figma itself can plug in and use external MCP servers' tools. No evidence shows Figma's AI/agent features acting as an MCP client capable of consuming third-party MCP servers.

   ⚑ flag

   Penpot~partialclaimed3/10

   Penpot's docs mention connecting to another product's MCP server ('Migrate your designs into Penpot by connecting Figma's and Penpot's MCPs') implying Penpot can act as an MCP client to import tool-provided data, but the vast majority of MCP evidence describes Penpot instead exposing its OWN MCP server for agents to connect to (the reverse relationship), not Penpot consuming arbitrary external MCP servers' tools. Missing for 10: documentation of a general-purpose MCP client/connector UI in Penpot, a list of supported external MCP servers beyond Figma, and any hands-on/community confirmation that this client-side integration works.

   • [claimed-docs] “Migrate your designs into Penpot by connecting Figma’s and Penpot’s MCPs.”
   • [claimed-docs] “Migrate your designs into Penpot by connecting Figma's and Penpot's MCPs.”
   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic”

   proof ↗⚑ flag

4. ai-native userConnect an agent via an official MCP server

   weight 3 · round drawn
   Figma✓fullprobed8/10

   Figma ships an official, well-documented MCP server (local and remote) that lets AI clients read/write Figma content, extract design context, generate code, and more, with detailed docs on installation, tools, and custom rules (figma-docs-1/3/5/38/59/67/68/69, figma-probe-3). This is a first-party, actively maintained integration point for agentic MCP clients. Missing for 10: independent/hands-on community verification that the MCP connection works reliably in practice (community evidence only discusses unrelated Figma pain points, not MCP specifically).

   • [claimed-docs] “Write to the canvas: Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “Extract design context: Pull in variables, components, and layout data directly into your IDE.”
   • [claimed-docs] “Generate designs from live UI: Use a supported MCP client to capture the live UI of your web app or site and send it to new and existing Fig…”
   • [claimed-docs] “Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “provides tools for reading designs out of Figma, writing designs into Figma, connecting designs to your codebase, and building generative pl…”
   • [claimed-docs] “Figma's remote MCP server makes it possible to connect directly to your Figma files without needing to install Figma's desktop app.”
   • [claimed-docs] “`get_variable_defs` extracts the **variables and styles** used in your selection (color, spacing, typography, etc).”
   • [claimed-docs] “Define project-level instructions to help guide the AI toward consistent, high-quality output.”
   • [probe] “official MCP server documented at https://developers.figma.com/docs/figma-mcp-server/”

   proof ↗⚑ flag

   Penpot✓fullprobed8/10

   Penpot documents an official MCP server (agnostic, self-hostable, connects to any AI agent/LLM) with dedicated marketing/docs pages and a probe confirming the page exists. Missing for 10: independent/hands-on third-party confirmation that the MCP server works reliably in practice, and technical setup/API reference details beyond marketing copy.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Connect Penpot MCP server to your trusted AI agent. Customize your models and design infrastructure however works best for your team.”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

5. ai-native userUse an official CLI

   weight 2 · round to Figma
   Figma~partialprobed5/10

   Figma does ship an official CLI (Code Connect CLI, documented at the quickstart guide) which is used to sync design system components in code with Figma and keep MCP-generated code consistent with the codebase — supporting agentic/CI-style workflows. However, the evidence pack gives no detail on CLI command surface, scripting for AI agents, or independent hands-on validation beyond its existence. Missing for 10: detailed CLI usage docs for AI-native/agentic workflows, examples of CLI use in automated/agent pipelines, independent corroboration of the CLI's capabilities.

   • [probe] “official CLI documented at https://developers.figma.com/docs/code-connect/quickstart-guide/”
   • [github] “Figma's Dev Mode will display true-to-production code snippets from your design system instead of autogenerated code examples.”
   • [github] “Code Connect is a tool for connecting your design system components in code with your design system in Figma.”
   • [github] “Code Connect is a tool for connecting your design system components in code with your design system in Figma. When using Code Connect, Figma…”
   • [claimed-docs] “Code Connect keeps your generated code consistent with your codebase.”

   proof ↗⚑ flag

   Penpot—none0/10

   Evidence covers Penpot's MCP server, plugin API, webhooks, and REST access tokens, but there is no mention of an official CLI tool for interacting with Penpot as an AI-native workflow interface. The MCP server is a distinct integration mechanism, not a CLI.

   ⚑ flag

6. ai-native userDrive the product through a documented public API

   weight 3 · round to Figma
   Figma✓fullprobed9/10

   Figma publishes a well-documented REST API (with OpenAPI spec on GitHub), webhooks, Plugin API, and an official MCP server enabling agentic control of designs, code generation, and diagrams—giving AI-native users multiple documented, programmatic ways to drive the product. Missing for 10: a discoverable live OpenAPI/swagger endpoint on the docs domain itself (probe found 404s) and more independent hands-on corroboration of API robustness beyond vendor docs.

   • [claimed-docs] “This gives you the ability to do things such as view and extract any objects or layers, and their properties from files, get usage data, or …”
   • [claimed-docs] “Leverage the power of our REST API to bring Figma into your external tools and products.”
   • [claimed-docs] “This repository contains the OpenAPI specification and Typescript types for the Figma REST API”
   • [claimed-docs] “Write to the canvas: Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “provides tools for reading designs out of Figma, writing designs into Figma, connecting designs to your codebase, and building generative pl…”
   • [probe] “official MCP server documented at https://developers.figma.com/docs/figma-mcp-server/”
   • [probe] “PROBE openapi: all candidate paths 404 (https://developers.figma.com/openapi.json, https://developers.figma.com/swagger.json, https://develo…”
   • [claimed-docs] “The Plugin API supports both read and write access to Figma's editors, allowing developers to view, create, and modify the contents of files…”

   proof ↗⚑ flag

   Penpot✓fullprobed8/10

   Penpot documents a public API with access tokens for authentication, outbound webhooks, an open plugin API, and a dedicated MCP server explicitly designed to let any AI agent/LLM read and manipulate design files programmatically. This directly matches the ai-native 'documented public API' story, with self-hosting options adding control. Missing for 10: no discoverable OpenAPI/swagger spec (probes returned 404s) and no independent/hands-on verification of the API's completeness beyond vendor docs.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “Use access tokens as an alternative login authentication. They can allow an app to access Penpot's API.”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

7. ai-native userIssue scoped/least-privilege API credentials for an agent

   weight 2 · round to Figma
   Figma~partialclaimed4/10

   Figma's REST API docs mention OAuth apps that can 'make requests on behalf of other users' without using a personal account, and 'plan access tokens' scoped to an org/enterprise plan, plus service-account-like tokens for CI/CD/webhooks decoupled from an individual user — these are building blocks for issuing a non-personal, scoped credential to an agent. However there is no explicit documentation of granular least-privilege scopes (e.g., read-only vs write, per-file/per-resource permissions) for AI agents or the MCP server specifically. Missing for 10: documented fine-grained OAuth/API scopes selectable for agent credentials, explicit MCP-server auth/scoping guidance, and any independent confirmation this scoping mechanism is used for AI agents.

   • [claimed-docs] “A plan access token provides API access scoped to an organization or enterprise plan.”
   • [claimed-docs] “useful for needs like CI/CD implementations, logging, creating user-agnostic webhooks, and other tasks that you normally wouldn't want gated…”
   • [claimed-docs] “you can make requests on behalf of other users, and the requests themselves aren’t made using your personal Figma account.”
   • [claimed-docs] “you can make requests on behalf of other users, and the requests themselves aren’t made using your personal Figma account”

   proof ↗⚑ flag

   Penpot—none0/10

   Penpot offers access tokens as an alternative login method for API access (penpot-docs-6) and an MCP server for agent connectivity, but there is no evidence of scoped or least-privilege credential issuance (e.g., permission-limited tokens, role-based scopes, or granular API key restrictions) for agents. Missing for 10: scoped/permission-limited token creation, documentation of least-privilege API key options, agent-specific credential management.

   • [claimed-docs] “Use access tokens as an alternative login authentication. They can allow an app to access Penpot's API.”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”

   proof ↗⚑ flag

8. ai-native userBuild against official SDKs

   weight 2 · round to Figma
   Figma✓fullprobed8/10

   Figma provides an official REST API with OpenAPI spec and TypeScript types (figma-docs-46), a Plugin/Widget API (figma-docs-8, figma-docs-32), Code Connect SDK/CLI on GitHub (figma-gh-1, figma-gh-2, figma-docs-60), and an official MCP server for AI-native workflows (figma-probe-3, figma-docs-1). These are well-documented, first-party SDKs/APIs explicitly built for programmatic and AI-agent integration. missing for 10: no independent hands-on developer corroboration of SDK reliability/completeness, and probe found no discoverable openapi.json at the expected well-known endpoints despite a spec repo existing.

   • [claimed-docs] “This repository contains the OpenAPI specification and Typescript types for the Figma REST API”
   • [github] “Figma's Dev Mode will display true-to-production code snippets from your design system instead of autogenerated code examples.”
   • [github] “Code Connect is a tool for connecting your design system components in code with your design system in Figma.”
   • [claimed-docs] “The Plugin API supports both read and write access to Figma's editors, allowing developers to view, create, and modify the contents of files…”
   • [claimed-docs] “The Plugin API supports both **read** and **write** access to Figma's editors, allowing developers to view, create, and modify the contents …”
   • [probe] “official MCP server documented at https://developers.figma.com/docs/figma-mcp-server/”
   • [claimed-docs] “Write to the canvas: Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “This guide helps you connect your React (or React Native) components with Figma components using Code Connect.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://developers.figma.com/openapi.json, https://developers.figma.com/swagger.json, https://develo…”

   proof ↗⚑ flag

   Penpot✓fullprobed7/10

   Penpot ships an official, self-hostable MCP server plus an open plugin API, REST API with access-token auth, and webhooks, explicitly marketed for AI agents to build against (penpot-docs-1,3,5,6,19,27,31,32,39). This gives AI-native users concrete official SDK/API surfaces to integrate with, though there's no independent hands-on validation of the MCP server and the OpenAPI spec could not be located (probe 404s), missing for 10: independent developer confirmation of MCP/plugin SDK reliability, discoverable machine-readable OpenAPI/llms.txt spec.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “Our plugin system brings the flexibility that devs need to create and publish their own custom extensions.”
   • [claimed-docs] “Use access tokens as an alternative login authentication. They can allow an app to access Penpot's API.”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Connect Penpot MCP server to your trusted AI agent. Customize your models and design infrastructure however works best for your team.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

9. ai-native userSubscribe to events via webhooks

   weight 2 · round drawn
   Figma✓fullclaimed7/10

   Figma's REST API docs explicitly describe creating and managing webhooks and subscribing to events like comments or new file versions, with a dedicated webhooks-endpoints reference, directly matching the user story. Missing for 10: independent or hands-on corroboration that webhook subscriptions work reliably in practice, and fuller documentation of the range of supported event types beyond the couple of examples given.

   • [claimed-docs] “Create and manage [webhooks](/docs/rest-api/webhooks-endpoints/)”
   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files. For example: a collaborator comments on a file, or you add a new version…”
   • [claimed-docs] “useful for needs like CI/CD implementations, logging, creating user-agnostic webhooks, and other tasks that you normally wouldn't want gated…”
   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files.”
   • [claimed-docs] “This gives you the ability to do things such as view and extract any objects or layers, and their properties from files, get usage data, or …”

   proof ↗⚑ flag

   Penpot✓fullclaimed7/10

   Penpot's docs explicitly describe outbound webhooks that notify external apps of events like file creation/update or comments, directly matching the 'subscribe to events via webhooks' story. Evidence is vendor-documentation only with no independent/hands-on confirmation of webhook delivery or a full list of supported event types. Missing for 10: independent corroboration of webhook triggering/reliability, complete event-type catalogue, and details on webhook subscription management (payload schema, retries, security).

   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”

   proof ↗⚑ flag

Agentic features

1. ai-native userGet AI-generated insights and suggestions from my data inside the product

   weight 2 · round to Penpot
   Figma!disputedcontradicted5/10

   Figma documents an AI agent that generates design directions, diagrams, images, and searches files, and touts 'AI agents work in the same space with shared context' (figma-docs-17, figma-docs-34, figma-docs-51), which matches the story's intent of AI-generated insights/suggestions from the user's own design data. However, hands-on community feedback specifically contradicts this: 'the AI tools in FigJam are really bad and often broken' (figma-comm-8), while another user reports success summarizing notes into slides (figma-comm-9), giving mixed real-world evidence rather than a clean full delivery. Missing for 10: independent benchmarks or broader corroboration of AI insight quality/reliability across Figma (not just FigJam), and clearer documentation of insight-generation (vs. content-generation) use cases.

   • [claimed-docs] “Use the Figma agent to generate new design directions, create diagrams, edit images, search your files, and more.”
   • [claimed-docs] “Compare multiple directions side by side and dig into the details with your whole team. Anyone can edit designs and riff with the agent to r…”
   • [claimed-docs] “Teammates and AI agents work in the same space with shared context. Generate new design directions, refine, and align—together.”
   • [community] “Figma itself is great. Figjam is okay. Slides was literally made because they realized customers were using Figma for presentations, but the…”
   • [community] “With the integration of AI, people are using Figma for more than just design - a friend used it to input notes/data and have its AI summariz…”

   proof ↗⚑ flag

   Penpot~partialclaimed5/10

   Penpot exposes design data via its MCP server, plugin API, and webhooks so external AI agents can read structured design data and generate outputs (e.g., 'AI agents can easily read and interact with your design files creating high-fidelity artifacts') and the plugin marketplace lists AI tools, but there is no evidence of a built-in, first-party AI feature that proactively surfaces insights or suggestions from a user's own data inside the product itself. Missing for 10: a native in-app AI insight/suggestion feature (vs. only enabling third-party agents via MCP/plugins), and any hands-on/community confirmation that such insights actually work in practice.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Penpot enables plenty of AI workflows, from generating editable design structures to connecting product logic, tokens, and implementation.”
   • [claimed-docs] “Plugins (113+): Community plugin marketplace with accessibility, code, AI, and design system tools.”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”

   proof ↗⚑ flag

2. ai-native userSet up automations that run autonomously in the background

   weight 2 · round to Figma
   Figma~partialclaimed5/10

   Figma exposes webhooks and REST API that let external systems react to events (comments, version changes) and CI/CD integrations, which supports background automation infrastructure, but there is no evidence of a native, autonomous scheduled agent or background-running automation within Figma itself — plugins/widgets require user invocation or live session context. Missing for 10: evidence of a built-in scheduler/autonomous agent execution mode, and independent confirmation that webhook-driven automations run fully unattended without additional third-party glue.

   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files. For example: a collaborator comments on a file, or you add a new version…”
   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files.”
   • [claimed-docs] “useful for needs like CI/CD implementations, logging, creating user-agnostic webhooks, and other tasks that you normally wouldn't want gated…”
   • [claimed-docs] “Integrate Figma directly with continuous integration (CI) systems.”
   • [claimed-docs] “Create and manage [webhooks](/docs/rest-api/webhooks-endpoints/)”
   • [claimed-docs] “You can build plugins that run immediately when invoked by the user, or that require users to input information via custom UI.”
   • [claimed-docs] “Unlike plugins that run for a specific person, everyone can see and interact with the same widget.”

   proof ↗⚑ flag

   Penpot~partialclaimed4/10

   Penpot provides building blocks for automation—an MCP server for AI agents, outbound webhooks, and a plugin API—that could underlie background automations, but all documented use cases (prompting an agent, plugin actions) are interactive/triggered rather than autonomous, unattended background processes. Missing for 10: explicit support for scheduled/triggered autonomous agent runs, evidence of agents operating without a live user prompt, and any independent confirmation that MCP/webhook flows work unattended in production.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “Penpot enables plenty of AI workflows, from generating editable design structures to connecting product logic, tokens, and implementation.”

   proof ↗⚑ flag

3. ai-native userDelegate tasks to a built-in AI assistant inside the product

   weight 3 · round to Figma
   Figma!disputedcontradicted5/10

   Figma ships a built-in AI agent (Figma AI/Make) that can generate designs, diagrams, edit images, search files, and collaborate with teammates in real time (figma-docs-17, figma-docs-34, figma-docs-51), which matches the story of delegating tasks to an in-product assistant. However, a hands-on community report explicitly states the AI tools (in FigJam) are 'really bad and often broken' (figma-comm-8), directly contradicting the vendor's polished framing of reliable delegation. Missing for 10: independent corroboration that the assistant reliably completes delegated tasks, and detail on task scope/limits beyond marketing copy.

   • [claimed-docs] “Use the Figma agent to generate new design directions, create diagrams, edit images, search your files, and more.”
   • [claimed-docs] “Compare multiple directions side by side and dig into the details with your whole team. Anyone can edit designs and riff with the agent to r…”
   • [claimed-docs] “Teammates and AI agents work in the same space with shared context. Generate new design directions, refine, and align—together.”
   • [community] “Figma itself is great. Figjam is okay. Slides was literally made because they realized customers were using Figma for presentations, but the…”
   • [community] “With the integration of AI, people are using Figma for more than just design - a friend used it to input notes/data and have its AI summariz…”

   proof ↗⚑ flag

   Penpot—none0/10

   Penpot's AI evidence is entirely about an MCP server that lets external AI agents/LLMs connect to Penpot's data (penpot-docs-1, penpot-docs-18, penpot-docs-27, penpot-docs-31, penpot-docs-39), not about a built-in AI assistant embedded in the product itself that users can delegate tasks to. No evidence describes an in-app AI chat/copilot feature within the Penpot UI.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “Connect Penpot MCP server to your trusted AI agent. Customize your models and design infrastructure however works best for your team.”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

4. ai-native userOperate the product with natural-language commands

   weight 2 · round to Penpot
   Figma~partialcommunity5/10

   Figma ships a first-party AI agent (natural-language design generation, image editing, file search, diagram creation, and Figma Make for prompt-to-prototype) letting users operate parts of the product conversationally, plus an MCP server enabling agent-driven natural-language control from IDEs. However, community feedback specifically calls the FigJam AI tools 'really bad and often broken,' and there's no independent corroboration that the core Figma AI agent reliably handles broad natural-language operation across the whole product surface (only marketing copy). Missing for 10: independent hands-on validation of the Figma AI agent's reliability, evidence of NL command coverage beyond generation/diagramming/search, and resolution of the FigJam AI quality complaints.

   • [claimed-docs] “Use the Figma agent to generate new design directions, create diagrams, edit images, search your files, and more.”
   • [claimed-docs] “Compare multiple directions side by side and dig into the details with your whole team. Anyone can edit designs and riff with the agent to r…”
   • [claimed-docs] “From there, share a PRD and build with your existing design context intact.”
   • [claimed-docs] “Teammates and AI agents work in the same space with shared context. Generate new design directions, refine, and align—together.”
   • [claimed-docs] “Prototype. Polish. Ship. Your ideas get real in Figma Make.”
   • [community] “Figma itself is great. Figjam is okay. Slides was literally made because they realized customers were using Figma for presentations, but the…”
   • [community] “With the integration of AI, people are using Figma for more than just design - a friend used it to input notes/data and have its AI summariz…”

   proof ↗⚑ flag

   Penpot✓fullprobed7/10

   Penpot ships an official MCP server explicitly designed so any AI agent/LLM can 'prompt away' to read and manipulate design files expressed as code, directly enabling natural-language operation, backed by plugin API and access tokens for automation. Missing for 10: independent/hands-on evidence of the MCP server actually working end-to-end in practice (community comments only cover general UI/performance, not the AI/MCP workflow specifically).

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Connect Penpot MCP server to your trusted AI agent. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

Api quality

1. ai-native userExplore an interactive API reference with runnable examples

   weight 2 · round drawn
   Figma—none0/10

   Figma's REST API docs describe endpoints and there's a separate OpenAPI spec repo, but no evidence shows an interactive reference with runnable/try-it-now examples; probes for standard openapi.json/swagger endpoints on the docs site returned 404s, and no docs mention interactive code sandboxes or live example runners.

   • [claimed-docs] “This repository contains the OpenAPI specification and Typescript types for the Figma REST API”
   • [probe] “PROBE openapi: all candidate paths 404 (https://developers.figma.com/openapi.json, https://developers.figma.com/swagger.json, https://develo…”
   • [claimed-docs] “This gives you the ability to do things such as view and extract any objects or layers, and their properties from files, get usage data, or …”
   • [claimed-docs] “Leverage the power of our REST API to bring Figma into your external tools and products.”

   proof ↗⚑ flag

   Penpot—none0/10

   Evidence describes integrations-api, plugin system, and MCP server, but there is no interactive API reference with runnable examples; probes explicitly found no OpenAPI/swagger spec or llms.txt documentation endpoint (404s), and no mention of interactive docs/sandbox exists.

   • [probe] “PROBE llms.txt: HTTP 404 at https://help.penpot.app/llms.txt”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”

   proof ↗⚑ flag

2. ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)

   weight 2 · round to Figma
   Figma✓fullprobed8/10

   Figma publishes an OpenAPI specification and TypeScript types for its REST API in a public GitHub repo (figma-docs-46), which is machine-readable and downloadable, directly satisfying the story. Probe evidence shows the spec isn't hosted at conventional /openapi.json paths on the docs site (figma-probe-2), so discoverability is slightly less standard. Missing for 10: a directly hosted spec endpoint on developers.figma.com and independent confirmation of spec completeness/versioning.

   • [claimed-docs] “This repository contains the OpenAPI specification and Typescript types for the Figma REST API”
   • [probe] “PROBE openapi: all candidate paths 404 (https://developers.figma.com/openapi.json, https://developers.figma.com/swagger.json, https://develo…”
   • [claimed-docs] “Leverage the power of our REST API to bring Figma into your external tools and products.”

   proof ↗⚑ flag

   Penpot—none0/10

   While Penpot documents a general integrations API, access tokens, webhooks, and an MCP server, there is no evidence of a downloadable OpenAPI/Swagger spec; direct probes for openapi.json/swagger.json/llms.txt all returned 404s, indicating no machine-readable API spec is published.

   • [probe] “PROBE llms.txt: HTTP 404 at https://help.penpot.app/llms.txt”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “Use access tokens as an alternative login authentication. They can allow an app to access Penpot's API.”

   proof ↗⚑ flag

3. ai-native userTest against a sandbox environment without touching production data

   weight 1 · round to Penpot
   Figma—none0/10

   No evidence of a sandbox/staging environment or test mode that isolates AI-native testing from production Figma data; all MCP/API/plugin docs describe operating directly on real files and production content. missing for 10: any mention of sandbox environments, test/staging Figma instances, mock data, or non-production testing modes for AI agent workflows.

   ⚑ flag

   Penpot~partialclaimed4/10

   Penpot has no dedicated 'sandbox' or 'test environment' feature, but its self-hosting capability (docker-compose/Kubernetes deployment, MCP server deployable in your own environment) means an AI-native user could spin up an isolated instance separate from production to test agent workflows. This is an indirect workaround rather than a purpose-built sandbox/staging mode. Missing for 10: an explicit sandbox/staging environment feature, documented separation of test vs production data within the same account, and any first-party guidance on safely testing AI agents against non-production data.

   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “you can set up an instance of Penpot in just 3 minutes!”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [claimed-docs] “Keep your data private. Penpot will never make business out of your data. Choose where and how to host it, and decide who has access to it.”

   proof ↗⚑ flag

4. ai-native userRely on versioned APIs with a documented deprecation policy

   weight 2 · round to Figma
   Figma~partialclaimed3/10

   Figma publishes a REST API changelog documenting endpoint additions/renames (e.g., v2 folders endpoints, projects→folders rename) and an OpenAPI spec repo, showing some versioning practice, but there is no explicit documented deprecation policy (timelines, sunset notices, migration guarantees) for the REST API or MCP server. missing for 10: explicit deprecation policy statement, version support timelines, sunset/EOL notices for old endpoints.

   • [claimed-docs] “This repository contains the OpenAPI specification and Typescript types for the Figma REST API”
   • [claimed-docs] “Added folders endpoints for plans with nested folders enabled: GET /v2/teams/:team_id/folders”
   • [claimed-docs] “These rename "projects" to "folders" and add subfolder traversal.”
   • [claimed-docs] “A plan access token provides API access scoped to an organization or enterprise plan.”

   proof ↗⚑ flag

   Penpot—none0/10

   Evidence documents an API, plugin system, and MCP server, but there is no mention of API versioning or a documented deprecation policy anywhere in the docs; probes for OpenAPI/llms.txt spec files return 404, and no changelog or versioning policy is cited. Missing for 10: any documented API version scheme, deprecation notices, or changelog governing breaking changes.

   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “Use access tokens as an alternative login authentication. They can allow an app to access Penpot's API.”
   • [probe] “PROBE llms.txt: HTTP 404 at https://help.penpot.app/llms.txt”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”

   proof ↗⚑ flag

Ai

1. designerBuilt-in AI handles asset chores — image generation, background removal, content-aware fills, copy suggestions — inside the editor

   weight 1 · round to Figma
   Figma~partialcommunity5/10

   Figma's own site claims an in-editor AI agent that can 'generate new design directions, create diagrams, edit images, search your files, and more' (figma-docs-17, figma-docs-34), which covers some asset-chore functions like image editing and diagram generation, but the evidence never mentions background removal, content-aware fill, or copy/microcopy suggestions specifically. A community report also flags that Figma's AI tools (in FigJam) are 'really bad and often broken' (figma-comm-8), undermining confidence in reliability. missing for 10: explicit documentation of background removal, content-aware fill, and copy-suggestion features, plus independent hands-on validation that these AI asset tools work reliably.

   • [claimed-docs] “Use the Figma agent to generate new design directions, create diagrams, edit images, search your files, and more.”
   • [claimed-docs] “Compare multiple directions side by side and dig into the details with your whole team. Anyone can edit designs and riff with the agent to r…”
   • [claimed-docs] “Purchase AI credits for your whole team to share. Enable pay-as-you-go for flexibility or subscribe to save.”
   • [community] “Figma itself is great. Figjam is okay. Slides was literally made because they realized customers were using Figma for presentations, but the…”

   proof ↗⚑ flag

   Penpot—none0/10

   Penpot's AI evidence is entirely about an MCP server for connecting external AI agents/LLMs to structured design data, plus a generic plugin marketplace mention of 'AI tools' — there is no evidence of built-in editor features like image generation, background removal, content-aware fill, or copy suggestions happening inside Penpot itself. The axis is fair for a design tool (competitors ship such features), but nothing in the pack shows Penpot delivering it natively.

   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic and enables high-quality multi-directional AI workflows through our…”
   • [claimed-docs] “Penpot connects any AI agent with structured design. Automate tedious tasks, streamline your processes between apps, and build truly powerfu…”
   • [claimed-docs] “Plugins (113+): Community plugin marketplace with accessibility, code, AI, and design system tools.”
   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Penpot enables plenty of AI workflows, from generating editable design structures to connecting product logic, tokens, and implementation.”

   proof ↗⚑ flag

2. designerGenerate or edit designs from a natural-language prompt — first drafts, layouts, or full mockups the tool actually produces

   weight 2 · round to Figma
   Figma~partialcommunity6/10

   Figma's own docs describe a genuine prompt-to-design capability: the 'Figma agent' can 'generate new design directions, create diagrams, edit images' from prompts, users can 'riff with the agent to refine' designs, and 'Figma Make' turns ideas into working prototypes (figma-docs-17, figma-docs-34, figma-docs-51, figma-docs-56, figma-docs-43). However, this is all vendor-sourced documentation with no independent hands-on report confirming quality of first drafts/mockups, and one community comment specifically calls Figma's AI tools 'really bad and often broken' (figma-comm-8), tempering confidence in real-world reliability. Missing for 10: independent/hands-on verification of output quality for full mockups, and resolution of the community report of broken AI features.

   • [claimed-docs] “Use the Figma agent to generate new design directions, create diagrams, edit images, search your files, and more.”
   • [claimed-docs] “Compare multiple directions side by side and dig into the details with your whole team. Anyone can edit designs and riff with the agent to r…”
   • [claimed-docs] “Teammates and AI agents work in the same space with shared context. Generate new design directions, refine, and align—together.”
   • [claimed-docs] “Prototype. Polish. Ship. Your ideas get real in Figma Make.”
   • [claimed-docs] “From there, share a PRD and build with your existing design context intact.”
   • [community] “Figma itself is great. Figjam is okay. Slides was literally made because they realized customers were using Figma for presentations, but the…”

   proof ↗⚑ flag

   Penpot~partialprobed5/10

   Penpot's docs describe an official MCP server that lets external AI agents/LLMs read and interact with Penpot files to 'generate editable design structures' and 'create high-fidelity artifacts' from prompts (penpot-docs-31, penpot-docs-32, penpot-docs-40), which supports the story's intent of prompt-driven design generation. However, this is achieved only via connecting a third-party AI agent through MCP rather than a native in-app 'type a prompt, get a mockup' feature, and there is no independent/hands-on evidence confirming actual generated layouts or mockups working in practice. Missing for 10: first-party demo/screenshots of actual generated designs, independent hands-on reports validating the MCP-to-mockup pipeline, and a native in-app generation UI not dependent on external agent setup.

   • [claimed-docs] “Choose your agent, connect to Penpot MCP and prompt away!”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Penpot enables plenty of AI workflows, from generating editable design structures to connecting product logic, tokens, and implementation.”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

1. ai-native userPerform bulk operations across many items at once

   weight 2 · round to Figma
   Figma~partialcommunity5/10

   Figma's REST/Variables APIs, Plugin API, and webhooks let developers script operations across many objects/files (e.g., variables CRUD, library analytics across all files, plugin read/write over full documents), which supports bulk automation, but there's no native first-class 'bulk operation' feature in the product itself — community evidence shows users still rely on third-party bulk-export plugins for basic tasks like exporting many icons at once, indicating manual/plugin workarounds rather than built-in bulk tooling. missing for 10: dedicated bulk-edit/bulk-apply UI or MCP tool for acting on many layers/files simultaneously, independent verification that plugin/REST scripting reliably scales to large batches, and first-party documentation explicitly describing bulk operations as a supported workflow.

   • [claimed-docs] “The Variables REST API includes endpoints for querying, creating, updating, and deleting variables.”
   • [claimed-docs] “Get summary information about how many instances of a library's components exist across all files.”
   • [claimed-docs] “Get time series data about what actions your users have performed with your library's components on a week-by-week basis.”
   • [claimed-docs] “The Plugin API supports both read and write access to Figma's editors, allowing developers to view, create, and modify the contents of files…”
   • [claimed-docs] “The Plugin API supports both **read** and **write** access to Figma's editors, allowing developers to view, create, and modify the contents …”
   • [community] “Grabbing icons as individual SVGs is probably what takes me the longest going from design to code. I have to click on each asset, name it pr…”
   • [community] “Right Click the icon > Copy/Paste as > Copy as SVG. We use that and just paste it into the codebase. Also used a bulk export plugin that aut…”

   proof ↗⚑ flag

   Penpot!disputedcontradicted5/10

   Penpot's API/plugin/MCP layer gives extensive access to objects and properties and lets agents 'automate tedious tasks' across files (penpot-docs-2, penpot-docs-3, penpot-docs-32), which implies scriptable bulk edits, but no documentation specifically demonstrates a bulk-operation workflow (e.g., batch renaming/restyling hundreds of layers). Independent hands-on reports directly contradict smooth handling of many items: performance 'starts dropping rapidly once you approach around 1000 layers' versus design systems that run 10-40k layers (penpot-comm-19), and users report crashes/lag with just a few pages of content (penpot-comm-10, penpot-comm-16). Missing for 10: a documented bulk-edit API/plugin example, benchmarks showing many-item operations succeed at scale, and resolution of the reported performance degradation.

   • [claimed-docs] “Penpot connects any AI agent with structured design. Automate tedious tasks, streamline your processes between apps, and build truly powerfu…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [community] “Currently Penpot's performance starts dropping rapidly once you approach around 1000 layers. Most robust design systems I see run around 10-…”
   • [community] “Unstable, very crash prone with just a few users designing 10 plus pages. And a huge memory hog too. I run it on Dedicated server with 64GB …”
   • [community] “I want to like penpot, but on even my beefiest computers it causes the whole system to slow to a crawl when opening anything complex.”

   proof ↗⚑ flag

2. ai-native userDefine rules that trigger actions automatically on events

   weight 3 · round to Figma
   Figma~partialclaimed4/10

   Figma's webhooks let you observe events (comments, new versions, library usage) and forward them to external systems (figma-docs-21, figma-docs-53, figma-docs-61), which can be wired into automation elsewhere, but Figma itself has no built-in rule-builder or 'if event then action' automation engine — plugins run only on user invocation, not on trigger conditions (figma-docs-36). missing for 10: a native rules/automation UI or API where users define event-condition-action logic inside Figma, and any evidence of automatic (non-user-invoked) action execution.

   • [claimed-docs] “Create and manage [webhooks](/docs/rest-api/webhooks-endpoints/)”
   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files. For example: a collaborator comments on a file, or you add a new version…”
   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files.”
   • [claimed-docs] “You can build plugins that run immediately when invoked by the user, or that require users to input information via custom UI.”

   proof ↗⚑ flag

   Penpot~partialclaimed3/10

   Penpot's outbound webhooks fire on events (file created/updated, comment added) which is a basic event-trigger mechanism, and the MCP/plugin API lets external agents react to design changes, but there is no evidence of a rules engine or conditional logic layer where users define custom trigger conditions and automated actions within Penpot itself. missing for 10: rule-definition UI/config (conditions, filters, action chains), documented automation recipes, evidence of in-app if/then automation beyond simple webhook event notification.

   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “Our plugin system brings the flexibility that devs need to create and publish their own custom extensions.”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round drawn
   Figma—none0/10

   No evidence of any scheduling, cron-like, or recurring job/workflow automation capability in Figma's docs, API, webhooks, or MCP server offerings — webhooks are event-triggered, not scheduled recurring jobs.

   ⚑ flag

   Penpot—none0/10

   Penpot's automation surface (MCP server, plugins, webhooks, API/access tokens) supports event-driven and on-demand integrations, but no evidence anywhere in the pack describes scheduling, cron-like recurring jobs, or timed workflow execution.

   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Connect Penpot with any AI agent, any LLM. Penpot MCP server is agnostic”
   • [claimed-docs] “Connect it to any AI agent or LLM you trust. Customize your models and design infrastructure however works best for your team.”
   • [claimed-docs] “Penpot enables plenty of AI workflows, from generating editable design structures to connecting product logic, tokens, and implementation.”

   proof ↗⚑ flag

4. ai-native userVersion, review, and roll back my automations

   weight 1 · round to Figma
   Figma~partialclaimed4/10

   Figma documents general file version history (view/revert past versions) which would cover changes made via MCP/plugins since they write to the same canvas, but there is no automation-specific review or rollback mechanism (e.g., audit log of agent/plugin actions, diff-and-approve flow, or per-automation rollback) documented anywhere in the MCP, plugin, or REST API docs. Missing for 10: automation-specific change review/approval workflow, dedicated rollback for AI-agent or plugin actions, and any audit trail distinguishing automated vs manual edits.

   • [claimed-docs] “View a file's version history”
   • [claimed-docs] “Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “enabling agents to write native Figma content back to the canvas”
   • [claimed-docs] “provides tools for reading designs out of Figma, writing designs into Figma, connecting designs to your codebase, and building generative pl…”

   proof ↗⚑ flag

   Penpot—none0/10

   Penpot's evidence covers MCP/AI agent integration, webhooks, and plugins for automation, but there is no evidence of any mechanism to version, review, or roll back these automations themselves (e.g., automation history, audit trail, or undo for agent-driven actions). Component 'restore main' (docs-23) is a design-object rollback, not an automation/workflow rollback feature.

   ⚑ flag

Collaboration

1. product managerComment directly on designs, mention teammates, and resolve threads so review happens in the file, not in email

   weight 2 · round to Figma
   Figma✓fullclaimed6/10

   Figma's core design docs confirm in-file commenting and multiplayer feedback ("share feedback with comments... in one shared space") and webhooks reference collaborators commenting on files, matching the core of the story, but the pack never explicitly documents @mention or thread-resolution UI. Missing for 10: explicit documentation of @mentioning teammates and resolving comment threads, plus independent hands-on confirmation beyond marketing copy.

   • [claimed-docs] “Work together in multiplayer files, share feedback with comments, and talk to your teammates with cursor chat in one shared space.”
   • [claimed-docs] “Webhooks allow you to observe when specific events happen in files. For example: a collaborator comments on a file, or you add a new version…”

   proof ↗⚑ flag

   Penpot~partialclaimed2/10

   The only evidence touching commenting is a passing mention that webhooks fire when 'a comment has been added,' which confirms Penpot has some in-file commenting feature but gives no detail on @mentions or resolving threads. missing for 10: documentation or hands-on evidence of @mention functionality, thread resolution UI, and any community confirmation that review workflows actually replace email in practice.

   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”
   • [claimed-docs] “Outbound webhooks are event calls from Penpot to other applications. They notify that some event occurred, e.g. a file has been created or u…”

   proof ↗⚑ flag

2. designerMy whole team can edit the same file simultaneously with live cursors and instant sync

   weight 3 · round to Figma
   Figma✓fullclaimed8/10

   Figma's docs directly describe multiplayer files with shared editing, cursor chat, and real-time collaboration ('Work together in multiplayer files... talk to your teammates with cursor chat in one shared space'; 'together in real-time and in one place'), matching the core story. Missing for 10: independent/hands-on verification of live-cursor sync at scale and no detail on conflict resolution or performance limits under heavy concurrent editing.

   • [claimed-docs] “Work together in multiplayer files, share feedback with comments, and talk to your teammates with cursor chat in one shared space.”
   • [claimed-docs] “Figma allows designers to create and prototype their digital experiences - together in real-time and in one place”
   • [claimed-docs] “Made for the big picture. Perfect down to every pixel.”

   proof ↗⚑ flag

   Penpot!disputedcontradicted4/10

   Vendor marketing implies real-time team collaboration ("Collaborate freely with unlimited teams") but the evidence pack contains no explicit documentation of live cursors or instant sync mechanics, and multiple hands-on reports describe multiplayer editing as crash-prone or unstable when several users work simultaneously on a file. Missing for 10: first-party docs describing live cursor presence/conflict resolution, latency/sync architecture details, and independent confirmation that simultaneous multi-user editing performs reliably at scale.

   • [claimed-docs] “Unlimited Teams - Collaborate freely with unlimited teams.”
   • [claimed-docs] “No file limits. Create as many as you need within your storage capacity. ... Unlimited Teams. Collaborate freely with unlimited teams.”
   • [community] “Unstable, very crash prone with just a few users designing 10 plus pages. And a huge memory hog too. I run it on Dedicated server with 64GB …”
   • [community] “I tried to self host penpot a few months ago but the app would crash after a few minutes and not properly show the canvases. So a no for me.”
   • [community] “I really wanted to like penpot, but when I tried a few months ago, simply navigating between pages (even on the example documents) was causi…”

   proof ↗⚑ flag

Design systems

1. designerManage design tokens or variables — colors, spacing, typography — with modes or themes applied across designs

   weight 2 · round to Figma
   Figma✓fullclaimed8/10

   Figma has native Variables with modes/themes for color, spacing, and typography, a dedicated Variables REST API for querying/creating/updating/deleting tokens and syncing design-system source of truth, and MCP tooling (get_variable_defs) that extracts variables and styles across selections; docs explicitly recommend using Figma variables for tokens across spacing, color, radius, and typography. Missing for 10: independent hands-on validation of multi-mode theming workflows and more detail on cross-file/library token publishing at scale.

   • [claimed-docs] “Sync design system source of truth to and from Figma”
   • [claimed-docs] “The Variables REST API includes endpoints for querying, creating, updating, and deleting variables.”
   • [claimed-docs] “`get_variable_defs` extracts the **variables and styles** used in your selection (color, spacing, typography, etc).”
   • [claimed-docs] “Use Figma variables for tokens. Apply variables for spacing, color, radius, and typography.”
   • [claimed-docs] “Pull in variables, components, and layout data directly into your IDE. This is especially useful for design systems and component-based work…”

   proof ↗⚑ flag

   Penpot~partialclaimed4/10

   Penpot explicitly advertises 'Design Tokens' and being a 'native design tokens' tool (penpot-docs-33, penpot-docs-13, penpot-docs-16), which directly supports token management for design-system alignment, but the evidence is only marketing tagline text with no detail on how modes/themes, multiple token sets, or per-property (color/spacing/typography) switching actually work. Components with linked instances (penpot-docs-11, penpot-docs-22) support consistency but aren't tokens/modes specifically, and no community/hands-on evidence corroborates the tokens feature's real-world robustness. Missing for 10: detailed documentation of token modes/themes switching, per-property (color/spacing/typography) token examples, and independent/hands-on confirmation that the tokens feature works as described.

   • [claimed-docs] “Design Tokens - Make design decisions that align designers and developers' workflows.”
   • [claimed-docs] “Make design decisions that align designers and developers' workflows.”
   • [claimed-docs] “Penpot vs Figma: Open-source alternative with self-hosting, unlimited files, native design tokens.”
   • [claimed-docs] “A component is a layer or group of layers that can be reused multiple times across files. This can help you maintain consistency across a gr…”
   • [claimed-docs] “All component copies used in a file are linked in a way that updates made to the Main component can reflect in their component copies.”

   proof ↗⚑ flag

2. designerBuild reusable components with variants and per-instance overrides that stay linked to their source

   weight 3 · round to Penpot
   Figma~partialclaimed3/10

   The evidence pack only points to a help-center article titled 'Guide to components in Figma' without any quoted content describing variants, per-instance overrides, or override-linking behavior; no other citation addresses this specific design-systems capability. Missing for 10: explicit documentation or examples of variant properties, instance override behavior, and how overrides remain linked to (and reset from) the main component.

   • [claimed-docs] “Guide to components in Figma”
   • [claimed-docs] “Translate designs into code”

   proof ↗⚑ flag

   Penpot~partialcommunity5/10

   Docs confirm reusable components with main/copy linkage that propagates updates (docs-11,22,23,35) and mention 'variants' as an extension (docs-41), but per-instance override mechanics are never detailed, and hands-on community feedback explicitly flags that variants/states handling is 'not on Figma's level yet' and components can feel 'difficult to handle' (penpot-comm-1, penpot-comm-9). missing for 10: documented per-instance override workflow, detailed variant creation/management docs, independent confirmation that variant/override linkage works robustly at scale.

   • [claimed-docs] “A component is a layer or group of layers that can be reused multiple times across files. This can help you maintain consistency across a gr…”
   • [claimed-docs] “All component copies used in a file are linked in a way that updates made to the Main component can reflect in their component copies.”
   • [claimed-docs] “If a main component has been deleted and you have access to a copy of it, you can use the copy to restore its main.”
   • [claimed-docs] “A component is a layer or group of layers that can be reused multiple times across files.”
   • [claimed-docs] “Extend components with variants—simpler to use, easier to control.”
   • [community] “Good: It is a good copy of figma's UI... Bad: In design systems particularly at variants and states of components, it is not on figma's leve…”
   • [community] “I've been toying a little with self hosted Penpot and it was really nice... Penpot was easy to use though it felt a little difficult to hand…”

   proof ↗⚑ flag

3. designerShared libraries publish components and styles across files and projects, with controlled updates when the source changes

   weight 2 · round drawn
   Figma~partialclaimed5/10

   Docs confirm centralized library/asset publishing across teams and departments (figma-docs-37, figma-docs-12) and a components guide (figma-docs-72), plus library usage analytics across files (figma-docs-55, figma-docs-75), but there is no explicit documentation in the pack of the update-notification/accept-update workflow when a library source component changes. missing for 10: explicit doc on component update propagation/notification workflow, independent/hands-on confirmation of controlled update behavior.

   • [claimed-docs] “Want to centralize assets, libraries, and workflows across departments”
   • [claimed-docs] “Publish resources across teams”
   • [claimed-docs] “Guide to components in Figma”
   • [claimed-docs] “Get summary information about how many instances of a library's components exist across all files.”
   • [claimed-docs] “Get time series data about what actions your users have performed with your library's components on a week-by-week basis.”
   • [claimed-docs] “Unlimited files and projects for a single team”

   proof ↗⚑ flag

   Penpot~partialcommunity5/10

   Docs confirm components as reusable linked elements where main-component edits propagate to copies (penpot-docs-22, penpot-docs-23, penpot-docs-35) and design-system features like tokens and variants (penpot-docs-33, penpot-docs-41), but there is no explicit documentation of publishing a library across separate files/projects or how updates propagate cross-project, and community feedback notes design-system/component sophistication lags Figma (penpot-comm-1, penpot-comm-9). missing for 10: explicit shared/library publishing workflow across files and projects, documentation of controlled update/accept-changes flow at library level, independent confirmation of cross-project sync reliability.

   • [claimed-docs] “All component copies used in a file are linked in a way that updates made to the Main component can reflect in their component copies.”
   • [claimed-docs] “If a main component has been deleted and you have access to a copy of it, you can use the copy to restore its main.”
   • [claimed-docs] “A component is a layer or group of layers that can be reused multiple times across files.”
   • [claimed-docs] “Design Tokens - Make design decisions that align designers and developers' workflows.”
   • [claimed-docs] “Extend components with variants—simpler to use, easier to control.”
   • [community] “Good: It is a good copy of figma's UI... Bad: In design systems particularly at variants and states of components, it is not on figma's leve…”
   • [community] “I've been toying a little with self hosted Penpot and it was really nice... Penpot was easy to use though it felt a little difficult to hand…”

   proof ↗⚑ flag

Handoff

1. developerDesigns map to production code — component-to-code mappings or direct design-to-code output I can actually ship

   weight 2 · round to Figma
   Figma~partialcommunity7/10

   Figma ships strong first-party dev-handoff tooling: Code Connect maps design system components directly to real production code snippets in Dev Mode (figma-gh-1, figma-gh-2, figma-docs-60), and the MCP server can generate code from selected frames, extract variables/component context, and even build into production (figma-docs-2, figma-docs-39, figma-docs-25, figma-docs-35). However, community evidence shows real friction shipping that code as-is — devs complain about receiving absolute-position CSS instead of usable layout code and needing manual/plugin workarounds for asset export (figma-comm-1, figma-comm-2, figma-comm-3), and advanced Dev Mode/MCP access is gated behind a paid tier (figma-comm-4, figma-docs-23). Missing for 10: independent hands-on validation that MCP/Code-Connect output is shippable without manual cleanup at scale, and confirmation that core code-mapping isn't paywalled behind Dev Mode license.

   • [github] “Figma's Dev Mode will display true-to-production code snippets from your design system instead of autogenerated code examples.”
   • [github] “Code Connect is a tool for connecting your design system components in code with your design system in Figma.”
   • [claimed-docs] “This guide helps you connect your React (or React Native) components with Figma components using Code Connect.”
   • [claimed-docs] “Select a Figma frame and turn it into code. Great for product teams building new flows or iterating on app features.”
   • [claimed-docs] “Code Connect keeps your generated code consistent with your codebase.”
   • [claimed-docs] “Turn your design into a code-backed prototype, or build it into production with Figma’s MCP server.”
   • [community] “I hate when figma just always gives me CSS for absolute positioning. Is there any way around that?”
   • [community] “Grabbing icons as individual SVGs is probably what takes me the longest going from design to code. I have to click on each asset, name it pr…”
   • [community] “Right Click the icon > Copy/Paste as > Copy as SVG. We use that and just paste it into the codebase. Also used a bulk export plugin that aut…”
   • [community] “2023: available for all users. 2024: separate license for Dev Mode. I guess Figma trying to get more paying customers... feel a bit Adobe vi…”
   • [claimed-docs] “Advanced Dev Mode inspection and MCP Server”

   proof ↗⚑ flag

   Penpot~partialclaimed6/10

   Penpot documents code-based design representation and an 'Inspect' feature exporting CSS/HTML/SVG/JSON that matches the design (penpot-docs-21/36), plus an MCP server letting AI agents read structured design files to generate implementation artifacts (penpot-docs-32, penpot-docs-40). However, this is inspection/AI-assisted code generation rather than a documented direct component-to-framework code mapping (e.g., to React/Vue components), and no independent/hands-on evidence confirms developers actually shipping this code in production. missing for 10: first-party or community evidence of production-ready component-to-code bindings (framework-specific), and independent verification that generated/inspected code is usable as-is in shipped products.

   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON as well as Penpot's open file for…”
   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON”
   • [claimed-docs] “In Penpot, design is expressed as code, so AI agents can easily read and interact with your design files creating high-fidelity artifacts.”
   • [claimed-docs] “Penpot enables plenty of AI workflows, from generating editable design structures to connecting product logic, tokens, and implementation.”
   • [github] “developers feel at home using Penpot, because design is expressed as code, enabling a direct translation and shipping products faster.”

   proof ↗⚑ flag

2. developerInspect any layer and get measurements, styles, assets, and code snippets (CSS/iOS/Android) without an editor seat

   weight 3 · round drawn
   Figma~partialcommunity5/10

   Figma's Dev Mode (figma-docs-64, figma-docs-23) and MCP tools like get_variable_defs (figma-docs-68) support extracting styles, variables, and code snippets, and Code Connect (figma-gh-1/3) provides true-to-production code snippets, with community confirmation of CSS export workflows (figma-comm-1/2/3). However, the evidence never explicitly confirms iOS/Android snippet generation, precise measurement tooling, or that Dev Mode access requires only a lower-cost seat rather than a full editor seat—figma-docs-23 even ties 'Advanced Dev Mode inspection' to a paid plan tier. missing for 10: explicit iOS/Android code snippet evidence, explicit seat-tier confirmation (dev seat vs editor seat), measurement/spec inspection detail beyond CSS.

   • [claimed-docs] “Development and design, connected at every step.”
   • [claimed-docs] “Advanced Dev Mode inspection and MCP Server”
   • [claimed-docs] “`get_variable_defs` extracts the **variables and styles** used in your selection (color, spacing, typography, etc).”
   • [github] “Figma's Dev Mode will display true-to-production code snippets from your design system instead of autogenerated code examples.”
   • [github] “Code Connect is a tool for connecting your design system components in code with your design system in Figma. When using Code Connect, Figma…”
   • [community] “I hate when figma just always gives me CSS for absolute positioning. Is there any way around that?”
   • [community] “Grabbing icons as individual SVGs is probably what takes me the longest going from design to code. I have to click on each asset, name it pr…”
   • [community] “2023: available for all users. 2024: separate license for Dev Mode. I guess Figma trying to get more paying customers... feel a bit Adobe vi…”

   proof ↗⚑ flag

   Penpot~partialclaimed5/10

   Penpot's docs confirm an inspect feature giving code that matches design (CSS, HTML, SVG, JSON), which covers measurements/styles/code snippets for web, but there is no evidence of iOS/Android-specific code snippet generation, and no explicit documentation confirming that viewers/inspectors can access this without a paid editor seat. missing for 10: iOS/Android code snippet support, explicit seat-free viewer/inspect access confirmation, asset-export detail in inspect mode.

   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON as well as Penpot's open file for…”
   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON”
   • [claimed-docs] “Unlimited Teams - Collaborate freely with unlimited teams.”
   • [claimed-docs] “No file limits - Create as many as you need within your storage capacity.”

   proof ↗⚑ flag

1. ai-native userDo everything through the API that I can do in the UI

   weight 2 · round drawn
   Figma~partialprobed5/10

   Figma exposes several APIs (REST API for reading objects/variables/webhooks, Plugin API for read/write of file contents, MCP server for writing to canvas and generating code/diagrams) that cover a large slice of UI functionality, but no evidence shows full parity — e.g. REST API is largely read/webhook-oriented, Plugin API requires running inside the editor UI rather than headless automation, and there's no documented API for things like commenting, team/project management, or prototyping interactions equivalent to the UI. missing for 10: comprehensive REST/plugin coverage of comments, prototyping settings and team administration, evidence of headless parity without plugin UI context, and independent confirmation that API-driven workflows match UI capability 1:1.

   • [claimed-docs] “This gives you the ability to do things such as view and extract any objects or layers, and their properties from files, get usage data, or …”
   • [claimed-docs] “The Plugin API supports both read and write access to Figma's editors, allowing developers to view, create, and modify the contents of files…”
   • [claimed-docs] “Create and modify native Figma content directly from your MCP client.”
   • [claimed-docs] “provides tools for reading designs out of Figma, writing designs into Figma, connecting designs to your codebase, and building generative pl…”
   • [claimed-docs] “The Variables REST API includes endpoints for querying, creating, updating, and deleting variables.”
   • [claimed-docs] “The Plugin API supports both **read** and **write** access to Figma's editors, allowing developers to view, create, and modify the contents …”
   • [probe] “official MCP server documented at https://developers.figma.com/docs/figma-mcp-server/”

   proof ↗⚑ flag

   Penpot~partialprobed5/10

   Penpot documents extensive API/plugin/MCP access (objects and properties, webhooks, access tokens, plugin system) suggesting broad programmatic control, but there's no explicit claim or evidence of full UI/API parity, and probes for an OpenAPI/swagger spec returned 404s, indicating the API surface isn't fully discoverable or documented as complete. missing for 10: explicit statement of full UI-API feature parity, a public OpenAPI/schema reference, and independent (community/hands-on) confirmation that all UI actions are scriptable via API.

   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [claimed-docs] “Our plugin system brings the flexibility that devs need to create and publish their own custom extensions.”
   • [claimed-docs] “Use access tokens as an alternative login authentication. They can allow an app to access Penpot's API.”
   • [claimed-docs] “Plugins (113+): Community plugin marketplace with accessibility, code, AI, and design system tools.”
   • [probe] “PROBE llms.txt: HTTP 404 at https://help.penpot.app/llms.txt”
   • [probe] “PROBE openapi: all candidate paths 404 (https://help.penpot.app/openapi.json, https://help.penpot.app/swagger.json, https://help.penpot.app/…”
   • [probe] “official MCP server documented at https://penpot.dev/ai/mcp-server”

   proof ↗⚑ flag

2. ai-native userExport all of my data in open formats and leave

   weight 3 · round to Penpot
   Figma!disputedcontradicted3/10

   Figma's REST API and Plugin API let you extract objects, layers, properties, and variables (figma-docs-7, figma-docs-26, figma-docs-49, figma-docs-62), suggesting some data portability, but this falls short of a genuine 'export all your data in open formats and leave' capability — designs remain in Figma's proprietary .fig format with no full-fidelity open-format export. A hands-on community report explicitly contradicts openness: 'your full fidelity work is locked up in a proprietary format' and you can't keep a fully up-to-date local copy without constant manual export (figma-comm-7). Missing for 10: an actual bulk/full-fidelity open-format export or documented data-portability/exit path, and no contradiction from independent sources.

   • [claimed-docs] “This gives you the ability to do things such as view and extract any objects or layers, and their properties from files, get usage data, or …”
   • [claimed-docs] “view and extract any objects or layers, and their properties from files, get usage data, or listen for events with webhooks”
   • [claimed-docs] “view and extract any objects or layers, and their properties from files”
   • [claimed-docs] “The Variables REST API includes endpoints for querying, creating, updating, and deleting variables.”
   • [community] “Not only is it weird that with Figma you don't get to keep a local file if you don't constantly export to keep your local copy up to date - …”

   proof ↗⚑ flag

   Penpot!disputedcontradicted5/10

   Penpot's docs promise open formats and no lock-in — the file format is open and design data can be inspected/exported as CSS, HTML, SVG and JSON, and self-hosting gives full data control (penpot-docs-21, penpot-docs-28, penpot-docs-38). However, a hands-on community report directly contradicts full-data export, stating the user 'had no way to export the diagram as one file like PDF or JPG. I could only export a layer' (penpot-comm-5), suggesting the practical export experience falls short of the 'export all my data and leave' promise. Missing for 10: independent confirmation of a full-project/all-files bulk export, verification that the open file format round-trips completely outside Penpot, and resolution of the community-reported export limitation.

   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON as well as Penpot's open file for…”
   • [claimed-docs] “Keep your data private. Penpot will never make business out of your data. Choose where and how to host it, and decide who has access to it.”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [community] “Maybe I'm using it wrong... when I tried Penpot about a year ago, I had no way to export the diagram as one file like PDF or JPG. I could on…”

   proof ↗⚑ flag

3. ai-native userRead the product's source under an open license

   weight 2 · round to Penpot
   Figma—none0/10

   Figma is a closed, proprietary commercial product; while some peripheral tools (Code Connect, REST API spec) are open-sourced on GitHub, there is no evidence the core Figma product/application source is available under an open license. Community feedback even notes work is 'locked up in a proprietary format,' reinforcing that the core product is closed-source.

   • [community] “Not only is it weird that with Figma you don't get to keep a local file if you don't constantly export to keep your local copy up to date - …”
   • [github] “Figma's Dev Mode will display true-to-production code snippets from your design system instead of autogenerated code examples.”
   • [github] “Code Connect is a tool for connecting your design system components in code with your design system in Figma.”
   • [claimed-docs] “This repository contains the OpenAPI specification and Typescript types for the Figma REST API”

   proof ↗⚑ flag

   Penpot~partialclaimed6/10

   Penpot is well known as open-source (GitHub repo referenced) and docs emphasize open standards, open file format, and self-hosting, which implies source availability, but the evidence pack lacks an explicit statement of the license type or direct pointer to license terms. missing for 10: explicit license name/terms (e.g. MPL-2.0) cited in docs, confirmation that full source (not just plugin API) is published under that license.

   • [github] “developers feel at home using Penpot, because design is expressed as code, enabling a direct translation and shipping products faster.”
   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON as well as Penpot's open file for…”
   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [claimed-docs] “Penpot vs Figma: Open-source alternative with self-hosting, unlimited files, native design tokens.”

   proof ↗⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round to Penpot
   Figma—none0/10

   Figma is a cloud SaaS product with no evidence of any self-hosted deployment option for the core design tool; evidence only covers cloud APIs, plugins, MCP server, and community complaints about proprietary lock-in (figma-comm-7), which actually underscores the lack of self-hosting.

   • [community] “Not only is it weird that with Figma you don't get to keep a local file if you don't constantly export to keep your local copy up to date - …”

   proof ↗⚑ flag

   Penpot✓fullcommunity8/10

   Penpot provides extensive first-party self-hosting documentation (Docker Compose, Kubernetes/Helm, on-prem, private cloud, 3-minute setup) and explicitly extends this to AI tooling by letting users deploy the MCP server in their own environment. Community reports corroborate real-world self-hosting via Docker/Portainer working, though some users report performance/stability issues at scale, which is a caveat rather than a failure of the self-hosting capability itself. Missing for 10: no first-party performance benchmarks or hardening guidance addressing the community-reported instability at scale.

   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”
   • [claimed-docs] “Deploy with docker compose... Use Kubernetes in its different flavors: Deploy the official Helm Chart”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “Keep your data private. Penpot will never make business out of your data. Choose where and how to host it, and decide who has access to it.”
   • [claimed-docs] “you can set up an instance of Penpot in just 3 minutes!”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [community] “I've been toying a little with self hosted Penpot and it was really nice... Penpot was easy to use though it felt a little difficult to hand…”
   • [community] “Have been self-hosting this on Docker/Portainer for several weeks for a few people. Works fine so far.”
   • [community] “I'm willing to pay the 'performance tax' of the web stack/self-hosting if it means my design files aren't held hostage in a proprietary clou…”

   proof ↗⚑ flag

Plugins

1. developerA documented plugin API with typings and samples lets me build and distribute my own editor extensions

   weight 2 · round to Figma
   Figma✓fullclaimed8/10

   Figma documents a full Plugin API with read/write access to editors, custom UI, and widgets, plus dedicated docs site (developers.figma.com/docs/plugins) and a marketplace for publishing/distributing plugins and widgets (public or private). Combined with the OpenAPI/TypeScript REST spec and Code Connect samples, this constitutes a documented, typed extensibility platform for developers. Missing for 10: explicit mention of TypeScript typings specifically for the Plugin API (typings confirmed only for REST API) and independent hands-on developer reviews of the plugin-building experience.

   • [claimed-docs] “The Plugin API supports both read and write access to Figma's editors, allowing developers to view, create, and modify the contents of files…”
   • [claimed-docs] “The Plugin API supports both **read** and **write** access to Figma's editors, allowing developers to view, create, and modify the contents …”
   • [claimed-docs] “You can build plugins that run immediately when invoked by the user, or that require users to input information via custom UI.”
   • [claimed-docs] “allowing developers to view, create, and modify the contents of files”
   • [claimed-docs] “Create private plugins and widgets to keep internal information and data safe.”
   • [claimed-docs] “Users and organizations take advantage of plugins to customize their experience and create more efficient workflows.”
   • [claimed-docs] “Automate tasks, add new functionality, and improve your workflow with plugins for everything from documentation to communication.”
   • [claimed-docs] “Unlike plugins that run for a specific person, everyone can see and interact with the same widget.”
   • [claimed-docs] “This repository contains the OpenAPI specification and Typescript types for the Figma REST API”

   proof ↗⚑ flag

   Penpot~partialclaimed5/10

   Docs confirm a dedicated plugin API/system ('Our plugin system brings the flexibility that devs need to create and publish their own custom extensions', 'Use community plugins or build your own') and a marketplace with 113+ community plugins, showing developers can and do build/distribute extensions. However, no evidence pack item shows actual typings, SDK reference docs, or code samples/tutorials for the plugin API itself. Missing for 10: documented TypeScript typings, published API reference/sample plugin code, and independent developer confirmation of using the plugin API to build an extension.

   • [claimed-docs] “Our plugin system brings the flexibility that devs need to create and publish their own custom extensions.”
   • [claimed-docs] “Plugins (113+): Community plugin marketplace with accessibility, code, AI, and design system tools.”
   • [claimed-docs] “Use community plugins or build your own.”

   proof ↗⚑ flag

2. designerExtend the editor from a large plugin community or marketplace — icons, data fillers, accessibility checkers, and more

   weight 2 · round to Figma
   Figma✓fullcommunity7/10

   Figma's Plugin API and Widget API docs explicitly support a broad plugin ecosystem for reading/writing files, building custom UI, and automating workflows 'from documentation to communication' (figma-docs-8, figma-docs-18, figma-docs-36, figma-docs-65), and independent hands-on community evidence confirms designers actually use third-party plugins (e.g., bulk SVG export/autonaming) in real workflows (figma-comm-3). Private plugin support for internal tooling is also documented (figma-docs-9). Missing for 10: explicit mention of a named 'Community/marketplace' browsing experience, plugin counts/scale, or concrete examples of accessibility-checker/data-filler plugins specifically.

   • [claimed-docs] “The Plugin API supports both read and write access to Figma's editors, allowing developers to view, create, and modify the contents of files…”
   • [claimed-docs] “Create private plugins and widgets to keep internal information and data safe.”
   • [claimed-docs] “Users and organizations take advantage of plugins to customize their experience and create more efficient workflows.”
   • [claimed-docs] “Automate tasks, add new functionality, and improve your workflow with plugins for everything from documentation to communication.”
   • [claimed-docs] “You can build plugins that run immediately when invoked by the user, or that require users to input information via custom UI.”
   • [claimed-docs] “Unlike plugins that run for a specific person, everyone can see and interact with the same widget.”
   • [community] “Right Click the icon > Copy/Paste as > Copy as SVG. We use that and just paste it into the codebase. Also used a bulk export plugin that aut…”

   proof ↗⚑ flag

   Penpot~partialcommunity6/10

   Docs confirm a plugin system and marketplace with 113+ plugins spanning accessibility, code, AI, and design-system tools, plus first-party docs on building custom extensions (penpot-docs-24, penpot-docs-5, penpot-docs-37). However, community feedback suggests the plugin ecosystem is still much smaller/younger than competitors' (penpot-comm-20 notes needing a 'bigger community' and missing pre-built element libraries), and there's no independent hands-on verification of marketplace breadth or quality. Missing for 10: independent reviews of specific popular plugins, marketplace UI/discovery evidence, and confirmation the 113+ figure reflects an actively curated, high-quality ecosystem rather than a small/early one.

   • [claimed-docs] “Plugins (113+): Community plugin marketplace with accessibility, code, AI, and design system tools.”
   • [claimed-docs] “Our plugin system brings the flexibility that devs need to create and publish their own custom extensions.”
   • [claimed-docs] “Use community plugins or build your own.”
   • [community] “Needs a bigger community. I know this project but still use Figma because in Figma I can simply use pre-created Elements from e.g. Ionic or …”

   proof ↗⚑ flag

Pricing

1. product managerPublished plan pricing makes seat types, tiers, and AI-feature gating clear before procurement

   weight 1 · round to Figma
   Figma~partialclaimed5/10

   Figma's public pricing page fragments show tier-gated features (e.g., 'Advanced Dev Mode inspection and MCP Server', 'Centralized admin tools', 'Publish resources across teams', 'Unlimited files and projects for a single team') and separate AI credit purchasing/allocation controls, indicating some AI-feature and tier gating is documented pre-purchase. However, the evidence pack lacks a full seat-type/tier comparison table, explicit per-seat pricing, or a clear breakdown of which AI features are included vs. add-on across each named plan (Starter/Professional/Organization/Enterprise), so the story is only partially supported. Missing for 10: explicit seat-type definitions, full tier-by-tier feature/price matrix, and clear enumeration of which AI capabilities are gated at each tier.

   • [claimed-docs] “Publish resources across teams”
   • [claimed-docs] “Centralized admin tools”
   • [claimed-docs] “Advanced Dev Mode inspection and MCP Server”
   • [claimed-docs] “Purchase AI credits for your whole team to share. Enable pay-as-you-go for flexibility or subscribe to save.”
   • [claimed-docs] “You have full control and visibility over how credits are allocated and used across your team.”
   • [claimed-docs] “Want to centralize assets, libraries, and workflows across departments”
   • [claimed-docs] “Unlimited files and projects for a single team”

   proof ↗⚑ flag

   Penpot—none0/10

   The evidence pack includes only scattered pricing-page fragments (unlimited teams, no file limits, community plugins) but no structured breakdown of seat types, plan tiers, or which AI features are gated behind specific plans. No pricing table, tier comparison, or AI-feature-gating disclosure is documented anywhere in the pack.

   • [claimed-docs] “Unlimited Teams - Collaborate freely with unlimited teams.”
   • [claimed-docs] “No file limits - Create as many as you need within your storage capacity.”
   • [claimed-docs] “No file limits. Create as many as you need within your storage capacity. ... Unlimited Teams. Collaborate freely with unlimited teams.”
   • [claimed-docs] “Use community plugins or build your own.”

   proof ↗⚑ flag

2. designerThe free tier supports real design work — usable editor and collaboration without a paid seat

   weight 2 · round to Penpot
   Figma—none0/10

   The evidence pack describes general Figma design/collaboration/prototyping capabilities (figma-docs-14, figma-docs-15, figma-docs-16) but nothing ties these specifically to the free tier vs. paid seats, and no pricing page excerpt enumerates what the free plan includes. One community note (figma-comm-4) even flags a trend of moving features (Dev Mode) behind paid licenses, but this doesn't confirm or deny free-tier usability for core design work either way.

   ⚑ flag

   Penpot~partialcommunity6/10

   Penpot's free tier documented as unlimited files and unlimited teams, and the core editor supports components, prototyping, and design tokens without gating behind a paid seat, which supports real collaborative design work. However, community reports raise concerns about performance/stability at scale (crashes, lag with many layers/pages) that could limit usability for complex real work, and there's no explicit pricing-page breakdown confirming free tier includes full collaboration features like comments/permissions. missing for 10: explicit free-tier feature/seat-limit breakdown from pricing page, independent confirmation that free tier collaboration (comments, real-time multiplayer) is unrestricted, and resolution of community-reported performance/stability issues affecting real design work.

   • [claimed-docs] “Unlimited Teams - Collaborate freely with unlimited teams.”
   • [claimed-docs] “No file limits - Create as many as you need within your storage capacity.”
   • [claimed-docs] “No file limits. Create as many as you need within your storage capacity. ... Unlimited Teams. Collaborate freely with unlimited teams.”
   • [claimed-docs] “Use community plugins or build your own.”
   • [claimed-docs] “A component is a layer or group of layers that can be reused multiple times across files. This can help you maintain consistency across a gr…”
   • [claimed-docs] “Penpot allows you to prototype interactions by connecting boards, which can act as screens.”
   • [community] “Unstable, very crash prone with just a few users designing 10 plus pages. And a huge memory hog too. I run it on Dedicated server with 64GB …”
   • [community] “I really wanted to like penpot, but when I tried a few months ago, simply navigating between pages (even on the example documents) was causi…”
   • [community] “Currently Penpot's performance starts dropping rapidly once you approach around 1000 layers. Most robust design systems I see run around 10-…”

   proof ↗⚑ flag

1. ai-native userChoose where my data is stored (region/residency)

   weight 2 · round to Penpot
   Figma—none0/10

   No evidence in the pack addresses data residency, regional storage options, or data localization controls for Figma; all evidence concerns design tools, MCP server capabilities, plugins, and collaboration features. Missing for 10: any mention of region selection, data residency commitments, or storage location controls.

   ⚑ flag

   Penpot✓fullclaimed7/10

   Penpot's self-hosting model directly delivers data residency choice: users can run Penpot in their own private cloud, on-premise, or any environment, giving full control over where data lives, and this extends to the MCP server which can also be self-deployed rather than routed through third-party clouds. Missing for 10: no first-party managed 'choose a region' feature for the SaaS-hosted offering, and no independent verification of self-hosting data-control claims beyond docs.

   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”
   • [claimed-docs] “Keep your data private. Penpot will never make business out of your data. Choose where and how to host it, and decide who has access to it.”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”
   • [claimed-docs] “you can set up an instance of Penpot in just 3 minutes!”

   proof ↗⚑ flag

2. ai-native userPrevent my data from being used to train AI models

   weight 3 · round to Penpot
   Figma—none0/10

   No evidence pack items address AI training data opt-out or data usage controls for AI model training; nothing about privacy settings, data processing agreements, or opt-out toggles is mentioned. This axis applies to Figma (a data-handling SaaS platform where AI training opt-out is a plausible policy), but no supporting evidence exists.

   ⚑ flag

   Penpot~partialclaimed6/10

   Penpot's self-host docs explicitly state 'Keep your data private. Penpot will never make business out of your data. Choose where and how to host it,' which directly addresses preventing data from being used for AI training by keeping it entirely under user control. However, this is a general privacy claim tied to self-hosting rather than an explicit AI-training opt-out policy or contractual clause, and there's no independent/third-party corroboration of this specific promise. missing for 10: explicit AI-training-specific policy/ToS language, independent verification of the no-training claim, and clarity on cloud-hosted (non-self-hosted) instance data usage.

   • [claimed-docs] “Keep your data private. Penpot will never make business out of your data. Choose where and how to host it, and decide who has access to it.”
   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”

   proof ↗⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round to Penpot
   Figma—none0/10

   No evidence pack items address data retention policies, deletion controls, or data lifecycle management for AI features; the pack covers MCP tooling, plugins, REST API, and collaboration features but nothing about retention/deletion settings for AI-native users. missing for 10: data retention policy documentation, deletion controls/APIs, AI data handling/opt-out settings, any admin controls for purging AI-processed data.

   ⚑ flag

   Penpot~partialclaimed4/10

   Penpot's self-hosting and 'keep your data private... decide where and how to host it' messaging (penpot-docs-28, penpot-docs-38) implies data control, and self-hosting inherently lets an org manage retention/deletion at the infrastructure level. However, there is no explicit documentation of data retention policies, file/version deletion mechanisms, or GDPR-style erasure APIs for AI-processed data. Missing for 10: explicit retention/deletion API or policy docs, confirmation of how MCP-accessed data is retained/purged, independent verification of deletion behavior.

   • [claimed-docs] “Keep your data private. Penpot will never make business out of your data. Choose where and how to host it, and decide who has access to it.”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”
   • [claimed-docs] “Deploy the MCP server in your own environment without relying on third-party clouds.”

   proof ↗⚑ flag

4. ai-native userOpt out of telemetry and usage tracking

   weight 2 · round drawn
   Figma—none0/10

   No evidence pack items address telemetry/usage-tracking opt-out settings or privacy controls of that kind; the evidence covers MCP server features, plugins, REST API, and admin/SCIM tools but nothing about disabling analytics or tracking for AI-native workflows.

   ⚑ flag

   Penpot—none0/10

   The evidence pack shows self-hosting and data-privacy marketing claims (e.g., 'Keep your data private,' 'never make business out of your data') but never mentions a specific telemetry/usage-tracking opt-out setting or configuration flag. Missing for 10: explicit documentation of a telemetry toggle or opt-out mechanism, confirmation of what usage data is collected, and any independent verification that self-hosted instances disable tracking by default.

   • [claimed-docs] “Keep your data private. Penpot will never make business out of your data. Choose where and how to host it, and decide who has access to it.”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”

   proof ↗⚑ flag

1. designerPrototypes can carry advanced behavior — animation between states, conditions or variables, scroll effects — to feel like the real product

   weight 1 · round to Figma
   Figma~partialclaimed5/10

   Figma's docs confirm high-fidelity, interactive, no-code prototyping and dedicated animation/motion tooling ([figma-docs-16],[figma-docs-33],[figma-docs-28]), supporting the 'feel like the real product' goal, but the evidence pack never explicitly documents prototyping-specific conditional logic, variables-driven interactions, or scroll-triggered effects (these are general Figma features not detailed here). Missing for 10: explicit documentation of conditions/variables used within prototype interactions, scroll-effect prototyping, and independent hands-on validation of these advanced behaviors.

   • [claimed-docs] “Figma's prototyping tools make it easy to build and share high-fidelity, no-code, interactive prototypes.”
   • [claimed-docs] “Figma’s prototyping tools make it easy to build and share high-fidelity, no-code, interactive prototypes.”
   • [claimed-docs] “Create precise animations, build out reusable motion systems, and ship dev-ready animations.”

   proof ↗⚑ flag

   Penpot—none0/10

   Evidence only shows basic board-to-board click interactions (penpot-docs-12, penpot-docs-14); nothing in the pack mentions animation/transition effects between states, conditional logic, variables, or scroll-triggered effects in prototypes. This is an applicable axis for a prototyping tool, but no evidence supports these advanced behaviors.

   • [claimed-docs] “Penpot allows you to prototype interactions by connecting boards, which can act as screens.”
   • [claimed-docs] “Design responsive and rules-based interfaces with wireframes, interactive prototypes, and CSS Grid and Flex layouts.”

   proof ↗⚑ flag

2. designerWire screens into clickable prototypes with triggers, transitions, and overlays — no code required

   weight 2 · round to Figma
   Figma✓fullcommunity9/10

   Figma's docs explicitly market native, no-code prototyping tools ('high-fidelity, no-code, interactive prototypes'), which per general product knowledge and the docs pages cover triggers, transitions, and overlays as core interaction-design features, corroborated by community praise for Figma's rapid feature growth in design/prototyping workflows. missing for 10: no explicit line-item mention of 'triggers/transitions/overlays' terminology or independent hands-on walkthrough of building a specific prototype flow.

   • [claimed-docs] “Figma's prototyping tools make it easy to build and share high-fidelity, no-code, interactive prototypes.”
   • [claimed-docs] “Figma’s prototyping tools make it easy to build and share high-fidelity, no-code, interactive prototypes.”
   • [claimed-docs] “With best-in-class layout tools, type tools, and more, you have full control over how you design.”
   • [community] “Over the last five years Illustrator has added no useful new features and XD has wandered with no clear direction. Meanwhile Figma has been …”

   proof ↗⚑ flag

   Penpot✓fullcommunity6/10

   Docs confirm board-to-board prototyping ("connect boards, which can act as screens") and marketing copy references "interactive prototypes"; a community user corroborates that "the prototype feature is working great." However, the evidence pack never details specific trigger types, transition/animation options, or overlay behavior, so the depth of the interaction model is unverified. Missing for 10: detailed documentation of trigger/transition/overlay options, hands-on walkthrough of prototyping fidelity, and independent reviews specifically praising or critiquing interaction complexity.

   • [claimed-docs] “Penpot allows you to prototype interactions by connecting boards, which can act as screens.”
   • [claimed-docs] “Design responsive and rules-based interfaces with wireframes, interactive prototypes, and CSS Grid and Flex layouts.”
   • [community] “It's really a fantastic tool, we are using it since several months in replacement of figma and Adobe XD. The prototype feature is working gr…”

   proof ↗⚑ flag

Canvas

1. designerFrames can behave responsively — auto layout, constraints, and grids resize designs the way real UIs flex

   weight 2 · round to Penpot
   Figma~partialclaimed2/10

   Evidence pack lacks any explicit mention of Figma's auto layout, constraints, or grid systems; the closest is a vague marketing line about 'best-in-class layout tools' which doesn't name the specific responsive-design mechanics the story describes. missing for 10: explicit docs on auto layout resizing behavior, constraint pinning, layout grids, and any hands-on corroboration of responsive frame behavior.

   • [claimed-docs] “With best-in-class layout tools, type tools, and more, you have full control over how you design.”

   proof ↗⚑ flag

   Penpot~partialclaimed5/10

   Penpot's marketing docs confirm CSS Grid and Flex layout support for responsive/rules-based interfaces (penpot-docs-14), but there is no detailed documentation of auto-layout resizing behavior, constraints on resize, or grid systems working the way native UI frameworks flex, and no independent/hands-on confirmation of these specific behaviors. Community evidence instead focuses on general performance/stability issues rather than confirming responsive layout fidelity. missing for 10: detailed docs on constraints-based resizing, auto-layout resize rules, hands-on validation that grids/flex truly mimic real UI responsiveness.

   • [claimed-docs] “Design responsive and rules-based interfaces with wireframes, interactive prototypes, and CSS Grid and Flex layouts.”
   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON as well as Penpot's open file for…”

   proof ↗⚑ flag

2. designerI get professional vector tools — pen and path editing, boolean operations, precise alignment — for real interface design work

   weight 3 · round to Figma
   Figma~partialclaimed4/10

   Figma's marketing copy claims 'best-in-class layout tools, type tools' and pixel-precise control (figma-docs-15, figma-docs-63), which implies strong vector design capability, but the evidence pack contains no specific documentation of pen/path tools, boolean operations, or precise alignment guides — these are core to the story but unevidenced here. Community comments focus on SVG export and Dev Mode licensing, not vector editing quality itself. Missing for 10: explicit docs/screenshots of pen tool and path editing, boolean operation (union/subtract/intersect) documentation, alignment/snapping tool documentation, and independent hands-on corroboration of vector editing precision.

   • [claimed-docs] “With best-in-class layout tools, type tools, and more, you have full control over how you design.”
   • [claimed-docs] “Made for the big picture. Perfect down to every pixel.”
   • [claimed-docs] “Create precise animations, build out reusable motion systems, and ship dev-ready animations.”

   proof ↗⚑ flag

   Penpot—none0/10

   The evidence pack covers AI/MCP integration, self-hosting, plugins, components, prototyping, and design tokens, but contains no documentation or hands-on mention of pen/path editing tools, boolean path operations, or precise alignment/snapping features. Community comments only compare general UI polish and performance to Figma without confirming these specific vector-editing capabilities.

   ⚑ flag

Files

1. designerExport production assets — PNG, SVG, PDF, and more — with per-layer presets, scales, and slices

   weight 2 · round to Figma
   Figma~partialcommunity4/10

   Community evidence confirms Figma supports exporting assets like SVGs (e.g., 'Copy as SVG', bulk export plugins) but only as a workaround with friction, not a documented first-party export panel with per-layer presets, scales, and slices. missing for 10: first-party docs describing the native Export panel, per-layer export presets, multiple-scale exports (1x/2x/3x), PDF export, and slice tool; independent confirmation these work smoothly without third-party plugins.

   • [community] “Grabbing icons as individual SVGs is probably what takes me the longest going from design to code. I have to click on each asset, name it pr…”
   • [community] “Right Click the icon > Copy/Paste as > Copy as SVG. We use that and just paste it into the codebase. Also used a bulk export plugin that aut…”

   proof ↗⚑ flag

   Penpot—none0/10

   The evidence pack contains no first-party documentation describing PNG/SVG/PDF export options, per-layer export presets, scale factors, or slices — the closest data point is a community comment noting an inability to export a whole file (only a single layer) in past testing, which is negative rather than supportive. No docs, help-center pages, or hands-on confirmation of this specific export feature set are present.

   • [community] “Maybe I'm using it wrong... when I tried Penpot about a year ago, I had no way to export the diagram as one file like PDF or JPG. I could on…”

   proof ↗⚑ flag

2. developerThe file format is open or documented, so my designs stay portable and toolable outside the vendor's editor

   weight 1 · round to Penpot
   Figma—none0/10

   Figma's native .fig file format itself is not published as an open or documented spec; the evidence pack offers only programmatic access surfaces (REST API, Plugin API, MCP server) rather than an open file-format specification, and community evidence explicitly states design work is 'locked up in a proprietary format' with no offline/local file portability without constant export.

   • [community] “Not only is it weird that with Figma you don't get to keep a local file if you don't constantly export to keep your local copy up to date - …”
   • [claimed-docs] “This gives you the ability to do things such as view and extract any objects or layers, and their properties from files, get usage data, or …”
   • [claimed-docs] “Leverage the power of our REST API to bring Figma into your external tools and products.”

   proof ↗⚑ flag

   Penpot✓fullclaimed8/10

   Penpot explicitly documents an open file format built on open standards (SVG, CSS, HTML, JSON) and is open-source itself, explicitly contrasting with Figma's proprietary format, plus REST/webhook APIs and plugin system for external tooling. Missing for 10: independent third-party corroboration that .penpot files are actually opened/edited by external tools, and no dedicated file-format spec page (llms.txt/openapi probes 404).

   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON as well as Penpot's open file for…”
   • [claimed-docs] “Inspect and integrate code that actually matches design. Enjoy open standards like CSS, HTML, SVG and JSON”
   • [claimed-docs] “Penpot vs Figma: Open-source alternative with self-hosting, unlimited files, native design tokens.”
   • [claimed-docs] “Get extensive access to objects and properties to enable external rendering, workflow automation, enhanced app functionality, and more.”
   • [github] “developers feel at home using Penpot, because design is expressed as code, enabling a direct translation and shipping products faster.”

   proof ↗⚑ flag

3. developerSelf-host the full design platform on my own infrastructure under an open-source license

   weight 2 · round to Penpot
   Figma—none0/10

   Figma is a proprietary, cloud-hosted SaaS platform; there is no evidence of an open-source license or self-hosting option for the full design platform—evidence even notes proprietary file format lock-in and cloud dependency. Community comments confirm files are locked in a proprietary format with no local self-hosted alternative.

   • [community] “Not only is it weird that with Figma you don't get to keep a local file if you don't constantly export to keep your local copy up to date - …”

   proof ↗⚑ flag

   Penpot!disputedcontradicted6/10

   Docs strongly document self-hosting (docker compose, Kubernetes/Helm/OpenShift/Rancher, private cloud/on-prem deployment, 'set up in 3 minutes', open-source positioning vs Figma) with no artificial file/team limits, which is exactly what this story asks for. However, hands-on community reports contradict the ease-of-self-hosting claim: one user says self-hosted instance 'crash after a few minutes and not properly show the canvases. So a no for me' and others report it being 'unstable, very crash prone... huge memory hog' under modest load, even as another reports self-hosting 'works fine so far.' Missing for 10: explicit confirmation of the open-source license terms/scope, independent security/production-readiness audit of self-hosted deployments, and resolution of the stability complaints reported by self-hosters.

   • [claimed-docs] “Run it in your private cloud, on-premise, or any environment you control.”
   • [claimed-docs] “Deploy with docker compose... Use Kubernetes in its different flavors: Deploy the official Helm Chart”
   • [claimed-docs] “Deploy with docker compose ... Use Kubernetes in its different flavors”
   • [claimed-docs] “you can set up an instance of Penpot in just 3 minutes!”
   • [claimed-docs] “Penpot is the only open-source design platform that is truly deployment agnostic. Run it in your private cloud, on-premise, or any environme…”
   • [community] “I've been toying a little with self hosted Penpot and it was really nice... Penpot was easy to use though it felt a little difficult to hand…”
   • [community] “I tried to self host penpot a few months ago but the app would crash after a few minutes and not properly show the canvases. So a no for me.”
   • [community] “Unstable, very crash prone with just a few users designing 10 plus pages. And a huge memory hog too. I run it on Dedicated server with 64GB …”
   • [community] “Have been self-hosting this on Docker/Portainer for several weeks for a few people. Works fine so far.”

   proof ↗⚑ flag

4. designerFull version history lets me name milestones, compare, and restore any earlier state of a file

   weight 2 · round to Figma
   Figma~partialclaimed3/10

   Only one citation confirms version history viewing exists (figma-docs-44), but the evidence pack contains no detail on naming milestones, comparing versions, or restoring earlier states. missing for 10: documentation on naming/labeling versions, comparing diffs between versions, restoring a file to an earlier state, and any independent/hands-on corroboration of these capabilities.

   • [claimed-docs] “View a file's version history”

   proof ↗⚑ flag

   Penpot—none0/10

   No evidence in the pack mentions version history, milestone naming, diffing/comparison, or restore-to-earlier-state functionality; only component/plugin/self-host/AI features are documented. missing for 10: any mention of file version history, snapshot naming, diff/compare tools, or restore capability.

   ⚑ flag