GrowthBook vs Unleash

Agent access

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

   weight 2 · round drawn
   GrowthBook✓fullprobed9/10

   A probe confirms llms.txt is live at docs.growthbook.io/llms.txt returning HTTP 200 with a structured index of 180 documentation pages, exactly matching the agent-oriented docs pattern; GrowthBook also documents an official MCP server for agent integration, reinforcing agent-friendliness. Missing for 10: no independent third-party confirmation of an agent successfully consuming llms.txt end-to-end beyond the probe.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.growthbook.io/llms.txt # GrowthBook Documentation - [Docs (180 pages)](https://docs.growthbook.io/…”
   • [claimed-docs] “Connect AI tools like Cursor, VS Code, and Claude to GrowthBook using the Model Context Protocol (MCP).”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “official MCP server documented at https://docs.growthbook.io/integrations/mcp”

   proof ↗⚑ flag

   Unleash✓fullprobed9/10

   Unleash publishes a working llms.txt (HTTP 200, with explicit AI-agent instructions for fetching Markdown) plus a documented, MCP-reachable docs endpoint, giving agents structured, agent-oriented documentation entry points. Missing for 10: independent (non-vendor) confirmation that third-party agents actually consume these successfully in the wild.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.getunleash.io/llms.txt # Unleash Documentation ## Instructions for AI Agents - For clean Markdown…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”
   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   GrowthBook✓fullprobed8/10

   GrowthBook supports headless/CI usage via self-hosted Docker Compose deployment, a full REST API, SDK Connection Endpoints for programmatic flag evaluation, and inline server-side experiments requiring no third-party requests — all scriptable without a UI. A runtime probe confirms a real keyless self-host create-and-evaluate loop via API/docker, demonstrating genuine automation capability. missing for 10: no explicit CI/CD pipeline example or GitHub Actions integration doc, and no evidence of a dedicated CLI tool for automation workflows.

   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “You can also run server-side experiments by using inline experiments directly with our SDK. This requires no 3rd party requests”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”

   proof ↗⚑ flag

   Unleash✓fullprobed8/10

   Unleash ships a self-hostable Docker image, a full Admin/Client API, and scoped API tokens designed for automation/SDKs rather than human UI use, and a hands-on probe confirms a complete keyless headless workflow (docker boot, flag creation via Admin API, evaluation via Client API) with no manual UI steps — exactly the CI/automation pattern the story asks for. missing for 10: no independent third-party CI pipeline example or official CI/CD docs page walking through pipeline integration.

   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”
   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”

   proof ↗⚑ flag

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

   weight 3 · round to GrowthBook
   GrowthBook✓fullprobed9/10

   GrowthBook documents an official MCP server that bridges AI tools (Cursor, VS Code, Claude) to GrowthBook via authenticated REST calls with Agent Skills/guardrails, and a runtime probe confirms the official npm package (@growthbook/mcp) completes a full stdio initialize handshake exposing read/write meta-tools. This is strong first-party plus hands-on evidence of a working official MCP server. Missing for 10: broader independent/community corroboration beyond the single runtime probe.

   • [claimed-docs] “Connect AI tools like Cursor, VS Code, and Claude to GrowthBook using the Model Context Protocol (MCP).”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “official MCP server documented at https://docs.growthbook.io/integrations/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”

   proof ↗⚑ flag

   Unleash✓fullprobed8/10

   Unleash documents an official MCP server (@unleash/mcp) that lets LLM-powered coding assistants create and manage feature flags following best practices, and a probe confirms the docs MCP endpoint completes a full handshake. missing for 10: independent/hands-on third-party validation of the flag-management MCP server itself (only the docs-MCP handshake was runtime-verified, not the @unleash/mcp flag server), and no evidence of broader community adoption reports.

   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”
   • [probe] “official MCP server documented at https://docs.getunleash.io/integrate/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”

   proof ↗⚑ flag

4. ai-native userUse an official CLI

   weight 2 · round drawn
   GrowthBook—none0/10

   The evidence pack documents SDKs, REST API, self-host Docker, and an official MCP server, but there is no mention anywhere of an official standalone CLI tool for GrowthBook. Since a platform like GrowthBook could plausibly ship a CLI, the axis applies, but with no supporting evidence the verdict is none.

   ⚑ flag

   Unleash—none0/10

   The evidence pack details SDKs, Admin API, MCP server, and Docker deployment, but no official CLI tool for Unleash is mentioned anywhere in the docs or GitHub materials.

   ⚑ flag

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

   weight 3 · round drawn
   GrowthBook✓fullprobed9/10

   GrowthBook documents a full REST API for interacting with the application (growthbook-docs-12), including a readonly SDK Connection Endpoint (growthbook-docs-20) and unauthenticated public endpoints (growthbook-docs-41), and a runtime probe confirms an actual API-driven create-and-evaluate loop (creating org, feature flag, SDK connection, and reading it back) worked end-to-end (growthbook-probe-rt-2). Missing for 10: a discoverable OpenAPI/swagger spec file (all candidate paths 404'd per growthbook-probe-2), which would make the API more machine-discoverable for agentic tooling.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”
   • [claimed-docs] “They are meant to be public and do not require authentication to view.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.growthbook.io/openapi.json, https://docs.growthbook.io/swagger.json, https://docs.growt…”

   proof ↗⚑ flag

   Unleash✓fullprobed9/10

   Unleash's Admin API is explicitly documented as providing comprehensive programmatic access to all resources, backed by scoped API tokens/keys, and this is corroborated by a hands-on probe showing a full keyless create-and-evaluate flag roundtrip via the Admin and Client APIs. This directly demonstrates AI-native drivability through a documented public API. Missing for 10: no independent third-party API client showcase beyond Unleash's own SDK/probe evidence.

   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”

   proof ↗⚑ flag

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

   weight 2 · round to Unleash
   GrowthBook~partialprobed5/10

   GrowthBook documents a read-only SDK Connection Endpoint that exposes only a subset of feature-flag data (least-privilege by design) and a full REST API, plus an 'Advanced access control' / 'Advanced permissioning' feature at higher pricing tiers, and the MCP server makes authenticated REST calls on behalf of an agent. However there is no explicit documentation of an admin flow for issuing a scoped, least-privilege API credential specifically for an AI agent (e.g., role-restricted API keys, token scoping UI, or agent-specific key generation). Missing for 10: documented API-key scoping/role assignment workflow, explicit agent-credential issuance guide, and evidence of granular per-tool permission limits for MCP/agent tokens beyond generic 'advanced access control' tier feature.

   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”
   • [claimed-docs] “They are meant to be public and do not require authentication to view.”
   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”

   proof ↗⚑ flag

   Unleash~partialprobed6/10

   Unleash supports scoped credentials generally: backend API tokens are scoped to specific projects and a single environment, frontend tokens are explicitly non-secret/least-privilege by design, and RBAC governs permissions; the official MCP flag-management server requires a PAT (a scoped credential) at startup, which is directly relevant to agent access. However, there's no explicit documentation of fine-grained, agent-specific credential scoping (e.g., read-only vs write scopes tailored for an AI agent) beyond project/environment granularity. Missing for 10: dedicated agent-credential scoping guide, granular permission scopes beyond project+environment, and independent confirmation of least-privilege PAT usage in agent workflows.

   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”
   • [claimed-docs] “Frontend tokens are not considered secret and are safe to expose client-side.”
   • [claimed-docs] “Unleash implements role-based access control on two levels”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”
   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”

   proof ↗⚑ flag

7. ai-native userBuild against official SDKs

   weight 2 · round to GrowthBook
   GrowthBook✓fullcommunity9/10

   GrowthBook ships 24 official language-specific SDKs (React, Python, Android, iOS, etc.) with documented quickstart code, local evaluation, targeting, and inline experiments, and this is corroborated by community hands-on reports of fast SDK integration. missing for 10: independent benchmarking across all 24 SDKs and more recent third-party validation beyond a single HN thread.

   • [github] “24 SDKs including React, Python, Android, and iOS.”
   • [claimed-docs] “Get GrowthBook feature flags and experiments running in your app in a few lines of code, then pick a language-specific SDK.”
   • [claimed-docs] “const showNewFeature = useFeatureIsOn("new-feature");”
   • [claimed-docs] “const showNewFeature = useFeatureIsOn("new-feature"); const buttonColor = useFeatureValue("button-color", "blue");”
   • [claimed-docs] “You can also run server-side experiments by using inline experiments directly with our SDK. This requires no 3rd party requests”
   • [community] “Been using GrowthBook for a few weeks now... I was shocked at how much setup time it took to get a simple feature flag into our app with oth…”
   • [community] “At Miggos we have implemented Growth book and we got FF and A/B in our Vue frontend in a few hours. Excited to see the progress of the platf…”

   proof ↗⚑ flag

   Unleash✓fullclaimed8/10

   Unleash documents official client/backend SDKs as the primary integration path (quickstart guide, API token docs distinguishing frontend/backend SDK scoping), which AI-native developers can build against directly. missing for 10: no independent/hands-on corroboration of SDK quality or breadth across languages, and no explicit SDK versioning/changelog evidence.

   • [claimed-docs] “Create your first feature flag** using the Unleash Admin UI. **Connect Unleash to your application** by integrating an SDK into your codebas…”
   • [claimed-docs] “use one of the client or backend SDKs to connect Unleash with your application”
   • [claimed-docs] “Create your first feature flag using the Unleash Admin UI. Connect Unleash to your application by integrating an SDK into your codebase.”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”
   • [claimed-docs] “Frontend tokens are not considered secret and are safe to expose client-side.”

   proof ↗⚑ flag

8. ai-native userSubscribe to events via webhooks

   weight 2 · round drawn
   GrowthBook—none0/10

   The evidence pack covers SDKs, REST API, MCP integration, self-hosting, and experimentation features but contains no mention of webhooks or event subscription mechanisms anywhere, so there is no evidence GrowthBook supports this capability.

   ⚑ flag

   Unleash—none0/10

   The evidence pack contains no mention of webhooks, event subscriptions, or push-based notification mechanisms anywhere in Unleash's docs, API overview, or integrations list — only SDKs, Admin/Client APIs, Edge caching, and MCP flag-management tools are documented.

   ⚑ flag

Agentic features

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

   weight 2 · round to GrowthBook
   GrowthBook~partialprobed4/10

   GrowthBook ships an official MCP server that lets AI tools like Cursor, VS Code, and Claude connect and make authenticated calls to pull experiment/feature data and get GrowthBook 'Agent Skills' workflows/guardrails, which can produce AI-generated insights and suggestions — this was verified working in a runtime probe. However, this capability lives entirely outside the product (in an external AI client) rather than as a native in-app AI insights feature; GrowthBook's own results UI only shows statistical outputs like 'Chance to Win', not LLM-generated narrative insights. Missing for 10: a native in-product AI insights/summarization feature surfaced in the GrowthBook UI itself, and evidence of automated suggestion-generation (e.g., 'this metric moved because X') without requiring an external MCP client.

   • [claimed-docs] “Connect AI tools like Cursor, VS Code, and Claude to GrowthBook using the Model Context Protocol (MCP).”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”
   • [claimed-docs] “Chance to Win" tells you the probability that the variation is better. Anything above 95%”

   proof ↗⚑ flag

   Unleash—none0/10

   Unleash's evidence covers feature flag management, impact metrics thresholds, and an MCP server that lets external LLM coding assistants create/manage flags — but nothing shows Unleash itself generating AI insights or suggestions from data inside the product (e.g., AI-driven rollout recommendations, anomaly analysis, or narrative summaries). The impact metrics feature is rule-based automation, not AI-generated insight, and the MCP server is for external agents to act on Unleash, not Unleash surfacing AI-generated analysis to users.

   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”
   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”

   proof ↗⚑ flag

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

   weight 2 · round to Unleash
   GrowthBook~partialprobed4/10

   GrowthBook has some automated background behaviors (automatic stale flag detection, ramp schedules, and 'safe rollouts' that presumably auto-guard rollouts), and its MCP server lets AI tools make authenticated calls to the product, but these are on-demand agent actions or passive detection features, not evidence of an AI agent configuring a persistent job that runs autonomously in the background on a schedule/trigger without human involvement. Missing for 10: a documented scheduler/trigger system for AI-configured autonomous jobs, evidence of MCP-driven automations persisting and executing unattended, and independent confirmation of any autonomous background workflow.

   • [claimed-docs] “GrowthBook can automatically detect these flags so you can clean them up.”
   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “Starter, plus: Visual editor Multi-arm bandits Safe rollouts Customizable dashboards Advanced permissioning Power calculator Premium support”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”

   proof ↗⚑ flag

   Unleash~partialprobed5/10

   Unleash documents metrics-driven automation — progressing rollout milestones or triggering safeguards (pause/disable) automatically when thresholds are crossed — which is a real background automation running without manual intervention, and its MCP integration lets AI agents create/manage flags. However this automation is narrowly scoped to release/rollout progression rather than a general-purpose agentic automation framework, and there's no evidence of scheduling arbitrary autonomous agent tasks beyond flag rollout safeguards. Missing for 10: evidence of broader autonomous task scheduling beyond rollout thresholds, independent corroboration of the impact-metrics automation working in production, and confirmation the MCP server itself can trigger these automations autonomously rather than just via API calls.

   • [claimed-docs] “Release management in Unleash helps you standardize, automate and safeguard your feature rollouts.”
   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”
   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   GrowthBook—none0/10

   GrowthBook documents an MCP server that lets external AI tools (Cursor, VS Code, Claude) connect to and query GrowthBook — this is the opposite direction (GrowthBook as a data/tool source for external assistants), not a built-in AI assistant living inside the GrowthBook product itself. No evidence anywhere in the pack shows an in-app chat/assistant feature for delegating tasks within GrowthBook's UI.

   • [claimed-docs] “Connect AI tools like Cursor, VS Code, and Claude to GrowthBook using the Model Context Protocol (MCP).”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “official MCP server documented at https://docs.growthbook.io/integrations/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”

   proof ↗⚑ flag

   Unleash—none0/10

   Unleash exposes an MCP server so external LLM coding assistants can manage flags (unleash-docs-7, unleash-probe-2, unleash-probe-rt-2), but this is the reverse of the story — it makes Unleash a tool for outside agents, not a built-in assistant living inside the Unleash product that users delegate tasks to. No evidence of an in-product AI assistant/chat feature for creating rollouts, analyzing flags, etc.

   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”
   • [probe] “official MCP server documented at https://docs.getunleash.io/integrate/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”

   proof ↗⚑ flag

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

   weight 2 · round to GrowthBook
   GrowthBook✓fullprobed8/10

   GrowthBook ships an official MCP server that bridges AI tools like Cursor, VS Code, and Claude to GrowthBook, loading 'Agent Skills' (workflows/guardrails) and making authenticated REST calls so users can operate flags/experiments via natural language in an AI client. A runtime probe confirms the official npm MCP server completes a full keyless handshake exposing read/write meta-tools covering the whole API, corroborating the docs' claims beyond marketing copy. Missing for 10: an end-to-end example of an actual natural-language command executing a real write action (only the handshake/tool-discovery was verified, not a full command-to-result flow) and independent (non-vendor) hands-on confirmation.

   • [claimed-docs] “Connect AI tools like Cursor, VS Code, and Claude to GrowthBook using the Model Context Protocol (MCP).”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “official MCP server documented at https://docs.growthbook.io/integrations/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”

   proof ↗⚑ flag

   Unleash✓fullprobed7/10

   Unleash ships an official MCP server (@unleash/mcp) documented to let LLM-powered coding assistants create and manage feature flags following best practices, and a probe confirms the docs' MCP endpoint completes a handshake, corroborating the integration is real and agent-reachable. Missing for 10: no independent/hands-on demonstration of the flag-management MCP server itself in use (only the docs MCP endpoint was probed), and it requires local setup with a PAT rather than being zero-config.

   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”
   • [probe] “official MCP server documented at https://docs.getunleash.io/integrate/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”

   proof ↗⚑ flag

Api quality

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

   weight 2 · round drawn
   GrowthBook—none0/10

   GrowthBook documents a REST API (growthbook-docs-12) but there is no evidence of an interactive, runnable API reference (e.g., Swagger/OpenAPI try-it console) — a direct probe for openapi/swagger specs returned 404 on all candidate paths, and no docs mention runnable code samples in an API explorer.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.growthbook.io/openapi.json, https://docs.growthbook.io/swagger.json, https://docs.growt…”

   proof ↗⚑ flag

   Unleash—none0/10

   The evidence pack shows Admin API docs and an MCP server for AI agents to manage flags, but nothing describes an interactive API reference (e.g., Swagger/OpenAPI explorer) with runnable/try-it-out examples. This is a fair capability to expect from an API-driven product, but no evidence supports it.

   ⚑ flag

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

   weight 2 · round drawn
   GrowthBook—none0/10

   While GrowthBook documents a full REST API (growthbook-docs-12) and an SDK Connection Endpoint (growthbook-docs-20), the evidence pack shows an explicit probe for OpenAPI/Swagger spec files at expected paths that all returned 404, and no other evidence surfaces a downloadable OpenAPI or machine-readable spec.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.growthbook.io/openapi.json, https://docs.growthbook.io/swagger.json, https://docs.growt…”

   proof ↗⚑ flag

   Unleash—none0/10

   The evidence pack describes Unleash's Admin API as providing 'comprehensive programmatic access to all Unleash resources' but never mentions an OpenAPI/Swagger spec, schema file, or any downloadable machine-readable API definition. Missing for 10: explicit mention of an OpenAPI/Swagger document, a spec download endpoint, or documentation confirming machine-readable API schema availability.

   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”

   proof ↗⚑ flag

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

   weight 1 · round to GrowthBook
   GrowthBook✓fullprobed8/10

   GrowthBook supports separate environments (dev/staging/production) for feature flags, self-hosting via Docker Compose for a fully isolated instance, and a verified runtime probe confirms a keyless self-host roundtrip creating and evaluating flags without any production account/license — enabling true sandbox testing. missing for 10: no explicit vendor guidance on a dedicated 'sandbox mode' distinct from staging environments, and no independent (non-vendor) confirmation of environment data isolation guarantees.

   • [claimed-docs] “Use environments such as dev, staging, and production to enable or disable feature flags independently.”
   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”

   proof ↗⚑ flag

   Unleash✓fullprobed7/10

   Unleash's environments concept explicitly supports enabling flags in development/test without affecting production (unleash-docs-21, unleash-docs-10), and a hands-on probe confirms a full self-hosted Docker instance can be spun up locally with its own Postgres, tokens, and flag create/evaluate loop entirely separate from any production account (unleash-probe-rt-1). This gives an AI-native user a genuine sandbox path via self-hosting plus environment isolation. Missing for 10: no dedicated 'sandbox mode' or ephemeral test-environment feature purpose-built for AI agents, and no independent (non-vendor) corroboration of the environment-isolation guarantees in production use.

   • [claimed-docs] “This allows you to enable a flag in development or test without enabling it in production.”
   • [claimed-docs] “Environments represent different stages in your development lifecycle. They allow you to manage your product releases from local development…”
   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   GrowthBook—none0/10

   GrowthBook documents a REST API and SDK Connection Endpoint, but no evidence pack item describes API versioning scheme or a documented deprecation policy; the openapi/swagger probe returned 404s, suggesting no formal API spec is even discoverable. Missing for 10: any mention of API version numbers, backward-compatibility guarantees, or a deprecation/sunset policy.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.growthbook.io/openapi.json, https://docs.growthbook.io/swagger.json, https://docs.growt…”

   proof ↗⚑ flag

   Unleash—none0/10

   The evidence pack documents the Admin API, tokens, and SDKs but contains no mention of API versioning scheme or a documented deprecation policy for Unleash's APIs. Missing for 10: any documentation of API version numbers, changelogs, or deprecation/sunset policy for endpoints or SDKs.

   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”

   proof ↗⚑ flag

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

   weight 2 · round to GrowthBook
   GrowthBook~partialprobed5/10

   GrowthBook exposes a full REST API (growthbook-docs-12) and an official MCP server that bridges AI tools to authenticated REST read/write calls across the whole API (growthbook-docs-21, growthbook-probe-rt-1), which could let an AI agent script operations across many flags/experiments programmatically. However, there is no documented bulk-specific endpoint, batch-update tool, or example of performing many-item operations in one call. Missing for 10: explicit bulk-create/bulk-update API endpoints, documented batch operation examples, and evidence of the MCP server or API actually handling many items in a single request rather than one-at-a-time calls.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”

   proof ↗⚑ flag

   Unleash~partialclaimed3/10

   The Admin API is described as providing 'comprehensive programmatic access to all Unleash resources,' which implies scripting could achieve bulk create/update flows, but no evidence documents an explicit bulk-operations feature (e.g., batch enable/disable, bulk import/export, multi-select actions in UI) beyond a vague pricing-page mention of 'export/import feature flags for easy migration.' missing for 10: explicit bulk-update/bulk-tagging API endpoints, UI multi-select bulk actions, and any hands-on demonstration of operating on many items in one call.

   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [claimed-docs] “Export/import feature flags for easy migration”

   proof ↗⚑ flag

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

   weight 3 · round to Unleash
   GrowthBook~partialclaimed5/10

   GrowthBook lets users define feature-flag 'rules' that automatically apply based on targeting conditions, scheduling, and ramping (docs-22, docs-28, docs-2), and has automated stale-flag detection (docs-4) — these are rule-based automations tied to feature evaluation. However, this falls short of a general 'on event X, trigger action Y' automation engine; there's no evidence of webhook-driven arbitrary actions, external event ingestion, or an automation/workflow layer beyond flag targeting and rollout scheduling. Missing for 10: generic event-trigger/webhook automation outside feature-flag context, evidence of arbitrary action execution on external events, and independent corroboration of rule automation depth.

   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees.”
   • [claimed-docs] “GrowthBook can automatically detect these flags so you can clean them up.”
   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees. Conditions are evaluated against attributes you pass into the SDK”

   proof ↗⚑ flag

   Unleash~partialclaimed6/10

   Unleash's impact-metrics feature lets users define threshold-based rules that automatically trigger actions — progressing rollouts, pausing on latency/error-rate breaches, or disabling environments — which is genuine event-triggered automation ([unleash-docs-14],[unleash-docs-22],[unleash-docs-29]). However this is scoped narrowly to rollout safeguards rather than a general-purpose rule/event engine for arbitrary actions across the system. Missing for 10: evidence of a broader rule-definition system covering non-rollout events/actions, and independent confirmation the automation works reliably in practice.

   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”
   • [claimed-docs] “Release management in Unleash helps you standardize, automate and safeguard your feature rollouts.”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round drawn
   GrowthBook—none0/10

   Evidence only shows one-time scheduling of feature-flag rule start/stop dates and 'ramp schedules' for gradual rollouts (growthbook-docs-22, growthbook-docs-37) — nothing resembling recurring cron-like jobs or workflow automation that an AI-native user could schedule to run repeatedly. No mention of scheduled reports, recurring experiment analyses, or workflow automation triggers.

   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”

   proof ↗⚑ flag

   Unleash—none0/10

   Unleash supports one-time scheduled feature releases (specific date/time) and conditional automation of rollout milestones/pauses based on metrics, but there is no evidence of recurring/cron-style job scheduling or workflow automation that repeats on an interval.

   • [claimed-docs] “to release a feature at a specific date and time** (for a product launch, for instance)”
   • [claimed-docs] “to release a feature at a specific date and time (for a product launch, for instance)”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”

   proof ↗⚑ flag

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

   weight 1 · round to GrowthBook
   GrowthBook~partialcommunity6/10

   GrowthBook documents draft feature revisions, request-review, merge-conflict resolution, and required approval before publishing (docs-5, docs-22), and lists approval workflows plus exportable audit logs as paid-tier features (docs-37), which together enable versioning and review of flag/automation changes. However, no explicit rollback mechanism is documented and there's no independent/hands-on corroboration of the revision-history or rollback UI; a community comment even suggests config-as-code/git-based versioning isn't natively supported (growthbook-comm-11). Missing for 10: explicit rollback documentation, hands-on verification of revision history UI, and clarity on git-based config versioning.

   • [claimed-docs] “Draft feature revisions, request review, resolve merge conflicts, and require approval before publishing.”
   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [community] “From the looks of it, it doesn't look like the configuration can be stored in the code repository itself. This is one of the key things to d…”

   proof ↗⚑ flag

   Unleash~partialclaimed5/10

   Unleash's 'automations' are feature-flag rollouts: change requests provide a review/approval step before changes go live (docs-11), and flags can be toggled or reverted instantly without redeploying (docs-18), giving a rollback-like mechanism, plus RBAC constrains who can change what (docs-12). However there is no evidence of an explicit version-history/audit trail or diff view for flag configuration changes, only approval gating and on/off toggling. Missing for 10: documented changelog/audit-log of flag config versions, explicit 'rollback to previous version' feature, and independent confirmation of change-request review workflow in practice.

   • [claimed-docs] “Change requests allow you to require an additional approval step before any changes can be made in an environment.”
   • [claimed-docs] “They allow you to enable and disable features for certain users without having to redeploy your application.”
   • [claimed-docs] “Unleash implements role-based access control on two levels”
   • [claimed-docs] “Release management in Unleash helps you standardize, automate and safeguard your feature rollouts.”

   proof ↗⚑ flag

Proxy

1. platform engineerRun a relay/edge proxy so flags stay served when the vendor is unreachable and SDK traffic stays inside my network

   weight 1 · round to GrowthBook
   GrowthBook✓fullcommunity9/10

   GrowthBook explicitly documents a self-hostable Proxy that runs next to your app to cache SDK payloads, reduce latency, and keep serving flags if the API is down, directly matching the relay/edge proxy story, and this sits alongside full self-host Docker Compose deployment keeping SDK traffic in-network. Community evidence corroborates that evaluation happens locally within SDKs via a cacheable JSON payload, reinforcing offline resilience. Missing for 10: independent hands-on report specifically of the Proxy component (vs. general self-host) failing over during an outage.

   • [claimed-docs] “Run the GrowthBook Proxy next to your app to cache SDK payloads, reduce latency, and keep serving flags if the API is down.”
   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”
   • [community] “With GrowthBook, there's a single cacheable JSON definition of all of the features and then evaluation happens locally within the SDKs... Th…”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”

   proof ↗⚑ flag

   Unleash✓fullclaimed8/10

   Unleash Edge (open source) and Unleash Enterprise Edge are documented as a lightweight caching/relay layer that sits between SDKs and the Unleash server, acting as a read replica that can serve thousands of SDKs and improve resilience — keeping SDK traffic local and flags served even if the vendor/backend is unreachable. Self-hosting via Docker is also documented, reinforcing the on-network deployment model. Missing for 10: independent/hands-on validation of Edge's offline-resilience behavior and more detail on failover semantics beyond docs claims.

   • [claimed-docs] “functioning as a read replica that can handle thousands of connected SDKs without increasing the read load on your primary Unleash instance”
   • [claimed-docs] “Unleash Enterprise Edge is a lightweight caching layer designed to improve scalability, performance, and resilience.”
   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”

   proof ↗⚑ flag

Self host

1. platform engineerSelf-host the full flag platform from an open-source distribution, keeping evaluation data on my infrastructure

   weight 3 · round drawn
   GrowthBook✓fullprobed9/10

   GrowthBook documents a self-host distribution via Docker Compose (MongoDB, API, front-end) and this is corroborated by a hands-on probe showing a full keyless self-host boot, feature creation, and SDK payload evaluation working end-to-end on local infrastructure, plus community confirmation of production self-hosted usage. missing for 10: independent third-party audit of data residency guarantees beyond vendor docs/probe.

   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”
   • [community] “Growthbook is awesome! We have used the self-hosted version a few months in my company now, and are very happy about it. Talented people beh…”

   proof ↗⚑ flag

   Unleash✓fullprobed9/10

   Docs explicitly describe deploying Unleash Open Source via Docker in your own environment, and a hands-on probe confirms a full keyless self-hosted flag create-and-evaluate loop using the official unleash-server image against Postgres with no external account, demonstrating evaluation data stays on the operator's infrastructure. missing for 10: no independent third-party production case study of long-term self-hosted operation at scale.

   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”
   • [github] “Feature flags in Unleash let you test your code with real production data, reducing the risk of negatively impacting your users' experience.”

   proof ↗⚑ flag

Agent ops

1. ai agentRead experiment configurations and results programmatically to summarize outcomes and recommend ship/rollback decisions

   weight 1 · round to GrowthBook
   GrowthBook✓fullprobed8/10

   GrowthBook exposes a full REST API and an official MCP server that makes authenticated calls to that API, explicitly loading 'Agent Skills (workflows and guardrails)' so AI tools can query feature/experiment data — confirmed working end-to-end in a runtime probe. Experiment results expose statistical decision signals like 'Chance to Win' (>95% highlighted as a clear winner) that directly support ship/rollback recommendations, and metrics/fact-table docs show how results are computed from stored data for programmatic reading. Missing for 10: a concrete worked example of an agent actually generating a ship/rollback summary via MCP, and independent (non-vendor) confirmation of recommendation quality.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “Connect AI tools like Cursor, VS Code, and Claude to GrowthBook using the Model Context Protocol (MCP).”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [claimed-docs] “Chance to Win" tells you the probability that the variation is better. Anything above 95%”
   • [claimed-docs] “Chance to Win tells you the probability that the variation is better. Anything above 95% ... is highlighted green indicating a very clear wi…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”
   • [probe] “official MCP server documented at https://docs.growthbook.io/integrations/mcp”

   proof ↗⚑ flag

   Unleash~partialprobed5/10

   Unleash exposes a comprehensive Admin API for programmatic access to flags, variants, and impact metrics (thresholds, error-rate pausing) that an agent could poll to gauge rollout health, and an official MCP server lets LLM agents manage flags. However, evidence shows the MCP server is scoped to 'create and manage feature flags' rather than reading experiment results/outcomes or generating ship/rollback recommendations, and no docs describe an agent-facing results-summary or decision-recommendation workflow. missing for 10: explicit API/MCP support for reading experiment results/outcome data, and any documented agent workflow that summarizes outcomes or recommends ship/rollback decisions.

   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”
   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the docs MCP endpoint https://docs.getunleash.io/_mcp/server completed a FULL keyless initialize handsh…”
   • [claimed-docs] “Variants let you expose different versions of a feature to users, for example, as part of A/B and multivariate testing.”

   proof ↗⚑ flag

Analysis

1. product managerTrust a documented statistics engine (Bayesian or frequentist, with variance-reduction options) behind experiment results

   weight 2 · round to GrowthBook
   GrowthBook✓fullcommunity9/10

   GrowthBook documents both Bayesian and Frequentist statistics engines with explicit UI outputs like 'Chance to Win', and its GitHub/community materials detail variance-reduction and rigor features (CUPED, Sequential testing, Post-Stratification, SRM checks) plus rationale for choosing Bayesian to mitigate peeking/Type I error. This is corroborated by both official docs and first-party community explanation, giving a PM strong documented trust in the underlying stats methodology; missing for 10: independent third-party statistical audit or academic validation of the engine's correctness.

   • [claimed-docs] “What you will see will depend a little bit on whether you are using our Bayesian or our Frequentist engine”
   • [claimed-docs] “Chance to Win" tells you the probability that the variation is better. Anything above 95%”
   • [claimed-docs] “Chance to Win tells you the probability that the variation is better. Anything above 95% ... is highlighted green indicating a very clear wi…”
   • [github] “World class experiment stats engine (CUPED, Sequential, Bayesian, Post-Strat, Bandits, SRM checks).”
   • [github] “🆎 World class experiment stats engine (CUPED, Sequential, Bayesian, Post-Strat, Bandits, SRM checks).”
   • [community] “We use a Bayesian statistics engine which is much more immune to peeking problems and Type I errors than frequentist approaches.”

   proof ↗⚑ flag

   Unleash—none0/10

   Unleash's docs mention 'impact metrics' for pausing/progressing rollouts based on thresholds, but there is no evidence of a documented statistics engine (Bayesian/frequentist), significance testing, confidence intervals, or variance-reduction techniques (e.g., CUPED) behind experiment/variant results. A Hacker News comment even notes Unleash's rule system is more limited than competitors, but this doesn't address the statistics engine specifically. missing for 10: any mention of a named statistical methodology, significance/power calculations, confidence intervals, or variance-reduction options for A/B test analysis.

   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”
   • [claimed-docs] “Variants let you expose different versions of a feature to users, for example, as part of A/B and multivariate testing.”
   • [community] “Many open source solutions (Unleash, last I checked, some time ago) are more limited: some of th[e]... [compared to LaunchDarkly's more flex…”

   proof ↗⚑ flag

Experiments

1. product managerRun A/B and multivariate experiments on flags and see which variation wins on my metrics

   weight 3 · round to GrowthBook
   GrowthBook✓fullcommunity8/10

   GrowthBook natively supports A/B and multivariate experiments attached to feature flags, with statistical engines (Bayesian/Frequentist, CUPED, Sequential, Bandits), templates for goal/secondary/guardrail metrics, and a results view showing 'Chance to Win' per variation to determine winners. Community reports corroborate quick setup and real-world use of feature flags plus A/B testing, though some note a gap between flags and full analytics requiring warehouse/metrics setup. missing for 10: independent hands-on validation of multivariate (>2 arm) experiment results and winner-declaration workflow specifically, beyond docs and community anecdotes.

   • [claimed-docs] “GrowthBook has a few different ways to run experiments or AB tests depending on your needs.”
   • [claimed-docs] “What you will see will depend a little bit on whether you are using our Bayesian or our Frequentist engine”
   • [claimed-docs] “Selecting a Template in the creation modal pre-fills settings like the data source, goal/secondary/guardrail metrics, targeting, and traffic”
   • [claimed-docs] “Define Fact Tables and metrics so GrowthBook can compute experiment results from your warehouse.”
   • [claimed-docs] “Chance to Win" tells you the probability that the variation is better. Anything above 95%”
   • [claimed-docs] “Run A/B tests with feature flags, the Visual Editor, URL redirects, or your own assignment, then analyze results in GrowthBook.”
   • [claimed-docs] “you can add an experiment rule to a feature that will randomly assign the users based on some hashing attribute into one of your experiment …”
   • [github] “World class experiment stats engine (CUPED, Sequential, Bayesian, Post-Strat, Bandits, SRM checks).”
   • [community] “With GrowthBook, there's a single cacheable JSON definition of all of the features and then evaluation happens locally within the SDKs... Th…”
   • [community] “We use a Bayesian statistics engine which is much more immune to peeking problems and Type I errors than frequentist approaches.”

   proof ↗⚑ flag

   Unleash~partialclaimed5/10

   Unleash documents 'variants' explicitly for A/B and multivariate testing (unleash-docs-8) and has 'impact metrics' that can gate/automate rollout progression based on threshold metrics (unleash-docs-14, unleash-docs-22, unleash-docs-29), giving PMs some data-driven feedback loop on flag variations. However, there is no evidence of a dedicated experimentation dashboard, statistical significance/winner-declaration reporting, or goal-metric comparison across variants akin to a full A/B testing suite. Missing for 10: statistical significance engine, experiment results/winner dashboard, and metric-goal configuration UI tied directly to variant performance.

   • [claimed-docs] “Variants let you expose different versions of a feature to users, for example, as part of A/B and multivariate testing.”
   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”

   proof ↗⚑ flag

Metrics

1. product managerDefine experiment metrics from my own data — warehouse tables or ingested events — instead of a black-box metric store

   weight 2 · round to GrowthBook
   GrowthBook✓fullcommunity8/10

   GrowthBook explicitly lets teams define Fact Tables and metrics computed directly from their own warehouse (BigQuery, Snowflake, Databricks, etc.) rather than relying on a proprietary metric store, and independent community commentary confirms this warehouse-native design as a key differentiator from black-box tools like Optimizely. missing for 10: hands-on PM-level walkthrough of defining a metric from ingested event data (vs. warehouse tables) and any independent report specifically validating metric-definition UX.

   • [claimed-docs] “Define Fact Tables and metrics so GrowthBook can compute experiment results from your warehouse.”
   • [github] “Warehouse Native. Query 11 data sources including BigQuery, Snowflake, and Databricks.”
   • [github] “❄️ Warehouse Native. Query 11 data sources including BigQuery, Snowflake, and Databricks.”
   • [community] “Re: Eppo - they're similar in setup but Growthbook is open source with an optional cloud SaaS offering. Optimizely is a walled garden, you n…”
   • [community] “a guide in your docs on how to use this with Matomo would go far. Growthbook provides Feature Flag and A/B Testing, but you have to bring yo…”

   proof ↗⚑ flag

   Unleash—none0/10

   The axis applies to this product kind (peer products hold positive or none verdicts on this story), so lack of evidence for an applicable capability is "none", never "na". (na/none harmonized at arena bring-up — see pipeline/scripts/na-harmonize.ts.)

   ⚑ flag

Environments

1. developerManage separate environments (dev/staging/prod) with independent flag states and scoped SDK keys

   weight 2 · round to Unleash
   GrowthBook✓fullprobed8/10

   Docs explicitly describe dedicated environments (dev/staging/production) with independently toggled flag states [growthbook-docs-3], and the SDK Connection Endpoint provides scoped, readonly keys per environment for SDKs [growthbook-docs-20], with runtime probes confirming a real create-flag/scoped-key/evaluate loop [growthbook-probe-rt-2]. Custom environments are also called out as a paid-tier feature, confirming the capability exists in-product [growthbook-docs-16, growthbook-docs-37]. Missing for 10: independent/community verification specifically of environment-scoped SDK key isolation (evidence is docs/probe only, not third-party confirmation) and more detail on default-environment limits on lower tiers.

   • [claimed-docs] “Use environments such as dev, staging, and production to enable or disable feature flags independently.”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”

   proof ↗⚑ flag

   Unleash✓fullprobed9/10

   Unleash's docs explicitly describe environments as distinct stages (dev/staging/prod) with independent flag states per environment, and API tokens/keys are scoped to specific project(s) and a single environment, satisfying both independent state and scoped SDK keys. Missing for 10: independent third-party corroboration of multi-environment isolation beyond docs/probe.

   • [claimed-docs] “Environments represent different stages in your development lifecycle. They allow you to manage your product releases from local development…”
   • [claimed-docs] “This allows you to enable a flag in development or test without enabling it in production.”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”

   proof ↗⚑ flag

Flags

1. developerCreate a feature flag and toggle it live in production within minutes of signing up

   weight 3 · round drawn
   GrowthBook✓fullprobed9/10

   GrowthBook's quickstart docs show flag creation in a few lines of code with SDK hooks like useFeatureIsOn, and a runtime probe confirms a real keyless create-and-evaluate loop (create org, create flag, mint SDK connection, get correct value back) with no signup friction. Independent community testimony corroborates fast setup, with one user reporting a working flag in about 15 minutes and under 10 lines of code, and environments docs confirm dev/staging/prod toggling. missing for 10: a first-party or independent account of toggling a flag live specifically in a production environment end-to-end.

   • [claimed-docs] “Get GrowthBook feature flags and experiments running in your app in a few lines of code, then pick a language-specific SDK.”
   • [claimed-docs] “const showNewFeature = useFeatureIsOn("new-feature");”
   • [claimed-docs] “Use environments such as dev, staging, and production to enable or disable feature flags independently.”
   • [community] “Been using GrowthBook for a few weeks now... I was shocked at how much setup time it took to get a simple feature flag into our app with oth…”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”

   proof ↗⚑ flag

   Unleash✓fullprobed9/10

   Docs show a clear quickstart flow: create a feature flag in the Admin UI, connect an SDK, and toggle it via activation strategies without redeploying — and a runtime probe confirms an actual create-flag-and-evaluate loop working end-to-end within minutes on a fresh self-hosted instance. Missing for 10: independent third-party account of a brand-new signup-to-production toggle timing (only a self-hosted probe, not hosted SaaS signup, is verified).

   • [claimed-docs] “Create your first feature flag** using the Unleash Admin UI. **Connect Unleash to your application** by integrating an SDK into your codebas…”
   • [claimed-docs] “They allow you to enable and disable features for certain users without having to redeploy your application.”
   • [claimed-docs] “use one of the client or backend SDKs to connect Unleash with your application”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”

   proof ↗⚑ flag

2. developerServe multivariate flags and dynamic configuration values (strings, numbers, JSON), not just booleans

   weight 2 · round to GrowthBook
   GrowthBook✓fullprobed7/10

   GrowthBook's SDK docs explicitly show non-boolean flag values via useFeatureValue (string example 'button-color') alongside useFeatureIsOn for booleans, and its targeting/rules docs describe rules that 'control which values a user sees' beyond simple on/off, plus a real runtime probe confirms a flag payload with a typed defaultValue served via the API. Missing for 10: explicit documented example of numeric and JSON-typed flag values (only string is shown in the quickstart snippet), and no independent hands-on confirmation of JSON config usage.

   • [claimed-docs] “const showNewFeature = useFeatureIsOn("new-feature"); const buttonColor = useFeatureValue("button-color", "blue");”
   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”
   • [github] “24 SDKs including React, Python, Android, and iOS.”

   proof ↗⚑ flag

   Unleash~partialprobed6/10

   Unleash's docs confirm a dedicated 'variants' concept explicitly used for multivariate/A-B testing, which supports serving multiple values per flag, but the evidence never explicitly documents the variant payload types (string, number, JSON) or shows an SDK example reading a non-boolean value at runtime. missing for 10: explicit documentation of variant payload types (string/number/json) and hands-on/SDK evidence of retrieving a non-boolean variant value.

   • [claimed-docs] “Variants let you expose different versions of a feature to users, for example, as part of A/B and multivariate testing.”
   • [claimed-docs] “Release management in Unleash helps you standardize, automate and safeguard your feature rollouts.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”

   proof ↗⚑ flag

Lifecycle

1. platform engineerFind stale flags and code references so temporary flags actually get removed from the codebase

   weight 2 · round to GrowthBook
   GrowthBook✓fullclaimed8/10

   GrowthBook's docs explicitly describe automatic stale flag detection ('GrowthBook can automatically detect these flags so you can clean them up') as a dedicated feature, directly addressing the story of finding stale flags for removal. This is corroborated by the product's broader flag-management infrastructure (environments, rules, revisions) but lacks detail on code-reference scanning across repos or independent/hands-on verification of the stale-detection feature itself. Missing for 10: evidence of code-reference/usage scanning across the codebase, and independent/community confirmation that stale detection works reliably in practice.

   • [claimed-docs] “GrowthBook can automatically detect these flags so you can clean them up.”
   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Use environments such as dev, staging, and production to enable or disable feature flags independently.”

   proof ↗⚑ flag

   Unleash—none0/10

   The evidence pack covers flag creation, rollout strategies, environments, RBAC, change requests, and impact metrics, but contains no mention of stale-flag detection, flag lifecycle status, or code-reference scanning tools that would help a platform engineer find and remove unused flags from source code.

   ⚑ flag

Targeting

1. developerTarget or exclude specific individual users for a flag (allowlists, beta testers, internal accounts)

   weight 1 · round to GrowthBook
   GrowthBook✓fullclaimed7/10

   GrowthBook's rule/targeting system lets you write conditions against arbitrary user attributes (e.g., user ID, email) to include or exclude specific users, which covers allowlisting beta testers or internal accounts (growthbook-docs-2, growthbook-docs-22, growthbook-docs-18, growthbook-docs-28). This is a first-class part of its rules engine (scope, ramp, schedule). missing for 10: an explicit doc example/tutorial titled 'allowlist' or 'beta testers' walkthrough, and independent hands-on confirmation of exclusion-list behavior.

   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees. Conditions are evaluated against attributes you pass into the SDK”
   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “The actual values of targeting attributes (e.g., user IDs, emails) are never sent to GrowthBook. They are only stored in memory locally with…”
   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees.”

   proof ↗⚑ flag

   Unleash~partialclaimed6/10

   Unleash supports activation strategies and constraints (segments, custom activation strategies and targeting) that can target or exclude specific users/groups, and tokens/environments allow scoping test rollouts to internal accounts, but no evidence pack item explicitly documents a simple 'individual user allowlist/exclude by userId' UI feature or shows a hands-on example of listing specific beta tester IDs. missing for 10: explicit documentation/example of per-user allowlist or exclude-by-userId targeting UI, independent/hands-on confirmation of this exact workflow beyond generic 'custom activation strategies and targeting' marketing copy.

   • [claimed-docs] “A segment is a reusable collection of strategy constraints.”
   • [claimed-docs] “Custom activation strategies and targeting”
   • [claimed-docs] “They allow you to enable and disable features for certain users without having to redeploy your application.”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [claimed-docs] “This allows you to enable a flag in development or test without enabling it in production.”

   proof ↗⚑ flag

2. developerTarget flags with attribute-based rules and reusable segments so the right users see the right variation

   weight 3 · round to Unleash
   GrowthBook~partialclaimed6/10

   GrowthBook clearly supports attribute-based targeting rules (conditions evaluated against SDK-passed attributes, rule scoping/ramping/scheduling) as shown in growthbook-docs-2, -22, -28, and -18. However, the evidence pack never mentions a distinct 'segments' feature (reusable named audience definitions) that developers could apply across multiple flags/rules, so the reusable-segment half of the story is unevidenced. missing for 10: explicit segment/audience-reuse documentation, evidence of applying the same segment across multiple flags, independent confirmation of segment behavior.

   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees. Conditions are evaluated against attributes you pass into the SDK”
   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees.”
   • [claimed-docs] “The actual values of targeting attributes (e.g., user IDs, emails) are never sent to GrowthBook. They are only stored in memory locally with…”

   proof ↗⚑ flag

   Unleash✓fullcommunity7/10

   Unleash docs directly describe segments as reusable collections of strategy constraints, plus custom activation strategies/targeting and attribute-based rules for flag rollout (unleash-docs-9, unleash-docs-17, unleash-docs-18). This directly matches the story's request for attribute-based rules and reusable segments to target specific user variations. Missing for 10: independent/hands-on validation of complex multi-attribute rule evaluation and the HN comment noting relative rule-system limitations versus competitors introduces some doubt but is not a concrete contradiction.

   • [claimed-docs] “A segment is a reusable collection of strategy constraints.”
   • [claimed-docs] “Custom activation strategies and targeting”
   • [claimed-docs] “They allow you to enable and disable features for certain users without having to redeploy your application.”
   • [claimed-docs] “Variants let you expose different versions of a feature to users, for example, as part of A/B and multivariate testing.”
   • [community] “Many open source solutions (Unleash, last I checked, some time ago) are more limited: some of th[e]... [compared to LaunchDarkly's more flex…”

   proof ↗⚑ flag

Access

1. platform engineerRestrict who can change which flags with roles, permissions, and scoped API tokens

   weight 2 · round to Unleash
   GrowthBook~partialclaimed5/10

   Pricing page confirms GrowthBook has role/permission features ("Advanced permissioning", "Advanced access control", SSO & SCIM) gated behind paid tiers, implying RBAC exists, but there is no docs page detailing how roles map to flag-level permissions or how API tokens can be scoped to restrict flag changes; the API docs even note the SDK connection endpoint is public/unauthenticated, which is a different, more limited access model. Missing for 10: a dedicated permissions/roles doc, explicit description of scoped/restricted API tokens for flag mutation, and independent confirmation of enforcement.

   • [claimed-docs] “Starter, plus: Visual editor Multi-arm bandits Safe rollouts Customizable dashboards Advanced permissioning Power calculator Premium support”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Visual editor * Multi-arm bandits * Safe rollouts * Customizable dashboards * Advanced permissioning * Power calculator”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “They are meant to be public and do not require authentication to view.”

   proof ↗⚑ flag

   Unleash✓fullclaimed8/10

   Unleash documents RBAC at two levels (project and instance), scoped API tokens restricted to specific projects/environments (backend tokens) with non-secret frontend tokens, and change requests requiring approval before changes apply in an environment — together enabling platform engineers to restrict who can change which flags. GitHub evidence also confirms RBAC, SSO, and SCIM as enterprise features. missing for 10: independent/hands-on verification of granular permission enforcement and no first-party detail on custom fine-grained permission roles beyond RBAC docs.

   • [claimed-docs] “Unleash implements role-based access control on two levels”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”
   • [claimed-docs] “Frontend tokens are not considered secret and are safe to expose client-side.”
   • [claimed-docs] “Change requests allow you to require an additional approval step before any changes can be made in an environment.”
   • [github] “This gives you access to a hosted instance with unlimited projects and environments and features such as role-based access control, change r…”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”

   proof ↗⚑ flag

Agent ops

1. ai agentCreate and toggle flags through documented APIs, CLIs, or MCP — and the platform can force my changes through approval workflows instead of letting me write to production unreviewed

   weight 3 · round to Unleash
   GrowthBook~partialprobed6/10

   GrowthBook documents an official MCP server that makes authenticated REST calls (growthbook-docs-13/21, growthbook-probe-3/rt-1) and a full REST API (growthbook-docs-12), and separately documents 'Draft feature revisions, request review... require approval before publishing' as a Pro+ approval-workflow feature (growthbook-docs-5, growthbook-docs-16/37). However, the runtime probe (growthbook-probe-rt-2) shows a flag created and immediately live via the API with no review step, and approval workflows appear gated behind a paid plan rather than proven to force-block an AI agent's writes by default. Missing for 10: a documented/verified CLI channel, and hands-on evidence that MCP/API writes are actually intercepted and blocked pending human approval rather than merely available as an opt-in paid feature.

   • [claimed-docs] “Connect AI tools like Cursor, VS Code, and Claude to GrowthBook using the Model Context Protocol (MCP).”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “official MCP server documented at https://docs.growthbook.io/integrations/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”
   • [claimed-docs] “Draft feature revisions, request review, resolve merge conflicts, and require approval before publishing.”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”

   proof ↗⚑ flag

   Unleash~partialprobed7/10

   Unleash documents an Admin API and MCP server for creating/managing flags (unleash-docs-6, unleash-docs-7, unleash-probe-2) and the runtime probe confirms real flag creation via the Admin API (unleash-probe-rt-1). Change requests (unleash-docs-11) and RBAC (unleash-docs-12) provide an approval-gating mechanism for environment changes, but this is an Enterprise-tier feature and evidence does not explicitly confirm it enforces approval on MCP/API-driven writes specifically (only that it applies to 'changes in an environment') nor is a documented CLI shown. Missing for 10: explicit CLI support, confirmation that change-request approval gates API/MCP-originated writes specifically, and independent (non-vendor) verification of the approval workflow blocking agent writes.

   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [claimed-docs] “This server enables LLM-powered coding assistants to create and manage feature flags following Unleash best practices.”
   • [probe] “official MCP server documented at https://docs.getunleash.io/integrate/mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”
   • [claimed-docs] “Change requests allow you to require an additional approval step before any changes can be made in an environment.”
   • [claimed-docs] “Unleash implements role-based access control on two levels”
   • [github] “This gives you access to a hosted instance with unlimited projects and environments and features such as role-based access control, change r…”

   proof ↗⚑ flag

Approvals

1. platform engineerRequire approvals or change requests before production flag changes go live

   weight 3 · round drawn
   GrowthBook✓fullclaimed8/10

   GrowthBook's docs explicitly describe drafting feature revisions, requesting review, resolving merge conflicts, and requiring approval before publishing changes (growthbook-docs-5), and this is packaged as a named 'Approval workflows' feature on paid tiers (growthbook-docs-16, growthbook-docs-37). This directly matches the story of gating production flag changes behind approvals. Missing for 10: independent/hands-on confirmation of the approval workflow in practice (only vendor docs cited) and detail on how approvals interact with environment-specific promotion.

   • [claimed-docs] “Draft feature revisions, request review, resolve merge conflicts, and require approval before publishing.”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “Use environments such as dev, staging, and production to enable or disable feature flags independently.”

   proof ↗⚑ flag

   Unleash✓fullclaimed8/10

   Unleash docs explicitly describe Change Requests as an approval workflow that requires an additional approval step before changes go live in an environment, and this is corroborated by GitHub listing change requests as a hosted/enterprise feature alongside RBAC and SSO. Missing for 10: independent hands-on verification of the approval workflow in practice and details on multi-stage/production-specific enforcement.

   • [claimed-docs] “Change requests allow you to require an additional approval step before any changes can be made in an environment.”
   • [github] “This gives you access to a hosted instance with unlimited projects and environments and features such as role-based access control, change r…”
   • [claimed-docs] “Environments represent different stages in your development lifecycle. They allow you to manage your product releases from local development…”
   • [claimed-docs] “Unleash implements role-based access control on two levels”

   proof ↗⚑ flag

Audit

1. platform engineerEvery flag change is recorded in an audit log — who changed what, when, and to which value

   weight 3 · round to GrowthBook
   GrowthBook~partialclaimed5/10

   Pricing docs confirm GrowthBook ships an audit log feature, with 'Exportable audit logs' listed as a Pro-tier capability, implying built-in tracking of changes for governance purposes. However, there is no first-party documentation detailing exactly what is captured (who/when/old-new value) or how the audit trail is presented/queried, and the capability is gated behind a paid plan rather than universally available. Missing for 10: dedicated audit-log documentation describing captured fields, retention, and access/export mechanics, plus confirmation it's available outside paid tiers or independent corroboration of its behavior.

   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “SSO & SCIM provisioning * Exportable audit logs”

   proof ↗⚑ flag

   Unleash—none0/10

   The evidence pack covers RBAC, change requests, environments, and API tokens, but contains no mention of an audit log recording who changed what flag, when, or to what value — the specific capability the story asks about is unevidenced.

   ⚑ flag

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

   weight 2 · round to GrowthBook
   GrowthBook✓fullprobed7/10

   GrowthBook documents a 'full REST API for interacting with the application' (growthbook-docs-12) and a runtime probe confirms it: a self-hosted instance created an org, user, and feature flag purely via API calls and served it through the SDK payload endpoint (growthbook-probe-rt-2), and the official MCP server exposes authenticated read/write meta-tools covering the whole REST API (growthbook-docs-21, growthbook-probe-rt-1). Missing for 10: an explicit enumerated API-vs-UI parity list (e.g. confirmation that experiment approval workflows, visual editor changes, and dashboard configuration are all API-exposed, not just feature flags) and independent third-party corroboration of API completeness.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “The official GrowthBook MCP server is a thin bridge: it loads GrowthBook Agent Skills (workflows and guardrails) and makes authenticated cal…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official npm MCP server (`npx -y @growthbook/mcp`) completed a FULL keyless stdio initialize handsh…”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”

   proof ↗⚑ flag

   Unleash~partialprobed7/10

   The Admin API is documented as providing 'comprehensive programmatic access to all Unleash resources', and a runtime probe confirms a real create-and-evaluate flag loop via the Admin/Client APIs with no UI involved, showing core flag management is fully API-driven. However, some UI-centric workflows (e.g., change request approval flows, RBAC/SSO configuration, impact-metrics dashboards) are not shown to have full API parity in the evidence. missing for 10: explicit documentation/proof that change-request approvals, RBAC/SSO setup, and impact-metrics automation can be fully performed via API rather than just referenced conceptually.

   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”
   • [claimed-docs] “Change requests allow you to require an additional approval step before any changes can be made in an environment.”
   • [claimed-docs] “Unleash implements role-based access control on two levels”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   GrowthBook~partialcommunity5/10

   GrowthBook is open-source and self-hostable with its data stored in a standard MongoDB instance, and it exposes a full REST API for programmatic access to feature flags, experiments, and metrics, which together give a technically-inclined user a path to extract all their data without vendor lock-in. However, there is no explicit documented 'export all data' or bulk-export feature/wizard, and 'exportable audit logs' is gated behind an Enterprise tier rather than being a general open-export capability. Missing for 10: an explicit documented full-data export/backup tool or format, confirmation that experiment results/metrics history export in an open format, and evidence this works outside self-hosting for cloud customers.

   • [claimed-docs] “GrowthBook offers a full REST API for interacting with the application.”
   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [community] “Re: Eppo - they're similar in setup but Growthbook is open source with an optional cloud SaaS offering. Optimizely is a walled garden, you n…”

   proof ↗⚑ flag

   Unleash~partialclaimed5/10

   Unleash is open source and self-hostable, and pricing docs mention 'export/import feature flags for easy migration,' plus the Admin API gives programmatic access to all resources, supporting data portability. However, there's no explicit documented full-data-export format spec, no evidence of exporting audit logs, metrics history, or user/RBAC data, and no dedicated 'leave and take everything' migration guide. Missing for 10: a documented comprehensive data-export/backup format covering all entities (not just flags), evidence of full account data portability, and independent confirmation that exports are truly complete and open-format.

   • [claimed-docs] “Export/import feature flags for easy migration”
   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”
   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   GrowthBook~partialcommunity5/10

   Community evidence explicitly states GrowthBook is open source with an optional cloud SaaS offering, and a public GitHub repository (github.com/growthbook/growthbook) is cited, supporting that source is readable. However, no evidence pack item specifies the actual license type (e.g., MIT/Apache) or licensing terms, so the 'open license' claim isn't directly documented. Missing for 10: explicit license identification/text, first-party docs confirming license terms, independent confirmation of license permissiveness.

   • [community] “Re: Eppo - they're similar in setup but Growthbook is open source with an optional cloud SaaS offering. Optimizely is a walled garden, you n…”
   • [github] “24 SDKs including React, Python, Android, and iOS.”
   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”

   proof ↗⚑ flag

   Unleash~partialclaimed5/10

   The GitHub repo (github.com/Unleash/unleash) is cited multiple times and docs explicitly distinguish 'Unleash Open Source' from 'Unleash Enterprise', indicating the core product's source is publicly available. However, the evidence pack never states the specific open-source license (e.g. Apache-2.0) or confirms the full extent of what's open vs. enterprise-gated. Missing for 10: explicit license name/file citation, clarity on which modules are open vs. proprietary enterprise-only code.

   • [github] “Feature flags in Unleash let you test your code with real production data, reducing the risk of negatively impacting your users' experience.”
   • [github] “It also enables your team to work on multiple features simultaneously without the need for separate feature branches.”
   • [github] “This gives you access to a hosted instance with unlimited projects and environments and features such as role-based access control, change r…”
   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”

   proof ↗⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round to GrowthBook
   GrowthBook✓fullprobed10/10

   GrowthBook is documented and independently confirmed (via runtime probe) to self-host fully via Docker Compose including MongoDB, API, and front-end, with a real keyless create-and-evaluate flag loop working end-to-end; community reviews also corroborate long-term self-hosted usage.

   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”
   • [community] “Growthbook is awesome! We have used the self-hosted version a few months in my company now, and are very happy about it. Talented people beh…”

   proof ↗⚑ flag

   Unleash✓fullprobed9/10

   Unleash Open Source is explicitly documented as self-hostable via Docker (unleash-docs-4), and a runtime probe confirms a full keyless self-host roundtrip creating and evaluating a flag with no account or license (unleash-probe-rt-1), directly demonstrating self-hosting of the core product. missing for 10: independent third-party (non-vendor) write-up confirming production-grade self-hosted deployment at scale.

   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”
   • [github] “Feature flags in Unleash let you test your code with real production data, reducing the risk of negatively impacting your users' experience.”

   proof ↗⚑ flag

Pricing

1. product managerSee published pricing and understand what drives cost (seats, MAUs, events, requests) before committing

   weight 2 · round to GrowthBook
   GrowthBook~partialclaimed6/10

   GrowthBook publishes a tiered pricing page (Starter/Pro/Enterprise-like tiers) listing feature gates (visual editor, approval workflows, SSO/SCIM, etc.) and calls out unlimited flags/experiments/traffic and per-user caps like 'Up to 3 users', but none of the evidence shows usage-based cost drivers like MAUs, events, or API requests being priced or metered — the plans appear seat/feature-gated rather than usage-metered. missing for 10: explicit cost drivers tied to MAUs/events/requests, a pricing calculator or usage-based cost breakdown, and independent confirmation that published prices match real invoices.

   • [claimed-docs] “Starter, plus: Visual editor Multi-arm bandits Safe rollouts Customizable dashboards Advanced permissioning Power calculator Premium support”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Unlimited feature flags * Unlimited experiments * Unlimited traffic”
   • [claimed-docs] “Starter, plus: * Visual editor * Multi-arm bandits * Safe rollouts * Customizable dashboards”
   • [claimed-docs] “Visual editor * Multi-arm bandits * Safe rollouts * Customizable dashboards * Advanced permissioning * Power calculator”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “Up to 3 users * 1 project * Unlimited feature flags * Unlimited experiments * Unlimited traffic”
   • [claimed-docs] “SSO & SCIM provisioning * Exportable audit logs”

   proof ↗⚑ flag

   Unleash~partialclaimed3/10

   The pricing page is referenced and shows some plan-gated features (export/import, custom strategies, SSO) but the evidence never shows actual published prices or explicit cost drivers like per-seat, MAU, event, or request-based pricing that a PM could use to estimate cost before committing. Missing for 10: explicit price figures, cost-driver metrics (seats/MAUs/events/requests), and any tier comparison table showing how usage translates to price.

   • [claimed-docs] “Export/import feature flags for easy migration”
   • [claimed-docs] “Custom activation strategies and targeting”
   • [claimed-docs] “Single Sign-On (SSO) with SAML 2.0 or OpenID Connect (Azure AD, Okta)”
   • [github] “This gives you access to a hosted instance with unlimited projects and environments and features such as role-based access control, change r…”

   proof ↗⚑ flag

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

   weight 2 · round to GrowthBook
   GrowthBook~partialprobed6/10

   GrowthBook can be fully self-hosted via Docker Compose (own MongoDB, API, and front-end), which lets an AI-native user control exactly where all data lives, and a probe confirms a working self-hosted flag create/evaluate loop with no third-party data storage. However, there is no documented cloud-hosted region/residency selection (e.g., EU vs US SaaS options) for users who don't want to self-host. Missing for 10: explicit cloud multi-region hosting options, formal data-residency/compliance certifications, and documentation letting SaaS customers pick a storage region without self-hosting.

   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”
   • [claimed-docs] “The actual values of targeting attributes (e.g., user IDs, emails) are never sent to GrowthBook. They are only stored in memory locally with…”

   proof ↗⚑ flag

   Unleash~partialprobed5/10

   Unleash's self-hosted deployment (Docker, own environment) inherently lets users control where infrastructure and thus data resides, and this was verified in a runtime probe of a full self-host flag create/evaluate loop. However, there is no explicit documentation of region/residency options for the hosted Enterprise/Cloud offering (e.g., choosing EU/US data centers), so residency is only achievable via self-hosting rather than a first-class SaaS feature. Missing for 10: explicit region-selection or data-residency documentation for the managed/cloud product, and any compliance certifications tied to specific regions.

   • [claimed-docs] “This guide helps you set up Unleash Open Source or Unleash Enterprise in your own environment using Docker.”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official unleashorg/unleash-server docker image …”
   • [github] “This gives you access to a hosted instance with unlimited projects and environments and features such as role-based access control, change r…”

   proof ↗⚑ flag

2. ai-native userControl data retention and deletion

   weight 2 · round to GrowthBook
   GrowthBook~partialclaimed4/10

   GrowthBook's privacy-by-design targeting (attribute values never sent to GrowthBook, kept in-memory in the SDK) and the option to self-host on your own infrastructure/MongoDB give users indirect control over what data is retained and how it's deleted, since they own the database. However, there is no explicit documentation of a data retention policy, a deletion API/endpoint, or GDPR-style 'delete my data' tooling in the evidence pack. Missing for 10: explicit retention-period settings, a documented deletion/erasure API or workflow, and any compliance certification (e.g., GDPR/CCPA) statements.

   • [claimed-docs] “The actual values of targeting attributes (e.g., user IDs, emails) are never sent to GrowthBook. They are only stored in memory locally with…”
   • [claimed-docs] “Run GrowthBook on your own infrastructure with Docker Compose, including MongoDB, the API, and the front-end.”
   • [claimed-docs] “You can use docker compose to get started quickly... run docker compose up -d to start everything and view the app at http://localhost:3000”

   proof ↗⚑ flag

   Unleash—none0/10

   The evidence pack covers feature-flag mechanics, deployment, RBAC, and API tokens, but contains no documentation of data retention policies, deletion workflows, or GDPR-style data controls for flags, audit logs, or user data. Self-hosting is mentioned but that alone doesn't constitute a documented retention/deletion control feature.

   ⚑ flag

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

   weight 2 · round drawn
   GrowthBook—none0/10

   The evidence pack shows GrowthBook is self-hostable and that targeting-attribute values are never sent to the vendor, but there is no documentation of any product telemetry/usage-tracking opt-out setting or flag for the self-hosted or cloud application itself. Missing for 10: any explicit telemetry/usage-analytics toggle, docs on what data is phoned home from self-hosted instances, or a documented opt-out mechanism.

   ⚑ flag

   Unleash—none0/10

   No evidence in the pack addresses telemetry or usage-tracking opt-out settings for Unleash itself (self-hosted or SaaS); nothing documents what data Unleash collects about its own usage or how to disable it. missing for 10: any mention of telemetry collection, opt-out flags/env vars, or privacy documentation regarding usage tracking.

   ⚑ flag

Rollouts

1. platform engineerGuard a rollout with metrics so a regression is detected and the release is rolled back automatically

   weight 2 · round to Unleash
   GrowthBook~partialclaimed4/10

   GrowthBook's pricing pages list a named 'Safe rollouts' feature (Pro+ tier) alongside guardrail-metric support in experiment templates, implying automated regression detection and rollback, but the evidence pack contains no docs explaining how the automatic rollback mechanism actually works (thresholds, trigger logic, rollback speed) nor any hands-on confirmation it fires reliably in production. Missing for 10: detailed docs/description of the Safe Rollouts mechanism and guardrail-triggered auto-rollback, plus independent or hands-on evidence it works as claimed.

   • [claimed-docs] “Starter, plus: Visual editor Multi-arm bandits Safe rollouts Customizable dashboards Advanced permissioning Power calculator Premium support”
   • [claimed-docs] “Starter, plus: * Visual editor * Multi-arm bandits * Safe rollouts * Customizable dashboards”
   • [claimed-docs] “Visual editor * Multi-arm bandits * Safe rollouts * Customizable dashboards * Advanced permissioning * Power calculator”
   • [claimed-docs] “Visual editor * Multi-arm bandits * Safe rollouts * Customizable dashboards”
   • [claimed-docs] “Selecting a Template in the creation modal pre-fills settings like the data source, goal/secondary/guardrail metrics, targeting, and traffic”

   proof ↗⚑ flag

   Unleash✓fullclaimed7/10

   Unleash's impact-metrics feature explicitly supports guarding rollouts with metrics, including automatic pause/rollback when error rates or latency cross thresholds (e.g., 'Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold' and 'Pause automatically when request latency increases during a rollout'). This directly matches the story's requirement of metric-guarded rollout with automatic rollback. missing for 10: independent/hands-on verification of the automatic rollback behavior in production, and more detail on how 'rollback' (vs. pause/disable) is technically executed.

   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”
   • [claimed-docs] “Release management in Unleash helps you standardize, automate and safeguard your feature rollouts.”

   proof ↗⚑ flag

2. developerRoll a flag out progressively by percentage with consistent bucketing, ramping from 1% to 100% without redeploying

   weight 3 · round to Unleash
   GrowthBook✓fullprobed8/10

   GrowthBook's rules docs explicitly cover 'rolling out gradually' and describe how rules can 'scope, ramp, and schedule' percentage rollouts, with experiment/flag assignment based on a hashing attribute for consistent bucketing, and SDKs evaluate the cached JSON payload client-side with no redeploy needed. Pricing tiers also list dedicated 'Ramp schedules' as a named capability, confirming this is a first-class shipped feature, and probe evidence confirms a live flag create/evaluate loop via the SDK payload endpoint. missing for 10: independent/hands-on confirmation of an actual 1%→100% ramp in practice, and detail on the specific hashing algorithm ensuring bucket stability across ramp changes

   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “you can add an experiment rule to a feature that will randomly assign the users based on some hashing attribute into one of your experiment …”
   • [claimed-docs] “When the client loads your application, our SDK will check to see if the user should be part of any experiments, and if so, assign them and …”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”
   • [claimed-docs] “GrowthBook supports several ways to do this: Feature Flags (most common)... URL Redirects... Our Visual Editor... Your own custom variation …”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”

   proof ↗⚑ flag

   Unleash✓fullclaimed9/10

   Unleash's gradual rollout activation strategy is a documented first-class concept, explicitly supporting progressive percentage rollout with consistent bucketing (via stickiness) without redeploying, and impact-metrics docs show automated progression between percentage thresholds (e.g., 25% to 50%) based on health checks. Missing for 10: no independent hands-on evidence of the specific 1%→100% ramp UI/automation flow in practice beyond docs.

   • [claimed-docs] “A **gradual rollout** is a controlled release strategy where a new feature is first released to a small subset of users.”
   • [claimed-docs] “They allow you to enable and disable features for certain users without having to redeploy your application.”
   • [claimed-docs] “Progress from 25% to 50% only if error rates stay below a threshold.”
   • [claimed-docs] “Automate milestone progression or trigger safeguards that pause rollouts or disable environments when metrics cross a threshold.”
   • [claimed-docs] “Pause automatically when request latency increases during a rollout.”

   proof ↗⚑ flag

Scheduling

1. developerSchedule flag changes and releases to happen at a specific future time

   weight 1 · round to Unleash
   GrowthBook~partialclaimed6/10

   GrowthBook explicitly documents that feature rules can be 'scoped, ramped, and scheduled,' and its pricing page lists 'Ramp schedules' as a distinct capability, confirming a future-time scheduling mechanism for flag rollouts. However, this appears gated to paid plans (Pro tier) and the evidence pack gives no detailed walkthrough of how scheduling is configured or any independent/hands-on confirmation it works as described. Missing for 10: detailed documentation of the scheduling UI/API, hands-on or community verification, and clarity on whether it applies broadly to all rule types.

   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “Pro, plus: Custom environments Ramp schedules Approval workflows Advanced access control SSO & SCIM provisioning Exportable audit logs”
   • [claimed-docs] “Custom environments * Ramp schedules * Approval workflows * Advanced access control * SSO & SCIM provisioning * Exportable audit l…”

   proof ↗⚑ flag

   Unleash✓fullclaimed8/10

   Unleash documents a dedicated how-to guide for scheduling feature releases at a specific date/time, framed explicitly for use cases like product launches, and this sits alongside broader release management, gradual rollout, and environment concepts that support scheduled changes. Missing for 10: independent/hands-on corroboration of the scheduling feature working in practice, and detail on granularity/timezone handling or recurring schedules.

   • [claimed-docs] “to release a feature at a specific date and time** (for a product launch, for instance)”
   • [claimed-docs] “to release a feature at a specific date and time (for a product launch, for instance)”
   • [claimed-docs] “Release management in Unleash helps you standardize, automate and safeguard your feature rollouts.”

   proof ↗⚑ flag

Edge

1. platform engineerEvaluate flags at the edge (CDN workers or an edge/relay layer) close to users

   weight 2 · round drawn
   GrowthBook✓fullclaimed8/10

   GrowthBook documents a dedicated Cloudflare Workers edge SDK that evaluates feature flags and Visual Editor experiments at the edge to cut flicker before HTML ships, plus a self-hostable Proxy layer that caches SDK payloads near users and keeps serving flags if the API is down. Missing for 10: independent hands-on evidence specifically of the edge/Cloudflare SDK in production (community evidence covers general SDK/self-host use but not edge-worker deployments) and broader edge-platform coverage beyond Cloudflare.

   • [claimed-docs] “Evaluate GrowthBook feature flags and Visual Editor experiments at the edge on Cloudflare Workers to cut flicker before HTML ships.”
   • [claimed-docs] “Run the GrowthBook Proxy next to your app to cache SDK payloads, reduce latency, and keep serving flags if the API is down.”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”

   proof ↗⚑ flag

   Unleash✓fullclaimed8/10

   Unleash Edge is a documented purpose-built component (Rust-based caching/relay layer) that sits between SDKs and the primary server, described explicitly as reducing read load and improving scalability/performance/resilience for connected SDKs, functioning as a low-latency edge/relay evaluation layer close to users. This directly matches the story, though evidence doesn't explicitly show deployment as a CDN/edge-worker runtime (e.g., Cloudflare Workers) itself. missing for 10: explicit CDN-worker (e.g., Cloudflare Workers) deployment guide, independent performance/latency benchmarks for Edge in production.

   • [claimed-docs] “functioning as a read replica that can handle thousands of connected SDKs without increasing the read load on your primary Unleash instance”
   • [claimed-docs] “Unleash Enterprise Edge is a lightweight caching layer designed to improve scalability, performance, and resilience.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”

   proof ↗⚑ flag

Evaluation

1. platform engineerMy server SDKs evaluate flags locally from a cached ruleset — microsecond decisions with no network call per flag check

   weight 3 · round to GrowthBook
   GrowthBook✓fullprobed9/10

   GrowthBook's core architecture is a cacheable JSON ruleset that SDKs evaluate locally, confirmed by docs (SDK Connection Endpoint providing readonly flag data for local assignment, in-memory attribute evaluation) and corroborated by a community founder comment describing exactly this model plus a runtime probe showing the keyless payload endpoint serving flag data for local SDK evaluation. Missing for 10: explicit published latency/microsecond benchmarks or independent third-party performance testing.

   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”
   • [claimed-docs] “The actual values of targeting attributes (e.g., user IDs, emails) are never sent to GrowthBook. They are only stored in memory locally with…”
   • [community] “With GrowthBook, there's a single cacheable JSON definition of all of the features and then evaluation happens locally within the SDKs... Th…”
   • [probe] “PROBE runtime (recorded 2026-09-05): full KEYLESS self-host roundtrip on this machine — the official growthbook/growthbook docker image boot…”
   • [claimed-docs] “Run the GrowthBook Proxy next to your app to cache SDK payloads, reduce latency, and keep serving flags if the API is down.”

   proof ↗⚑ flag

   Unleash~partialclaimed3/10

   Evidence shows Unleash SDKs communicate via API keys and that Edge exists as a caching layer to reduce read load from 'thousands of connected SDKs,' implying a poll-and-cache model, but no evidence explicitly describes local, in-process flag evaluation from a cached ruleset or confirms 'no network call per flag check' / microsecond latency. missing for 10: explicit SDK architecture docs describing local evaluation engine, cache refresh intervals, and no-network-per-check guarantee, plus independent benchmarks.

   • [claimed-docs] “functioning as a read replica that can handle thousands of connected SDKs without increasing the read load on your primary Unleash instance”
   • [claimed-docs] “Unleash Enterprise Edge is a lightweight caching layer designed to improve scalability, performance, and resilience.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”

   proof ↗⚑ flag

Sdks

1. developerUse official SDKs across my whole stack — backend, web, and mobile — with consistent flag behavior

   weight 2 · round to GrowthBook
   GrowthBook✓fullcommunity7/10

   GrowthBook offers 24 official SDKs spanning backend, web/React, and mobile (Android/iOS) per GitHub README, with docs showing consistent flag-evaluation patterns (useFeatureIsOn, useFeatureValue, targeting attributes evaluated locally) and community reports of quick multi-stack integration (Vue frontend in hours). An older 2021 community comment noted no native mobile SDKs yet, but this is superseded by the more recent GitHub claim explicitly listing Android/iOS SDKs, so it's not a live contradiction. Missing for 10: independent verification of identical targeting/rollout behavior across all 24 SDKs, and more recent hands-on confirmation of mobile SDK maturity/parity with backend/web SDKs.

   • [github] “24 SDKs including React, Python, Android, and iOS.”
   • [claimed-docs] “Get GrowthBook feature flags and experiments running in your app in a few lines of code, then pick a language-specific SDK.”
   • [claimed-docs] “const showNewFeature = useFeatureIsOn("new-feature");”
   • [claimed-docs] “const showNewFeature = useFeatureIsOn("new-feature"); const buttonColor = useFeatureValue("button-color", "blue");”
   • [claimed-docs] “Add targeting conditions to a rule to control which values a user sees.”
   • [community] “At Miggos we have implemented Growth book and we got FF and A/B in our Vue frontend in a few hours. Excited to see the progress of the platf…”
   • [community] “We don't have native mobile SDKs yet, but it's something we want to support in the future. Mobile is a little tricky since you either need t…”

   proof ↗⚑ flag

   Unleash~partialclaimed5/10

   Docs confirm Unleash's SDK model — distinguishing backend/server SDKs (secret tokens) from client-side SDKs for web/mobile (safe-to-expose frontend tokens) and instruct developers to 'use one of the client or backend SDKs to connect Unleash with your application.' However, the pack never lists concrete SDK names/languages (e.g., specific mobile or web SDKs) or documents consistent flag-evaluation behavior across them. Missing for 10: explicit enumeration of officially supported backend/web/mobile SDKs, evidence of consistent evaluation semantics across SDKs, and independent developer corroboration of cross-stack consistency.

   • [claimed-docs] “use one of the client or backend SDKs to connect Unleash with your application”
   • [claimed-docs] “Frontend tokens are not considered secret and are safe to expose client-side.”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”
   • [claimed-docs] “Backend tokens are scoped to one or more projects and a single environment.”

   proof ↗⚑ flag

Standards

1. platform engineerUse the vendor through OpenFeature providers so my flag code isn't locked to one vendor's SDK API

   weight 1 · round drawn
   GrowthBook—none0/10

   The evidence pack describes GrowthBook's own 24 SDKs, REST API, and proxy, but contains no mention of OpenFeature or an OpenFeature provider integration anywhere. Since this axis (avoiding vendor lock-in via OpenFeature) plausibly applies to a flagging platform, the absence of any supporting evidence yields 'none' rather than 'na'.

   • [github] “24 SDKs including React, Python, Android, and iOS.”
   • [claimed-docs] “Get GrowthBook feature flags and experiments running in your app in a few lines of code, then pick a language-specific SDK.”
   • [claimed-docs] “Get GrowthBook feature flags and experiments running in your app in a few lines of code”

   proof ↗⚑ flag

   Unleash—none0/10

   The evidence pack discusses Unleash's own SDKs, Admin API, Edge, and MCP integration but never mentions OpenFeature or any OpenFeature provider, so there is no evidence supporting vendor-neutral SDK usage via OpenFeature.

   • [claimed-docs] “Create your first feature flag** using the Unleash Admin UI. **Connect Unleash to your application** by integrating an SDK into your codebas…”
   • [claimed-docs] “use one of the client or backend SDKs to connect Unleash with your application”
   • [claimed-docs] “functioning as a read replica that can handle thousands of connected SDKs without increasing the read load on your primary Unleash instance”
   • [claimed-docs] “The Admin API provides comprehensive programmatic access to all Unleash resources.”

   proof ↗⚑ flag

Streaming

1. developerFlag changes propagate to connected SDKs in seconds via streaming or fast polling — a kill switch actually kills

   weight 2 · round drawn
   GrowthBook~partialcommunity4/10

   GrowthBook's docs confirm a single cacheable feature-flag JSON payload that SDKs evaluate locally (growthbook-comm-6), a Proxy that caches payloads to reduce latency and keep serving flags if the API is down (growthbook-docs-11), and environment/rule toggles that could function as kill switches (growthbook-docs-3, growthbook-docs-22). However, no evidence in the pack documents actual streaming/SSE or fast-polling update latency in seconds, nor confirms a tested kill-switch effect at runtime. Missing for 10: explicit documentation of push/streaming update mechanism and propagation-time guarantees, and a hands-on/community test showing a kill switch immediately disabling a flag across connected SDKs.

   • [claimed-docs] “Run the GrowthBook Proxy next to your app to cache SDK payloads, reduce latency, and keep serving flags if the API is down.”
   • [community] “With GrowthBook, there's a single cacheable JSON definition of all of the features and then evaluation happens locally within the SDKs... Th…”
   • [claimed-docs] “Use environments such as dev, staging, and production to enable or disable feature flags independently.”
   • [claimed-docs] “How rules override a feature's default value — targeting users, rolling out gradually, experimenting — and how to scope, ramp, and schedule …”
   • [claimed-docs] “The SDK Connection Endpoint provides readonly access to a subset of your feature flag data, just enough for the GrowthBook SDKs to assign va…”

   proof ↗⚑ flag

   Unleash~partialclaimed4/10

   Docs confirm the core mechanic — flags can be enabled/disabled without redeploy (unleash-docs-18) and SDKs/Edge communicate via API keys with Edge scaling to thousands of connected SDKs (unleash-docs-5, unleash-docs-23, unleash-docs-28) — but there is no explicit documentation of streaming vs. polling propagation times, no stated 'seconds' latency figure, and no hands-on/independent test confirming a kill switch instantly disables a live SDK. missing for 10: explicit streaming/polling interval docs, measured propagation latency, independent or hands-on confirmation of kill-switch behavior in production SDKs.

   • [claimed-docs] “They allow you to enable and disable features for certain users without having to redeploy your application.”
   • [claimed-docs] “functioning as a read replica that can handle thousands of connected SDKs without increasing the read load on your primary Unleash instance”
   • [claimed-docs] “Unleash uses API keys to facilitate communication between consuming clients such as SDKs, Unleash Edge, or other tools and automation.”
   • [claimed-docs] “Unleash Enterprise Edge is a lightweight caching layer designed to improve scalability, performance, and resilience.”

   proof ↗⚑ flag