Stagehand vs Steel

Caching

1. developerCache resolved actions or generated code so repeat runs replay deterministically at lower cost and latency than re-prompting the LLM

   weight 2 · round to Stagehand
   Stagehand✓fullclaimed8/10

   Stagehand explicitly documents server-side caching of act()/observe()/extract() results to cut LLM cost/latency, and a dedicated v3 guide describes converting agent-discovered workflows into deterministic, cached scripts running 10-100x faster. missing for 10: independent/hands-on benchmarks confirming the speedup and cost savings, and details on cache invalidation/consistency across page changes.

   • [claimed-docs] “Stagehand caches `act()`, `observe()`, and `extract()` results server-side to reduce LLM costs and speed up your automations.”
   • [claimed-docs] “This guide shows you how to use Stagehand's built-in auto-caching to convert agent-discovered workflows into fast, deterministic scripts tha…”

   proof ↗⚑ flag

   Steel—none0/10

   Steel's evidence covers session management, stealth, proxies, human-in-the-loop debugging, and agent traces, but nothing about caching resolved actions or generated code to enable deterministic, lower-cost replay without re-invoking the LLM. Agent traces (steel-docs-6/7) provide observability/export, not action-cache replay for cost savings.

   ⚑ flag

Dom

1. developerDrive the page through DOM-understanding action primitives (act/click/type on described elements) that survive selector and layout changes

   weight 3 · round to Stagehand
   Stagehand✓fullcommunity9/10

   Stagehand's core primitives (act/observe/extract) are explicitly documented as natural-language, DOM-understanding actions that discover elements and execute them, with selfHeal to re-infer actions when selectors break, plus automatic iframe/shadow DOM handling — directly matching the story. Community feedback corroborates the self-healing/resilience claim (dynamically regenerating Playwright actions vs brittle hardcoded selectors), though skepticism about cost-effectiveness exists as caveat, not contradiction. Missing for 10: independent, rigorous benchmark of selector-survival across real layout changes (community evidence is anecdotal/qualitative only).

   • [claimed-docs] “Execute actions using natural language”
   • [claimed-docs] “observe() discovers actionable elements on a page and returns structured actions you can execute or validate before acting.”
   • [claimed-docs] “Turn on `selfHeal` to re-infer an action when its recorded selector breaks.”
   • [claimed-docs] “Stagehand automatically handles iFrame traversal and shadow DOM elements without requiring additional configuration.”
   • [claimed-docs] “Traditional selectors break when websites change”
   • [claimed-docs] “Write automation in plain English. No selectors or complex syntax.”
   • [claimed-docs] “Playwright was built for testing, Stagehand is built for agents. Use familiar APIs, self-healing actions, and network-level security across …”
   • [community] “Playwright codegen is incredibly powerful, but still pretty brittle. Its DOM selectors are still hardcoded... With Stagehand, the code is se…”

   proof ↗⚑ flag

   Steel—none0/10

   Steel's own docs describe CLI-level click/fill/type and CDP/Puppeteer control (steel-gh-1, steel-docs-8), which is standard selector-based automation, not a DOM-understanding 'act on described element' primitive that survives layout/selector changes. Semantic action-taking is delegated to third-party integrations (Claude/OpenAI/Gemini Computer Use, Browser-Use) rather than being a native Steel capability.

   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”
   • [claimed-docs] “Use Gemini Computer Use with Steel Browser.”
   • [claimed-docs] “Use Claude Computer Use with Steel Browser.”
   • [claimed-docs] “The OpenAI Computer Use integration runs OpenAI's vision-based agent loop on a Steel browser session.”
   • [claimed-docs] “Use Browser-Use to interact with a Steel browser.”

   proof ↗⚑ flag

Observe

1. developerPreview candidate actions on the current page (observe/plan) before committing the agent to act

   weight 1 · round to Stagehand
   Stagehand✓fullclaimed9/10

   Stagehand's observe() explicitly discovers actionable elements and returns structured actions that can be inspected, validated, or executed before acting, directly matching the preview-before-commit workflow; act() can then take an observed action to execute deterministically. missing for 10: independent hands-on developer confirmation specifically of the observe→act preview workflow (community evidence covers other features but not this one).

   • [claimed-docs] “observe() discovers actionable elements on a page and returns structured actions you can execute or validate before acting.”
   • [claimed-docs] “`observe()` discovers actionable elements on a page and returns structured actions you can execute or validate before acting.”
   • [claimed-docs] “Playwright was built for testing, Stagehand is built for agents. Use familiar APIs, self-healing actions, and network-level security across …”

   proof ↗⚑ flag

   Steel—none0/10

   Steel exposes session snapshot/extract/screenshot tools and a human-in-the-loop debug URL (steel-docs-5, steel-docs-39), but there is no evidence of an explicit preview/plan primitive that lets a developer see candidate actions on a page before committing the agent to execute them — it's an observability/handoff feature, not an action-preview mechanism.

   • [claimed-docs] “Steel's debug URL feature allows you to implement human-in-the-loop workflows where users can directly interact with and control browser ses…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session (open, navigate, snapshot, extract, return typed results)”
   • [github] “Browser Tools: Exposes APIs to quick convert pages to markdown, readability, screenshots, or PDFs.”

   proof ↗⚑ flag

Vision

1. developerSwitch to a vision or computer-use action mode that operates on screenshots for canvases and UIs the DOM path can't handle

   weight 2 · round to Steel
   Stagehand~partialcommunity3/10

   Stagehand's core act/observe/extract primitives operate on the DOM/accessibility tree, not screenshots, and its integrations expose a generic `screenshot` tool and an autonomous `agent` primitive that could invoke vision-capable LLMs, but there is no documentation describing a dedicated vision/computer-use mode specifically for canvas or non-DOM UI elements. A community comment even states the team is still 'working on a better computer use integration,' implying this capability is not yet mature or shipped. missing for 10: explicit docs on a vision/computer-use fallback mode, evidence of canvas/non-DOM UI handling, confirmation the feature is released rather than in-progress.

   • [claimed-docs] “Each integration gives your agent one persistent browser and three tools: `run`, `snapshot`, and `screenshot`.”
   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”
   • [community] “Our Stagehand MCP server actually won Anthropic's Claude MCP hackathon :) ... We're working on a better computer use integration using Stage…”

   proof ↗⚑ flag

   Steel✓fullclaimed7/10

   Steel documents dedicated integrations for OpenAI, Claude, and Gemini Computer Use that run vision-based agent loops (operating on screenshots) atop a Steel browser session, directly enabling a vision/computer-use mode alongside its DOM-based Sessions API and CLI actions. missing for 10: independent/hands-on corroboration of vision mode working on canvas-heavy UIs, and detail on switching seamlessly between DOM and vision modes within one session.

   • [claimed-docs] “Use Gemini Computer Use with Steel Browser.”
   • [claimed-docs] “Use Claude Computer Use with Steel Browser.”
   • [claimed-docs] “The OpenAI Computer Use integration runs OpenAI's vision-based agent loop on a Steel browser session.”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”

   proof ↗⚑ flag

Agent access

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

   weight 2 · round drawn
   Stagehand✓fullprobed9/10

   A probe confirms Stagehand serves a proper llms.txt at docs.stagehand.dev/llms.txt returning HTTP 200 with structured links to docs pages, and the docs also include an explicit ai-rules page for coding assistants to consume. This directly satisfies pointing an agent at agent-oriented docs. Missing for 10: independent/community confirmation of an agent actually consuming llms.txt successfully.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.stagehand.dev/llms.txt # Stagehand - [Introducing Stagehand](https://docs.stagehand.dev/v4/first-s…”
   • [claimed-docs] “This page collects the rules, configs, and copy-paste snippets that get your coding assistant writing correct Stagehand v4 code.”

   proof ↗⚑ flag

   Steel✓fullprobed9/10

   Steel serves a live llms.txt file at docs.steel.dev/llms.txt (HTTP 200, confirmed via probe) summarizing its docs, which an agent can be pointed at directly, plus a full agent-oriented docs site with skills, MCP, and SDK integration guides. Missing for 10: no independent/community confirmation that agents actually consume the llms.txt file successfully in practice.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.steel.dev/llms.txt # Steel Documentation > Steel is the open-source browser API for AI agents — ma…”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”
   • [claimed-docs] “Expose a Steel browser to any MCP client”

   proof ↗⚑ flag

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

   weight 2 · round to Steel
   Stagehand~partialclaimed5/10

   Stagehand is a programmatic SDK (TypeScript/Python/Go) with local browser launch, CDP attach, and Browserbase cloud session options, which implies it can run without a UI and be scripted into pipelines, but no evidence explicitly mentions a headless flag, CI/CD examples, or GitHub Actions integration. missing for 10: explicit headless-mode documentation, CI/CD pipeline examples or guides, independent confirmation of running Stagehand unattended in automated build environments.

   • [claimed-docs] “There are three ways to get one: **Browserbase (`browserbase.launch`)**... **Local (`localBrowser.launch`)**... **Attach over CDP (`localBro…”
   • [claimed-docs] “Attach over CDP (localBrowser.connect): Attach to any Chromium browser you are already running, by URL”
   • [claimed-docs] “This page gets you from an empty directory to a working automation in three steps.”
   • [claimed-docs] “Browserbase runs browsers in four regions, so you can cut latency by starting the browser near your users or your target site, and keep sess…”

   proof ↗⚑ flag

   Steel✓fullprobed8/10

   Steel is API-first and ships a CLI, Docker image (API+UI), and Sessions API that spins up isolated cloud browsers on demand, all designed to be driven programmatically with no GUI required — exactly the shape needed for CI/headless automation. It also supports standard automation clients (Puppeteer/Playwright/Selenium via CDP) which are routinely run headlessly in CI pipelines. Missing for 10: an explicit CI/CD example (e.g., GitHub Actions workflow) or independent report confirming real-world headless CI usage.

   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [github] “Pre-built Docker Image (combined API + UI)”
   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”
   • [probe] “official CLI documented at https://docs.steel.dev/overview/steel-cli”

   proof ↗⚑ flag

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

   weight 3 · round to Stagehand
   Stagehand✓fullcommunity8/10

   Stagehand ships an official MCP server/integration ('Give a Claude Code agent persistent Stagehand browser tools over MCP/stdio', docs on MCP introduction and MCP best-practices), and independent community evidence corroborates this (the Stagehand MCP server won Anthropic's Claude MCP hackathon). Missing for 10: deeper hands-on user reports specifically testing the MCP server in production and more comprehensive first-party MCP setup docs beyond the overview pages.

   • [claimed-docs] “Give a Claude Code agent persistent Stagehand browser tools over MCP/stdio.”
   • [claimed-docs] “Interleave your tool results with Stagehand's primitives. Because v4 has no autonomous loop, you are already writing the orchestration, so a…”
   • [claimed-docs] “Control browsers using plain English commands like "click the login button" or "fill out the contact form"”
   • [community] “Our Stagehand MCP server actually won Anthropic's Claude MCP hackathon :) ... We're working on a better computer use integration using Stage…”

   proof ↗⚑ flag

   Steel✓fullclaimed6/10

   Steel is a browser-API platform (not itself an agent), so the axis applies, and its docs explicitly describe exposing a Steel browser as an MCP server/tool set ('Expose a Steel browser to any MCP client' and 'exposes a cloud browser as in-process MCP tools' for the Claude Agent SDK integration), letting external agents connect via MCP. Missing for 10: deeper standalone MCP-server setup docs/config reference, and independent/hands-on confirmation beyond a single cookbook and integration mention.

   • [claimed-docs] “Expose a Steel browser to any MCP client”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the browser.”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the brow”

   proof ↗⚑ flag

4. ai-native userUse an official CLI

   weight 2 · round to Steel
   Stagehand—none0/10

   No evidence of an official Stagehand CLI tool; docs mention SDKs, quickstart steps, and MCP/agent integrations but never a standalone CLI. Missing for 10: any mention of a CLI binary/command, its install method, or its command set.

   ⚑ flag

   Steel✓fullprobed7/10

   Steel ships an official CLI (documented at docs.steel.dev/overview/steel-cli) that lets users run full browser workflows from the terminal—start sessions, navigate, click/fill/type, extract content, and stop sessions—directly serving agentic/AI-native use cases. missing for 10: independent/hands-on community corroboration of the CLI itself, and detail on CLI scripting/composability beyond the basic workflow description.

   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [probe] “official CLI documented at https://docs.steel.dev/overview/steel-cli”
   • [claimed-docs] “Install Steel CLI and the steel-browser skill so your agent can control a browser.”

   proof ↗⚑ flag

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

   weight 3 · round to Steel
   Stagehand✓fullprobed8/10

   Stagehand ships a well-documented SDK API (act/observe/extract/agent) across TypeScript, Python, and Go, with a quickstart, AI-rules page for coding assistants, and an llms.txt endpoint confirming AI-native documentation access. missing for 10: no formal OpenAPI/REST spec (openapi probe returned 404s) and no independent third-party audit of API completeness beyond docs/community sentiment.

   • [claimed-docs] “Playwright was built for testing, Stagehand is built for agents. Use familiar APIs, self-healing actions, and network-level security across …”
   • [claimed-docs] “This page gets you from an empty directory to a working automation in three steps.”
   • [claimed-docs] “This page collects the rules, configs, and copy-paste snippets that get your coding assistant writing correct Stagehand v4 code.”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.stagehand.dev/llms.txt # Stagehand - [Introducing Stagehand](https://docs.stagehand.dev/v4/first-s…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.stagehand.dev/openapi.json, https://docs.stagehand.dev/swagger.json, https://docs.stage…”
   • [claimed-docs] “Execute actions using natural language”
   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”

   proof ↗⚑ flag

   Steel✓fullprobed9/10

   Steel exposes a fully documented public REST API (Sessions, CAPTCHA, Credentials, Files, Agent Traces) confirmed by a live openapi.json spec, plus an official CLI and SDK/agent-framework integrations (CrewAI, OpenAI Agents SDK, AI SDK, Claude Agent SDK, AgentKit, Pydantic AI) that let AI-native users drive it programmatically. Community comments corroborate the API/docs quality and usability. Missing for 10: independent hands-on benchmarking of the API's reliability/limits beyond docs and one HN thread.

   • [probe] “PROBE openapi: HTTP 200 at https://docs.steel.dev/openapi.json — contains "openapi" key”
   • [claimed-docs] “Explore API endpoints for building on Steel.”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [claimed-docs] “The Steel integration runs each agent's browser actions on a Steel cloud session, so AgentKit handles the orchestration and Steel handles th…”
   • [claimed-docs] “The Steel integration exposes a Steel browser as a CrewAI tool, so your crew can search, navigate, fill forms, extract data, and validate re…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session, so you can stand up a typed browser agent that opens a session, navigate…”
   • [community] “beautiful docs + api ref! what are you using? (cool that you're doing open-source browserbase also, excited to check this out)”

   proof ↗⚑ flag

6. ai-native userBuild against official SDKs

   weight 2 · round to Stagehand
   Stagehand✓fullprobed8/10

   Stagehand ships official SDKs across TypeScript, Python, and Go with documented APIs (act/observe/extract/agent), quickstart guides, AI coding rules, and llms.txt for AI-native consumption, corroborated by community usage. Missing for 10: no official REST/OpenAPI spec (probe shows 404s) and no independent benchmark of SDK completeness across all three languages.

   • [claimed-docs] “Playwright was built for testing, Stagehand is built for agents. Use familiar APIs, self-healing actions, and network-level security across …”
   • [claimed-docs] “This page gets you from an empty directory to a working automation in three steps.”
   • [claimed-docs] “This page collects the rules, configs, and copy-paste snippets that get your coding assistant writing correct Stagehand v4 code.”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.stagehand.dev/llms.txt # Stagehand - [Introducing Stagehand](https://docs.stagehand.dev/v4/first-s…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.stagehand.dev/openapi.json, https://docs.stagehand.dev/swagger.json, https://docs.stage…”
   • [community] “I've been playing around with Stagehand for a minute now, actually a useful abstraction here. We build scrapers for websites that are pretty…”

   proof ↗⚑ flag

   Steel✓fullprobed7/10

   Steel exposes a documented REST API (OpenAPI spec, steel-probe-2), an official CLI (steel-docs-8, steel-probe-3), and native connectivity via Puppeteer/Playwright/Selenium (steel-gh-1), plus first-party integrations with major agent frameworks (AI SDK, CrewAI, OpenAI Agents SDK, Claude Agent SDK, Pydantic AI, AgentKit) that act as official SDK-level bindings for AI-native development. Missing for 10: explicit named client-library SDKs (e.g., dedicated Python/Node package docs) and independent/hands-on developer confirmation of SDK ergonomics beyond vendor docs.

   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.steel.dev/openapi.json — contains "openapi" key”
   • [probe] “official CLI documented at https://docs.steel.dev/overview/steel-cli”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session (open, navigate, snapshot, extract, return typed results)”
   • [claimed-docs] “The Steel integration exposes a Steel browser as a CrewAI tool, so your crew can search, navigate, fill forms, extract data, and validate re…”
   • [claimed-docs] “Build a Pydantic AI browser agent on Steel cloud browsers: provider-agnostic, typed Python agents with dependency injection and real web acc…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session, so you can stand up a typed browser agent that opens a session, navigate…”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the brow”
   • [claimed-docs] “The Steel integration runs each agent's browser actions on a Steel cloud session, so AgentKit handles the orchestration and Steel handles th…”

   proof ↗⚑ flag

Agentic features

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

   weight 2 · round to Steel
   Stagehand~partialclaimed4/10

   Stagehand's v3 `agent()` API explicitly supports 'fully autonomous' browser workflows with configurable steps and fallbacks, suggesting some background/autonomous automation capability, but the current v4 docs explicitly state 'v4 has no autonomous loop' and require the developer to write the orchestration themselves, undercutting the 'runs autonomously' claim for the current version. There's also no evidence of scheduling, unattended/background execution infrastructure, or persistent job runners beyond a single script's runtime. missing for 10: evidence of true unattended/scheduled background execution, confirmation that v4 (current version) supports autonomous loops without manual orchestration, and independent corroboration of autonomous run reliability.

   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”
   • [claimed-docs] “Interleave your tool results with Stagehand's primitives. Because v4 has no autonomous loop, you are already writing the orchestration, so a…”
   • [claimed-docs] “Use an agent fallback as a failsafe when a one step action unexpectedly becomes a multi-step flow.”

   proof ↗⚑ flag

   Steel~partialclaimed5/10

   Steel provides infrastructure that agents can call programmatically (Sessions API, CLI, and integrations with agent frameworks like CrewAI, OpenAI Agents SDK, Claude Agent SDK) to run browser automations without human intervention, and sessions can be created on-demand for autonomous agent workflows. However, there is no evidence of a native scheduler, cron/trigger mechanism, or persistent background job runner within Steel itself — autonomy and 'background' execution depend entirely on the calling agent/framework, not a Steel-native automation scheduler. Missing for 10: native scheduling/triggers, evidence of long-running/persistent background jobs managed by Steel, and independent confirmation of autonomous unattended runs.

   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the browser.”
   • [claimed-docs] “The Steel integration runs each agent's browser actions on a Steel cloud session, so AgentKit handles the orchestration and Steel handles th…”
   • [claimed-docs] “The Steel integration exposes a Steel browser as a CrewAI tool, so your crew can search, navigate, fill forms, extract data, and validate re…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session, so you can stand up a typed browser agent that opens a session, navigate…”

   proof ↗⚑ flag

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

   weight 2 · round to Stagehand
   Stagehand✓fullcommunity9/10

   Stagehand's core act()/extract()/observe() APIs are explicitly natural-language driven ('write automation in plain English, no selectors'), with self-healing and structured output, and this is corroborated by community accounts calling it self-healing/resilient to DOM changes. missing for 10: independent hands-on benchmark of NL command accuracy across diverse real-world sites.

   • [claimed-docs] “Execute actions using natural language”
   • [claimed-docs] “Write automation in plain English. No selectors or complex syntax.”
   • [claimed-docs] “observe() discovers actionable elements on a page and returns structured actions you can execute or validate before acting.”
   • [claimed-docs] “Turn on `selfHeal` to re-infer an action when its recorded selector breaks.”
   • [community] “Playwright codegen is incredibly powerful, but still pretty brittle. Its DOM selectors are still hardcoded... With Stagehand, the code is se…”

   proof ↗⚑ flag

   Steel—none0/10

   Steel is a browser-automation infrastructure API for agents/developers, not itself an interface that accepts natural-language commands from a user; the CLI (steel-docs-8) is a scriptable command-line tool with structured commands, not NL input, and no evidence shows a chat/NL interface for operating Steel directly. missing for 10: any documented NL command interface, chatbot/assistant front-end, or evidence that end users type plain-English instructions to control Steel.

   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [claimed-docs] “Install Steel CLI and the steel-browser skill so your agent can control a browser.”

   proof ↗⚑ flag

Api quality

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

   weight 2 · round to Steel
   Stagehand—none0/10

   Stagehand's docs (docs.stagehand.dev) provide code snippets and an llms.txt for AI consumption, but there's no evidence of an interactive, runnable API reference (e.g., embedded sandbox/playground) — the probe explicitly found no OpenAPI/Swagger spec (404s), and no docs item mentions runnable in-browser examples. missing for 10: interactive/runnable code playground, OpenAPI/API-explorer UI, evidence of executable examples within the docs site.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.stagehand.dev/openapi.json, https://docs.stagehand.dev/swagger.json, https://docs.stage…”
   • [claimed-docs] “This page gets you from an empty directory to a working automation in three steps.”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.stagehand.dev/llms.txt # Stagehand - [Introducing Stagehand](https://docs.stagehand.dev/v4/first-s…”

   proof ↗⚑ flag

   Steel~partialprobed5/10

   Steel documents dedicated API-reference pages ('Explore API endpoints for...') and exposes a live OpenAPI spec (openapi.json), and a community commenter independently praised the 'beautiful docs + api ref', suggesting a solid reference exists. However, there's no explicit evidence of interactive 'try it now' / runnable-example functionality within that reference (e.g., embedded request builders or live code execution) — missing for 10: confirmation of in-browser runnable/try-it examples, independent hands-on demonstration of executing calls directly from the docs.

   • [claimed-docs] “Explore API endpoints for managing Steel Captchas.”
   • [claimed-docs] “Explore API endpoints for building on Steel.”
   • [claimed-docs] “Explore API endpoints for managing Steel Credentials.”
   • [claimed-docs] “Explore API Endpoints for managing Files on Steel.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.steel.dev/openapi.json — contains "openapi" key”
   • [community] “beautiful docs + api ref! what are you using? (cool that you're doing open-source browserbase also, excited to check this out)”

   proof ↗⚑ flag

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

   weight 2 · round to Steel
   Stagehand—none0/10

   Direct probes for OpenAPI/swagger specs all returned 404, and no documentation mentions a downloadable machine-readable API spec; Stagehand is an SDK/library, not an HTTP API with a published spec.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.stagehand.dev/openapi.json, https://docs.stagehand.dev/swagger.json, https://docs.stage…”

   proof ↗⚑ flag

   Steel✓fullprobed9/10

   Steel exposes a live, machine-readable OpenAPI spec confirmed via probe (HTTP 200 with valid 'openapi' key), and docs reference extensive API endpoint documentation (steel-docs-13 through steel-docs-16) built on this spec. Missing for 10: no independent/community confirmation of the OpenAPI spec's completeness or third-party tooling built against it.

   • [probe] “PROBE openapi: HTTP 200 at https://docs.steel.dev/openapi.json — contains "openapi" key”
   • [claimed-docs] “Explore API endpoints for building on Steel.”
   • [claimed-docs] “Explore API endpoints for managing Steel Captchas.”
   • [claimed-docs] “Explore API endpoints for managing Steel Credentials.”
   • [claimed-docs] “Explore API Endpoints for managing Files on Steel.”

   proof ↗⚑ flag

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

   weight 1 · round to Steel
   Stagehand—none0/10

   Evidence covers browser automation features (act/observe/extract, caching, session persistence, Browserbase regions) but nothing addresses sandboxed test environments or isolation from production data/systems. Missing for 10: any mention of staging/sandbox environment configuration, data isolation guarantees, or safeguards against touching production systems.

   ⚑ flag

   Steel✓fullclaimed7/10

   Steel's Sessions API explicitly provisions isolated browser instances, each with its own state, cookies, and storage, letting an agent test without affecting other sessions or shared/production data, and session lifecycle docs show sessions can be created/torn down independently (steel-docs-1, steel-docs-10, steel-docs-33). Self-hosted Docker image and CLI further support standing up isolated test environments (steel-gh-4, steel-docs-8). Missing for 10: independent/hands-on verification that isolation holds in practice, and no explicit framing of 'sandbox vs production' terminology in the docs.

   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [claimed-docs] “Steel generates a session ID for you, but `create` also accepts one. Pass your own UUID when the ID has to exist before the browser does”
   • [claimed-docs] “Session Lifecycle | Steel Docs”
   • [github] “Pre-built Docker Image (combined API + UI)”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”

   proof ↗⚑ flag

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

   weight 2 · round to Stagehand
   Stagehand~partialclaimed3/10

   Docs show a versioned structure (v3 vs v4 paths, e.g. stagehand-docs-28 through -32 under /v3/ and current docs under /v4/), implying some API versioning practice, but there is no documented deprecation policy, migration timeline, or changelog referenced anywhere in the evidence. missing for 10: explicit deprecation policy, version support lifecycle/migration guide, changelog of breaking changes.

   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”
   • [claimed-docs] “This guide shows you how to use Stagehand's built-in auto-caching to convert agent-discovered workflows into fast, deterministic scripts tha…”
   • [claimed-docs] “Use an agent fallback as a failsafe when a one step action unexpectedly becomes a multi-step flow.”
   • [claimed-docs] “Control browsers using plain English commands like "click the login button" or "fill out the contact form"”
   • [claimed-docs] “The StagehandTool wraps the Stagehand Python SDK to provide CrewAI agents with the ability to control a real web browser and interact with w…”
   • [claimed-docs] “This page gets you from an empty directory to a working automation in three steps.”

   proof ↗⚑ flag

   Steel—none0/10

   Evidence shows an OpenAPI spec and extensive API documentation, but nothing addresses API versioning scheme or a documented deprecation policy. missing for 10: versioning scheme documentation, deprecation policy, changelog/migration guides for breaking changes.

   • [probe] “PROBE openapi: HTTP 200 at https://docs.steel.dev/openapi.json — contains "openapi" key”
   • [claimed-docs] “Explore API endpoints for building on Steel.”

   proof ↗⚑ flag

Compat

1. developerConnect my existing Playwright, Puppeteer, or CDP automation code to the product's browsers instead of rewriting it

   weight 2 · round to Steel
   Stagehand~partialcommunity7/10

   Docs show Stagehand attaches to any existing Chromium browser via CDP (localBrowser.connect) and lets developers use familiar Playwright page methods/selectors directly alongside AI actions, which supports bringing over existing Playwright/CDP automation code. However, there's no explicit mention of Puppeteer compatibility, and one community comment notes Stagehand is designed to run directly rather than as a drop-in wrapper for pre-existing Playwright/Puppeteer test suites. Missing for 10: explicit Puppeteer support/migration docs, hands-on confirmation of reusing full existing Playwright/Puppeteer codebases without rewrites.

   • [claimed-docs] “When you know the selector or want zero inference, use page methods you already know.”
   • [claimed-docs] “Attach over CDP (localBrowser.connect): Attach to any Chromium browser you are already running, by URL”
   • [claimed-docs] “Playwright was built for testing, Stagehand is built for agents. Use familiar APIs, self-healing actions, and network-level security across …”
   • [claimed-docs] “There are three ways to get one: **Browserbase (`browserbase.launch`)**... **Local (`localBrowser.launch`)**... **Attach over CDP (`localBro…”
   • [community] “This looks very cool and makes a lot of sense, except for the idea that it should take the place of Playwright et al. Personally I'd love to…”

   proof ↗⚑ flag

   Steel✓fullclaimed8/10

   GitHub docs explicitly state Steel exposes CDP endpoints that let developers connect using Puppeteer, Playwright, or Selenium, meaning existing automation code can target Steel's browsers with minimal rewrite, and the Sessions API/session lifecycle docs support this connection model. Missing for 10: independent hands-on developer reports confirming drop-in compatibility and more detail on any required code changes beyond endpoint swapping.

   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”
   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [claimed-docs] “Steel generates a session ID for you, but `create` also accepts one. Pass your own UUID when the ID has to exist before the browser does”
   • [claimed-docs] “Session Lifecycle | Steel Docs”

   proof ↗⚑ flag

Credentials

1. automation-engineerStore credentials in a vault and have the agent complete logins including TOTP/2FA challenges without exposing secrets to the model

   weight 2 · round to Steel
   Stagehand—none0/10

   No evidence of a credential vault, secure secret injection, or TOTP/2FA handling in Stagehand's docs or community sources; the pack covers session persistence via cookies/local storage but not secret management or MFA challenge automation.

   ⚑ flag

   Steel~partialclaimed3/10

   Steel documents a 'Credentials' API endpoint and separate 'Reusing Auth Context' feature for persisting authenticated sessions/cookies across runs, which addresses avoiding repeated logins, but there is no evidence describing a credential vault workflow, TOTP/2FA handling, or explicit guarantees that secrets are withheld from the model during login. missing for 10: dedicated vault/secrets-manager docs, TOTP/2FA challenge handling, explicit model-isolation guarantee for credentials, independent corroboration.

   • [claimed-docs] “Explore API endpoints for managing Steel Credentials.”
   • [claimed-docs] “This is particularly useful for maintaining authenticated states across multiple sessions, helping your AI agents access protected resources…”
   • [claimed-docs] “Reusing Context & Auth | Steel Docs”

   proof ↗⚑ flag

Profiles

1. developerPersist logged-in browser state in reusable profiles so agents skip the login wall on every subsequent run

   weight 3 · round drawn
   Stagehand✓fullclaimed8/10

   Docs explicitly describe persisting local browser user-data directories (cookies/local storage survive across runs) and Browserbase contexts for persisting session/browser data across cloud runs, directly matching the reusable-profile/login-skip story. Missing for 10: independent hands-on confirmation that a persisted profile actually skips a real login wall, and more detail on context lifecycle/expiry limits.

   • [claimed-docs] “Stagehand creates the directory if it does not exist and leaves it in place after the browser shuts down, so the next run starts from the sa…”
   • [claimed-docs] “For Browserbase sessions, use contexts to persist browser data”
   • [claimed-docs] “Browserbase runs browsers in four regions, so you can cut latency by starting the browser near your users or your target site, and keep sess…”

   proof ↗⚑ flag

   Steel✓fullclaimed8/10

   Steel's docs explicitly describe reusing auth context/persistent profiles across sessions so agents can access protected resources without repeating login flows, backed by a dedicated docs page and general session state/cookie persistence via the Sessions API. Missing for 10: independent/hands-on developer confirmation that reused profiles reliably skip login walls in practice, and more detail on profile creation/management UX.

   • [claimed-docs] “This is particularly useful for maintaining authenticated states across multiple sessions, helping your AI agents access protected resources…”
   • [claimed-docs] “Reusing Context & Auth | Steel Docs”
   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”

   proof ↗⚑ flag

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

   weight 2 · round to Steel
   Stagehand—none0/10

   Stagehand's docs focus on single-page primitives (act/observe/extract) and single-session agent workflows; there is no evidence of built-in bulk/batch operation support (e.g., running the same action across many items, URLs, or records in parallel) or a bulk API surface. missing for 10: any documentation of parallel/batch execution across multiple items, batch job scheduling, or a bulk-processing API.

   ⚑ flag

   Steel~partialclaimed4/10

   Steel supports spinning up many isolated browser sessions concurrently (Sessions API, CLI, SDK integrations) which enables running many browser tasks in parallel, but there is no explicit documentation of a bulk/batch operations API (e.g., batch session creation, bulk item processing, or queue-based multi-item automation) — the evidence only shows single-session workflows orchestrated one at a time via various agent frameworks. missing for 10: explicit bulk/batch API or documented pattern for orchestrating many items at once, concurrency limits/guidance, and any hands-on evidence of large-scale parallel session usage.

   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [claimed-docs] “Steel generates a session ID for you, but `create` also accepts one. Pass your own UUID when the ID has to exist before the browser does”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [claimed-docs] “This is particularly useful for maintaining authenticated states across multiple sessions, helping your AI agents access protected resources…”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   Stagehand—none0/10

   Stagehand's docs describe imperative act()/extract()/observe() calls and agent-driven workflows, plus self-healing selector re-inference, but there is no evidence of a mechanism for AI-native users to define persistent 'if event then action' rules that trigger automatically outside of a script's control flow.

   • [claimed-docs] “Turn on `selfHeal` to re-infer an action when its recorded selector breaks.”
   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”
   • [claimed-docs] “Use an agent fallback as a failsafe when a one step action unexpectedly becomes a multi-step flow.”

   proof ↗⚑ flag

   Steel—none0/10

   Steel's evidence covers sessions, proxies, captcha solving, CLI, and agent traces, but nothing describes a rules engine or event-triggered automation (e.g., 'if X happens then do Y') that a user could configure declaratively.

   ⚑ flag

Local

1. developerRun the agent against a local browser on my own machine for development, without any cloud account

   weight 2 · round to Stagehand
   Stagehand✓fullclaimed8/10

   Docs explicitly describe launching a Local browser (`localBrowser.launch`) or attaching over CDP to a Chromium instance you're already running, as alternatives to Browserbase cloud sessions, and the quickstart shows getting from an empty directory to a working automation without mention of requiring a cloud account. This directly supports running against a local browser for development. Missing for 10: no independent/hands-on confirmation of a fully offline/no-account local workflow, and no explicit statement that no API keys/cloud accounts are ever needed for LLM inference during local runs.

   • [claimed-docs] “There are three ways to get one: **Browserbase (`browserbase.launch`)**... **Local (`localBrowser.launch`)**... **Attach over CDP (`localBro…”
   • [claimed-docs] “Attach over CDP (localBrowser.connect): Attach to any Chromium browser you are already running, by URL”
   • [claimed-docs] “This page gets you from an empty directory to a working automation in three steps.”

   proof ↗⚑ flag

   Steel✓fullclaimed7/10

   Steel is explicitly open-source with a pre-built Docker image combining the API and UI, letting a developer self-host the browser locally, and it exposes CDP so Puppeteer/Playwright/Selenium can connect directly to a local instance without any cloud account (steel-gh-4, steel-gh-1, steel-gh-5). This directly satisfies running an agent against a local browser for development. Missing for 10: a dedicated 'local dev quickstart' doc walking through docker-compose setup and confirmation that no cloud sign-in/telemetry is required, plus independent hands-on confirmation of local-only usage.

   • [github] “Pre-built Docker Image (combined API + UI)”
   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”
   • [github] “Steel.dev is an open-source browser API that makes it easy to build AI apps and agents that interact with the web. Instead of building autom…”

   proof ↗⚑ flag

Frameworks

1. developerPlug the browser layer into agent frameworks (Claude Agent SDK, Vercel AI SDK, LangChain, CrewAI) through documented adapters

   weight 2 · round to Steel
   Stagehand~partialclaimed5/10

   Docs confirm dedicated adapters for CrewAI (stagehand-docs-25, stagehand-docs-32) and Claude Code via MCP/stdio (stagehand-docs-11), plus a generic 'integrations overview' pattern of run/snapshot/screenshot tools (stagehand-docs-22, stagehand-docs-24). However, there is no evidence of documented adapters for Vercel AI SDK or LangChain, and 'Claude Agent SDK' is only implied via Claude Code/MCP rather than explicitly named. missing for 10: explicit LangChain adapter docs, explicit Vercel AI SDK adapter docs, confirmation that the Claude Code MCP integration equals the 'Claude Agent SDK' specifically.

   • [claimed-docs] “Give a Claude Code agent persistent Stagehand browser tools over MCP/stdio.”
   • [claimed-docs] “Each integration gives your agent one persistent browser and three tools: `run`, `snapshot`, and `screenshot`.”
   • [claimed-docs] “The Deep Agents integration provides two deployment patterns with the same `run`, `snapshot`, and `screenshot` tools.”
   • [claimed-docs] “One server process owns the browser, so page state survives across `run`, `snapshot`, and `screenshot` calls.”
   • [claimed-docs] “The StagehandTool wraps the Stagehand Python SDK to provide CrewAI agents with the ability to control a real web browser and interact with w…”

   proof ↗⚑ flag

   Steel✓fullclaimed8/10

   Steel documents dedicated integration guides for Claude Agent SDK, Vercel AI SDK, LangChain-adjacent (CrewAI), and other frameworks, each describing how Steel's cloud browser plugs in as a tool/MCP server for the agent loop (steel-docs-9/43, steel-docs-39, steel-docs-40, plus AgentKit, OpenAI Agents SDK, Pydantic AI). Missing for 10: explicit LangChain-named adapter page (only CrewAI/AgentKit/AI SDK/Claude named) and independent/hands-on confirmation beyond vendor docs.

   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the browser.”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session (open, navigate, snapshot, extract, return typed results)”
   • [claimed-docs] “The Steel integration exposes a Steel browser as a CrewAI tool, so your crew can search, navigate, fill forms, extract data, and validate re…”
   • [claimed-docs] “The Steel integration runs each agent's browser actions on a Steel cloud session, so AgentKit handles the orchestration and Steel handles th…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session, so you can stand up a typed browser agent that opens a session, navigate…”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the brow”
   • [claimed-docs] “Expose a Steel browser to any MCP client”

   proof ↗⚑ flag

Models

1. developerBring my own LLM provider — the framework is model-agnostic rather than locked to one vendor's models

   weight 2 · round drawn
   Stagehand✓fullclaimed7/10

   Docs explicitly state you can customize the agent by specifying the LLM provider and model, indicating Stagehand is not locked to a single vendor's models [stagehand-docs-28]. However, evidence doesn't enumerate the full list of supported providers or show independent confirmation of multi-provider use in practice. missing for 10: a documented list of supported LLM providers/models, independent/community confirmation of switching providers.

   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”

   proof ↗⚑ flag

   Steel✓fullclaimed7/10

   Steel documents integrations across many LLM/agent ecosystems — OpenAI Computer Use, Claude Computer Use, Gemini Computer Use, Browser-Use, CrewAI, Pydantic AI (explicitly 'provider-agnostic'), OpenAI Agents SDK, AI SDK, Claude Agent SDK — showing it is not locked to a single vendor's models and can be paired with whichever LLM the developer chooses. Missing for 10: an explicit first-party 'model-agnostic' positioning statement and independent/community corroboration of using Steel with a non-default LLM provider.

   • [claimed-docs] “Use Gemini Computer Use with Steel Browser.”
   • [claimed-docs] “Use Claude Computer Use with Steel Browser.”
   • [claimed-docs] “The OpenAI Computer Use integration runs OpenAI's vision-based agent loop on a Steel browser session.”
   • [claimed-docs] “Use Browser-Use to interact with a Steel browser.”
   • [claimed-docs] “Build a Pydantic AI browser agent on Steel cloud browsers: provider-agnostic, typed Python agents with dependency injection and real web acc…”
   • [claimed-docs] “The Steel integration runs each agent's browser actions on a Steel cloud session, so AgentKit handles the orchestration and Steel handles th…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session (open, navigate, snapshot, extract, return typed results)”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session, so you can stand up a typed browser agent that opens a session, navigate…”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the brow”

   proof ↗⚑ flag

Tasks

1. ai agentSubmit a browser task over a hosted HTTP API and receive the result by polling or webhook, without managing any browser myself

   weight 2 · round to Steel
   Stagehand—none0/10

   Stagehand is an SDK (TypeScript/Python/Go) that developers embed in their own code to drive a browser (local or Browserbase-hosted), not a hosted HTTP API where an agent submits a task and polls or receives a webhook for the result; the probe explicitly found no OpenAPI/API endpoints (404s across all candidate paths). Evidence only shows Browserbase providing remote browser infrastructure and session dashboards, not a task-submission/result-retrieval API contract.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.stagehand.dev/openapi.json, https://docs.stagehand.dev/swagger.json, https://docs.stage…”
   • [claimed-docs] “Browserbase runs browsers in four regions, so you can cut latency by starting the browser near your users or your target site, and keep sess…”
   • [claimed-docs] “Playwright was built for testing, Stagehand is built for agents. Use familiar APIs, self-healing actions, and network-level security across …”

   proof ↗⚑ flag

   Steel~partialclaimed4/10

   Steel's Sessions API lets an agent spin up a hosted, isolated browser via HTTP without managing browser infrastructure (steel-docs-1, steel-docs-33), and its agent-trace/timeline features (steel-docs-6, steel-docs-27, steel-docs-29) could support polling for run results. But there is no evidence of a discrete 'submit task, get result via polling/webhook' primitive — the model shown is that the agent (or a partner SDK like AgentKit/CrewAI) still drives actions step-by-step over CDP/Puppeteer/Playwright or the CLI (steel-gh-1, steel-docs-8), not a single task-submission endpoint. Missing for 10: an explicit task/job endpoint, webhook-based completion notification, and confirmation that the calling agent need not issue any browser actions itself.

   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [claimed-docs] “Session Lifecycle | Steel Docs”
   • [claimed-docs] “It turns the run into a timeline of agent activity, so you can see what happened without scrubbing through the whole recording.”
   • [claimed-docs] “Agent Traces: Observability for Browser Agents | Steel Docs”
   • [claimed-docs] “Agent Traces API | Steel Docs”
   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”

   proof ↗⚑ flag

2. developerHand the product a natural-language goal and it completes a multi-step web task end to end — navigating, filling forms, and clicking through flows

   weight 3 · round to Stagehand
   Stagehand✓fullcommunity8/10

   Stagehand's `agent` primitive explicitly turns high-level natural-language tasks into fully autonomous multi-step browser workflows (navigating, clicking, filling forms), backed by act/observe/extract primitives and self-healing selectors, with community corroboration of natural-language control and self-healing resilience. missing for 10: independent end-to-end hands-on validation of a complex multi-step flow (e.g., checkout) succeeding autonomously, and quantitative reliability/success-rate data beyond docs and anecdotal HN comments.

   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”
   • [claimed-docs] “Playwright was built for testing, Stagehand is built for agents. Use familiar APIs, self-healing actions, and network-level security across …”
   • [claimed-docs] “Write automation in plain English. No selectors or complex syntax.”
   • [claimed-docs] “observe() discovers actionable elements on a page and returns structured actions you can execute or validate before acting.”
   • [claimed-docs] “extract() grabs structured data from a webpage. Every call takes an instruction and an output shape”
   • [claimed-docs] “Turn on `selfHeal` to re-infer an action when its recorded selector breaks.”
   • [community] “Playwright codegen is incredibly powerful, but still pretty brittle. Its DOM selectors are still hardcoded... With Stagehand, the code is se…”
   • [community] “I've been playing around with Stagehand for a minute now, actually a useful abstraction here. We build scrapers for websites that are pretty…”

   proof ↗⚑ flag

   Steel~partialclaimed6/10

   Steel provides the browser infrastructure (sessions, navigation, click/fill/extract via CLI or API) and integrates with third-party agent loops (Claude/OpenAI Computer Use, browser-use, CrewAI, OpenAI Agents SDK) that can take a natural-language goal and drive multi-step web flows end-to-end, but Steel itself explicitly delegates the 'agent loop'/reasoning to these other SDKs rather than natively interpreting NL goals itself (e.g. 'the SDK runs the agent loop and Steel handles the browser'). The CLI supports scripted end-to-end browser workflows but not NL-goal parsing on its own. missing for 10: a native Steel agent loop that itself parses an NL goal and autonomously plans/executes steps without pairing with an external agent SDK; independent hands-on evidence of a full NL-to-task run succeeding.

   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the browser.”
   • [claimed-docs] “The OpenAI Computer Use integration runs OpenAI's vision-based agent loop on a Steel browser session.”
   • [claimed-docs] “Use Browser-Use to interact with a Steel browser.”
   • [claimed-docs] “The Steel integration exposes a Steel browser as a CrewAI tool, so your crew can search, navigate, fill forms, extract data, and validate re…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session, so you can stand up a typed browser agent that opens a session, navigate…”
   • [claimed-docs] “Use Gemini Computer Use with Steel Browser.”
   • [claimed-docs] “Use Claude Computer Use with Steel Browser.”

   proof ↗⚑ flag

Workflows

1. automation-engineerCompose repeatable multi-step workflows with loops, conditionals, and parameters instead of one-shot prompts

   weight 2 · round to Stagehand
   Stagehand~partialclaimed5/10

   Stagehand is an SDK (act/observe/extract primitives) embedded in normal TS/Python/Go code, and docs note 'you are already writing the orchestration' (stagehand-docs-26) and describe converting 'agent-discovered workflows' into deterministic scripts (stagehand-docs-29), implying loops/conditionals/parameters come from the host language rather than a built-in workflow engine. There's no explicit documentation of a dedicated workflow-composition feature (e.g., parameterized flows, branching primitives) as a first-class product capability. Missing for 10: explicit docs/examples of parameterized reusable workflows, native conditional/loop constructs, or a workflow templating system beyond raw host-language code.

   • [claimed-docs] “Interleave your tool results with Stagehand's primitives. Because v4 has no autonomous loop, you are already writing the orchestration, so a…”
   • [claimed-docs] “This guide shows you how to use Stagehand's built-in auto-caching to convert agent-discovered workflows into fast, deterministic scripts tha…”
   • [claimed-docs] “Use an agent fallback as a failsafe when a one step action unexpectedly becomes a multi-step flow.”

   proof ↗⚑ flag

   Steel—none0/10

   Steel's CLI and Sessions API support running sequential browser steps (navigate, click, extract, stop) via terminal or SDK, but nothing in the evidence describes composing workflows with loops, conditionals, or parameterized reusable flows — that logic is left to whichever orchestrating agent framework (CrewAI, AgentKit, etc.) sits on top of Steel. Missing for 10: any documentation of control-flow constructs (loops/branches), workflow parameters, or a workflow builder/editor within Steel itself.

   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [claimed-docs] “The Steel integration exposes a cloud browser as in-process MCP tools, so the SDK runs the agent loop and Steel handles the browser.”
   • [claimed-docs] “The Steel integration runs each agent's browser actions on a Steel cloud session, so AgentKit handles the orchestration and Steel handles th…”
   • [claimed-docs] “The Steel integration exposes a Steel browser as a CrewAI tool, so your crew can search, navigate, fill forms, extract data, and validate re…”

   proof ↗⚑ flag

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

   weight 3 · round to Steel
   Stagehand—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

   Steel~partialclaimed4/10

   Steel documents exporting agent trace/session run data in open formats (markdown, JSON, ZIP with screenshots) and is itself open-source/self-hostable via Docker, giving users a path to leave the managed cloud. However there is no documentation of exporting other data types (credentials, files, session history/metadata, account data) in open formats, nor any explicit 'export everything and leave' workflow. missing for 10: full-account data export (credentials, files, session records) in open formats, documented data-portability/deletion workflow, independent confirmation of successful export/migration.

   • [claimed-docs] “Copy the run as markdown, download JSON, or grab a ZIP with markdown plus screenshots.”
   • [claimed-docs] “Agent Traces: Observability for Browser Agents | Steel Docs”
   • [github] “Pre-built Docker Image (combined API + UI)”
   • [github] “Steel.dev is an open-source browser API that makes it easy to build AI apps and agents that interact with the web. Instead of building autom…”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”

   proof ↗⚑ flag

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

   weight 2 · round to Steel
   Stagehand—none0/10

   No evidence pack item mentions a GitHub repository, license (e.g., MIT/Apache), or any statement about source availability; all evidence is docs/community discussion of features, not code openness.

   ⚑ flag

   Steel✓fullclaimed8/10

   Steel is explicitly described as an open-source browser API with a public GitHub repository (steel-dev/steel-browser) containing the source code, docs, and Docker image, confirming readable open-source code. Missing for 10: explicit statement of the license type (e.g., MIT/Apache) in the evidence pack and independent confirmation of license terms.

   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”
   • [github] “Pre-built Docker Image (combined API + UI)”
   • [github] “Steel.dev is an open-source browser API that makes it easy to build AI apps and agents that interact with the web. Instead of building autom…”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”
   • [claimed-docs] “Steel is an open source browser API that lets you control fleets of browsers in the cloud.”

   proof ↗⚑ flag

3. ai-native userSelf-host the core product

   weight 3 · round to Steel
   Stagehand~partialclaimed6/10

   Stagehand is an open-source automation library that can run entirely locally without depending on Browserbase's cloud service, via `localBrowser.launch` or attaching over CDP to a browser you already run — meaning the core product can be self-hosted rather than requiring the vendor's cloud backend. However, there's no explicit self-hosting/deployment guide, container image, or independent confirmation of a fully self-hosted setup (caching and observability features still reference Browserbase-hosted infra). Missing for 10: dedicated self-host deployment docs, containerization/infra guidance, and community corroboration of running fully self-hosted.

   • [claimed-docs] “There are three ways to get one: **Browserbase (`browserbase.launch`)**... **Local (`localBrowser.launch`)**... **Attach over CDP (`localBro…”
   • [claimed-docs] “Attach over CDP (localBrowser.connect): Attach to any Chromium browser you are already running, by URL”
   • [claimed-docs] “When you know the selector or want zero inference, use page methods you already know.”

   proof ↗⚑ flag

   Steel✓fullcommunity8/10

   Steel is explicitly open-source (steel-dev/steel-browser repo) and ships a pre-built combined API+UI Docker image, letting an AI-native user self-host the core product; community comments corroborate its open-source nature. Missing for 10: detailed self-host deployment/config docs (scaling, storage, auth setup) beyond the single Docker image mention, and no independent hands-on report of a successful self-hosted deployment.

   • [github] “Pre-built Docker Image (combined API + UI)”
   • [github] “Steel.dev is an open-source browser API that makes it easy to build AI apps and agents that interact with the web. Instead of building autom…”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”
   • [claimed-docs] “Steel is an open source browser API that lets you control fleets of browsers in the cloud.”
   • [community] “beautiful docs + api ref! what are you using? (cool that you're doing open-source browserbase also, excited to check this out)”

   proof ↗⚑ flag

Pricing

1. developerSee transparent per-task or per-browser-hour pricing and documented rate/concurrency limits before committing

   weight 2 · round to Steel
   Stagehand—none0/10

   No evidence pack item discusses Stagehand's pricing, per-task/per-browser-hour costs, or documented rate/concurrency limits; documentation focuses on features, integrations, and configuration only.

   ⚑ flag

   Steel!disputedcontradicted3/10

   There is a pricing page implied but no documented rate/concurrency limits in the evidence pack, and community evidence directly contradicts pricing transparency: a user reports the pricing page shows $59 while the docs show $99 for the developer tier, indicating inconsistent/undocumented pricing rather than clear transparent pricing. missing for 10: documented per-task or per-browser-hour rate card, documented concurrency/rate limits, resolution of the pricing discrepancy, independent confirmation of consistent current pricing.

   • [community] “Looking interesting, will definitely give it a go. Btw, there is inconsistency between pricing page and pricing on docs. Pricing page for de…”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”

   proof ↗⚑ flag

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

   weight 2 · round to Stagehand
   Stagehand~partialclaimed6/10

   Docs state Browserbase-hosted sessions can be started in one of four regions and that this can keep session data in a required jurisdiction, giving some data-residency control (stagehand-docs-9). However this only covers Browserbase-run browser sessions, not other data flows like server-side act/observe/extract caching (stagehand-docs-6) or local user-data directories (stagehand-docs-7), and there is no independent/hands-on confirmation of residency guarantees. Missing for 10: region control over cached LLM/action results and other stored artifacts, explicit compliance/residency guarantees, and third-party verification.

   • [claimed-docs] “Browserbase runs browsers in four regions, so you can cut latency by starting the browser near your users or your target site, and keep sess…”
   • [claimed-docs] “Stagehand caches `act()`, `observe()`, and `extract()` results server-side to reduce LLM costs and speed up your automations.”
   • [claimed-docs] “Stagehand creates the directory if it does not exist and leaves it in place after the browser shuts down, so the next run starts from the sa…”

   proof ↗⚑ flag

   Steel—none0/10

   No evidence in the pack mentions data residency, region selection, or geographic hosting options for Steel's cloud browser sessions; docs cover proxies, sessions, stealth, and integrations but never data storage location controls. Missing for 10: any mention of region selection, data residency options, or geographic data storage controls.

   ⚑ flag

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

   weight 3 · round drawn
   Stagehand—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

   Steel—none0/10

   No evidence pack item addresses AI training data usage or opt-out policies for Steel; the docs focus on browser automation, sessions, proxies, and integrations with no mention of a data-training privacy commitment.

   ⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round drawn
   Stagehand—none0/10

   Docs describe persisting user data (cookies/local storage, Browserbase contexts) and choosing a data region for jurisdiction, but there is no evidence of any deletion controls, retention limits, or user-facing settings to purge stored session/browser data. missing for 10: explicit retention policy, deletion/purge mechanism, and user controls over how long session data or extracted data is kept.

   • [claimed-docs] “Stagehand creates the directory if it does not exist and leaves it in place after the browser shuts down, so the next run starts from the sa…”
   • [claimed-docs] “For Browserbase sessions, use contexts to persist browser data”
   • [claimed-docs] “Browserbase runs browsers in four regions, so you can cut latency by starting the browser near your users or your target site, and keep sess…”

   proof ↗⚑ flag

   Steel—none0/10

   While Steel manages sessions, credentials, and files (which could involve data retention concerns), no evidence describes user-facing controls for data retention periods, deletion policies, or GDPR-style data purging.

   ⚑ flag

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

   weight 2 · round drawn
   Stagehand—none0/10

   No evidence pack mention of telemetry collection, usage tracking, or an opt-out mechanism/env variable/config flag for Stagehand; the axis is applicable since developer tools commonly ship telemetry controls, but no documentation or community evidence addresses it.

   ⚑ flag

   Steel—none0/10

   No evidence pack item mentions telemetry, usage analytics, or an opt-out/opt-in setting for data collection; Steel is open-source and self-hostable which could make this a fair question, but no documentation addresses it.

   ⚑ flag

Live

1. automation-engineerWatch a session live and take human control mid-run when the agent gets stuck

   weight 2 · round to Steel
   Stagehand~partialclaimed4/10

   Stagehand docs mention Browserbase's session dashboard offering real-time screen recording/replay for observability (stagehand-docs-10), which supports 'watching a session live,' but there is no evidence of a mechanism for a human to seize control mid-run when the agent stalls — no handoff, pause-and-resume, or manual override feature is documented. missing for 10: documented human-takeover/handoff control during an active agent run, evidence of pausing autonomous execution for manual intervention, independent confirmation of live control switching.

   • [claimed-docs] “Browserbase provides real-time visibility into your automation sessions: **Session dashboard features** * Real-time browser screen recordi…”
   • [claimed-docs] “`agent` turns high level tasks into **fully autonomous** browser workflows. You can customize the agent by specifying the LLM provider and m…”

   proof ↗⚑ flag

   Steel✓fullclaimed7/10

   Steel's debug URL / human-in-the-loop feature explicitly enables watching a live session and taking direct control when an agent gets stuck, and embed-sessions support live viewing in an app context. Missing for 10: independent/hands-on verification of the live handoff experience and no detail on how control reverts to the agent after human intervention.

   • [claimed-docs] “Steel's debug URL feature allows you to implement human-in-the-loop workflows where users can directly interact with and control browser ses…”
   • [claimed-docs] “Implement Human-in-the-Loop Controls | Steel Docs”
   • [claimed-docs] “Embed Sessions](/overview/sessions-api/embed-sessions)”

   proof ↗⚑ flag

Replay

1. automation-engineerDebug a failed agent run from recorded replays — video, screenshots, step-by-step action timelines

   weight 2 · round to Steel
   Stagehand~partialclaimed5/10

   Stagehand docs mention Browserbase's session dashboard providing real-time screen recording and replay (stagehand-docs-10), and integrations expose a screenshot tool (stagehand-docs-22), giving partial support for replay-based debugging. However there is no documented step-by-step action timeline or dedicated debugging UI beyond the generic session recording feature, and no community corroboration of using these for debugging failed runs. Missing for 10: dedicated action-timeline/step-log feature, explicit debugging workflow docs, independent hands-on confirmation of replay-based debugging.

   • [claimed-docs] “Browserbase provides real-time visibility into your automation sessions: **Session dashboard features** * Real-time browser screen recordi…”
   • [claimed-docs] “Each integration gives your agent one persistent browser and three tools: `run`, `snapshot`, and `screenshot`.”

   proof ↗⚑ flag

   Steel✓fullclaimed7/10

   Steel's Agent Traces feature explicitly turns a run into a step-by-step timeline of agent activity, and lets you export the run as markdown, JSON, or a ZIP with markdown plus screenshots, directly supporting replay debugging; session replays and debug URLs (live session view) are also documented. Missing for 10: independent/hands-on corroboration of the replay/timeline UI actually working, and explicit detail on 'video' replay format beyond the general 'session replays' tagline.

   • [claimed-docs] “It turns the run into a timeline of agent activity, so you can see what happened without scrubbing through the whole recording.”
   • [claimed-docs] “Copy the run as markdown, download JSON, or grab a ZIP with markdown plus screenshots.”
   • [claimed-docs] “Agent Traces: Observability for Browser Agents | Steel Docs”
   • [claimed-docs] “Timeline and exports | Steel Docs”
   • [claimed-docs] “Agent Traces API | Steel Docs”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”
   • [claimed-docs] “Steel's debug URL feature allows you to implement human-in-the-loop workflows where users can directly interact with and control browser ses…”

   proof ↗⚑ flag

Fleets

1. automation-engineerRun a fleet of concurrent browser sessions with documented concurrency limits and programmatic session management

   weight 2 · round to Steel
   Stagehand—none0/10

   The evidence pack covers single-session configuration (region selection, CDP attach, persistence) but contains no documentation of concurrency limits, fleet-level session orchestration, or programmatic management of multiple simultaneous sessions.

   ⚑ flag

   Steel~partialclaimed5/10

   Steel's Sessions API supports spinning up isolated on-demand browser sessions with programmatic lifecycle management (create, custom session IDs, session lifecycle docs) and a CLI/SDK for scripting sessions, which supports parallel automation use cases. However, there is no documented concurrency limit, fleet-level quota, or explicit guidance on running many sessions concurrently (rate limits, max parallel sessions per plan, autoscaling behavior) in the evidence provided. missing for 10: documented concurrency/session limits per plan, explicit fleet-scale orchestration guidance, benchmarks or independent confirmation of concurrent session handling at scale.

   • [claimed-docs] “the Sessions API lets your agents spin up isolated browser instances on demand. Each session maintains its own state, cookies, and storage”
   • [claimed-docs] “Steel generates a session ID for you, but `create` also accepts one. Pass your own UUID when the ID has to exist before the browser does”
   • [claimed-docs] “Session Lifecycle | Steel Docs”
   • [claimed-docs] “The Steel CLI lets you run full browser workflows from the terminal, end-to-end. You can start a browser session, navigate pages, click/fill…”
   • [github] “Uses Puppeteer and CDP for complete control over Chrome instances -- allowing you to connect using Puppeteer, Playwright, or Selenium.”

   proof ↗⚑ flag

Lifecycle

1. developerGet webhook notifications when tasks and sessions finish instead of polling for status

   weight 1 · round drawn
   Stagehand—none0/10

   No evidence of any webhook/callback mechanism for task or session completion; Stagehand's docs focus on act/observe/extract, caching, and session dashboards but nothing about push notifications replacing polling.

   ⚑ flag

   Steel—none0/10

   No evidence anywhere in the pack of a webhook or event-notification system for session/task completion; Steel's docs focus on session lifecycle, agent traces, and API endpoints but never mention webhooks or push notifications for status changes.

   ⚑ flag

Captcha

1. automation-engineerRely on a documented captcha stance — automatic solving, human fallback, or explicit non-support — instead of silent task failures

   weight 2 · round to Steel
   Stagehand~partialcommunity3/10

   Only a single community anecdote claims Stagehand/Browserbase have 'built in proxies and captcha' handling, but no first-party documentation in the pack states an explicit captcha policy (auto-solve, human fallback, or non-support). missing for 10: official docs describing captcha handling behavior, guidance on fallback/human-in-the-loop when captchas are hit, and independent verification beyond one forum comment.

   • [community] “I've been playing around with Stagehand for a minute now, actually a useful abstraction here. We build scrapers for websites that are pretty…”
   • [community] “I recently tried to implement a workflow automation using similar frameworks that were playwright or puppeteer based... What stopped me enti…”

   proof ↗⚑ flag

   Steel✓fullclaimed8/10

   Steel documents an explicit CAPTCHA stance: automatic solving is built into the stealth mode (one flag covers detection/solving/verification) with a dedicated captcha-solving doc and API endpoints, plus human-in-the-loop debug URLs for manual takeover as fallback, avoiding silent failures. Missing for 10: independent/hands-on confirmation that captcha solving actually succeeds in practice and clearer documentation of failure/error signaling when solving fails.

   • [claimed-docs] “One flag covers detection, solving, and verification for the whole session”
   • [claimed-docs] “What Is a CAPTCHA Solver? Automatic CAPTCHA Solving API | Steel Docs”
   • [claimed-docs] “Explore API endpoints for managing Steel Captchas.”
   • [claimed-docs] “Steel's debug URL feature allows you to implement human-in-the-loop workflows where users can directly interact with and control browser ses…”
   • [claimed-docs] “Implement Human-in-the-Loop Controls | Steel Docs”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”

   proof ↗⚑ flag

Posture

1. automation-engineerPoint to the vendor's published acceptable-use and anti-abuse posture governing what its stealth and automation features may be used for

   weight 1 · round drawn
   Stagehand—none0/10

   No evidence pack item references an acceptable-use policy, anti-abuse terms, or governance around stealth/automation/captcha-bypass usage; docs focus purely on technical capability and community comments only discuss captcha-evasion effectiveness, not policy.

   ⚑ flag

   Steel—none0/10

   The evidence pack contains extensive documentation of Steel's stealth, captcha-solving, and proxy features, but no published acceptable-use policy, anti-abuse guidelines, or terms governing what these features may legally/ethically be used for. No AUP, ToS excerpt, or abuse-prevention statement is cited anywhere in the pack.

   ⚑ flag

Stealth

1. automation-engineerEnable stealth fingerprinting and residential or geo-targeted proxies so legitimate automations aren't blocked as bots

   weight 2 · round to Steel
   Stagehand~partialcommunity5/10

   A community hands-on comment praises Stagehand/Browserbase's 'built in proxies and captcha' handling for adversarial sites, and docs confirm Browserbase supports multi-region session placement (geo-targeting) — but there is no first-party documentation of stealth fingerprinting configuration or explicit residential-proxy selection controls. missing for 10: dedicated docs on fingerprint spoofing/stealth mode, explicit residential proxy configuration options, and independent verification that bot-block evasion works reliably.

   • [community] “I've been playing around with Stagehand for a minute now, actually a useful abstraction here. We build scrapers for websites that are pretty…”
   • [community] “I recently tried to implement a workflow automation using similar frameworks that were playwright or puppeteer based... What stopped me enti…”
   • [claimed-docs] “Browserbase runs browsers in four regions, so you can cut latency by starting the browser near your users or your target site, and keep sess…”

   proof ↗⚑ flag

   Steel✓fullcommunity8/10

   Steel's docs explicitly describe stealth mode (bot-detection evasion + CAPTCHA solving in one flag) and both Managed Residential Proxies and Bring-Your-Own-Proxy options, directly matching the story; a community comment corroborates that custom proxies work. Missing for 10: explicit geo-targeting/country-selection documentation and independent hands-on verification that stealth actually reduces bot-blocking in production.

   • [claimed-docs] “One flag covers detection, solving, and verification for the whole session”
   • [claimed-docs] “Steel offers two powerful ways to use proxies: our built-in **Managed Residential Proxies** or connecting to your own proxy provider with ou…”
   • [claimed-docs] “Steel is the open-source browser API for AI agents — managed cloud browsers with stealth, residential proxies, CAPTCHA solving, persistent p…”
   • [community] “It appears you can set your own proxies to not use their cloud.”

   proof ↗⚑ flag

Extraction

1. developerExtract typed, schema-validated data (Zod/Pydantic-style) from pages the agent visits, not just raw text

   weight 3 · round to Stagehand
   Stagehand✓fullclaimed8/10

   Docs explicitly describe extract() taking an output shape and validating results against that shape before returning, so returned data is typed/schema-validated rather than raw text (stagehand-docs-2, stagehand-docs-17). This directly matches the story of schema-driven structured extraction from visited pages. Missing for 10: explicit mention of Zod/Pydantic naming and independent hands-on confirmation of schema validation behavior beyond first-party docs.

   • [claimed-docs] “extract() grabs structured data from a webpage. Every call takes an instruction and an output shape”
   • [claimed-docs] “Stagehand validates the result against that shape before returning it, so what you get back is already typed.”
   • [claimed-docs] “`observe()` discovers actionable elements on a page and returns structured actions you can execute or validate before acting.”

   proof ↗⚑ flag

   Steel~partialclaimed4/10

   Steel doesn't natively expose a Zod/Pydantic-style schema-validated extraction API, but several ecosystem integrations reference typed extraction — the AI SDK integration explicitly does 'extract, return typed results' and the Pydantic AI integration builds 'typed Python agents' on Steel sessions, implying schema validation is handled by those frameworks atop Steel's browser access rather than by Steel itself. Missing for 10: first-party Steel API/SDK documentation showing a defined schema (Zod or Pydantic model) passed directly to a Steel extraction endpoint, and independent confirmation that this pattern works reliably.

   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session (open, navigate, snapshot, extract, return typed results)”
   • [claimed-docs] “Build a Pydantic AI browser agent on Steel cloud browsers: provider-agnostic, typed Python agents with dependency injection and real web acc…”
   • [claimed-docs] “The Steel integration runs each tool against a Steel cloud session, so you can stand up a typed browser agent that opens a session, navigate…”
   • [github] “Browser Tools: Exposes APIs to quick convert pages to markdown, readability, screenshots, or PDFs.”

   proof ↗⚑ flag

Files

1. developerMy agent can download files from and upload files to the sites it operates, with the artifacts retrievable afterwards

   weight 1 · round to Steel
   Stagehand—none0/10

   No evidence in the pack describes file download/upload handling or retrievable artifact storage from browser sessions; Stagehand's docs focus on act/extract/observe automation, caching, and browser session config, not file transfer or artifact retrieval.

   ⚑ flag

   Steel~partialclaimed5/10

   Steel documents a Files API endpoint for managing files on Steel sessions (steel-docs-16), plus agent traces that can be downloaded as JSON/ZIP/markdown artifacts (steel-docs-7), suggesting some upload/download and artifact retrieval capability. However, there's no detailed documentation of the file upload/download workflow itself (e.g., how an agent uploads a file to a site form or downloads a file from a page and retrieves it via API), no code examples, and no independent verification of this working end-to-end. missing for 10: detailed docs/examples of agent-initiated file upload to sites and file download from sites, confirmation of artifact retrieval workflow, independent/hands-on corroboration.

   • [claimed-docs] “Explore API Endpoints for managing Files on Steel.”
   • [claimed-docs] “Copy the run as markdown, download JSON, or grab a ZIP with markdown plus screenshots.”
   • [claimed-docs] “It turns the run into a timeline of agent activity, so you can see what happened without scrubbing through the whole recording.”

   proof ↗⚑ flag