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Browser Use To Stagehand

BrowserbaseOfficialPublished by Browserbase

  • Skill
  • Workflow
  • Software development
  • MIT
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From the author

Migrate browser-use (Python) browser-automation scripts to Stagehand v3 (TypeScript) on Browserbase. Use when the user wants to convert, port, rewrite, or migrate a browser-use Agent script to Stagehand, map browser-use features/APIs to Stagehand primitives (act/extract/observe/agent), or move agentic browser automation onto Browserbase with more determinism. Triggers on "browser-use", "browser_use", or "Agent(task=...)".
— the description by Browserbase

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured methodology for porting browser-use (Python) agentic scripts to Stagehand v3 (TypeScript) on Browserbase. Rather than a direct transpilation, it emphasizes refactoring opaque agent loops into inspectable, deterministic pipelines. By applying a determinism spectrum, it helps developers replace LLM-heavy agentic steps with specific Stagehand primitives (act, extract, observe) where the page flow is predictable, reserving AI-driven agents only for genuinely open-ended tasks.

What it does

  • Analyzes browser-use scripts to extract tasks, browser configurations, and custom actions.
  • Maps agentic browser-use steps to Stagehand v3 primitives based on a determinism decision tree.
  • Generates runnable TypeScript code using Stagehand v3 and Zod for structured data extraction.
  • Provides setup templates for package.json, environment variables, and index.ts.
  • Offers a trace-assisted workflow for debugging and migrating flaky or opaque agent scripts.
  • Ensures best practices for secret management and browser session handling.

When to use it

  • When you need to migrate an existing browser-use Python script to a more stable TypeScript environment.
  • When you want to improve the reliability and speed of browser automation by reducing unnecessary LLM calls.
  • When you need to move agentic workflows onto the Browserbase platform for better observability.
  • When you are refactoring an opaque, flaky agent script into a maintainable, deterministic pipeline.

Advantages

  • Increases automation reliability by replacing non-deterministic agent loops with predictable primitives.
  • Reduces token costs and latency by using AI only where the page structure is unpredictable.
  • Improves maintainability through structured, inspectable TypeScript code.
  • Leverages Browserbase platform features for better session management and debugging.

Usage examples

“Migrate my browser-use script that searches for products on Amazon and extracts prices.”
The agent will inventory your script, identify the search and extraction steps, and provide a Stagehand v3 script using page.goto for navigation and stagehand.extract for price gathering.
“I have a flaky browser-use agent that logs into a portal. How do I move it to Stagehand?”
The agent will guide you through mapping the login flow to a deterministic Stagehand sequence, potentially using Browserbase context to handle authentication reliably.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/browserbase/browser-use-to-stagehand/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip browser-use-to-stagehand.zip -d .agents/skills

Documentation by Browserbase

browser-use → Stagehand on Browserbase (/browser-use-to-stagehand)

Convert a browser-use (Python) script into an idiomatic Stagehand v3 (TypeScript) script on Browserbase, choosing the right level of determinism at each step rather than producing a one-to-one agentic copy.

Core principle: browser-use is agentic-by-default (the LLM decides every action). Stagehand lets you choose how much AI to use. A good migration replaces opaque agent loops with an inspectable, mostly-deterministic pipeline — using AI only where the page is genuinely unpredictable. This is a refactor with judgment, not a transpile.

Source of truth & versions. This skill's durable value is the judgment — the determinism spectrum and the decompose-vs-agent decision — not the API specifics, which drift every release. The code mappings here are a snapshot validated against @browserbasehq/stagehand 3.6.x and browser-use 0.13.x (2026-06). On any conflict, the live docs win — always verify against the installed package and these sources before emitting code:

If the installed Stagehand major is not 3, treat this skill as conceptual only and follow the live docs for every signature.

Reference files (read as needed)

  • references/api-mapping.md — the mechanical browser-use → Stagehand mapping: variant detection, the full feature table, before/after code, Browserbase platform options, and v3 version gotchas. Read this for any non-trivial construct.

  • references/determinism.md — how to choose agent() vs act/extract/observe vs cached observe→act. The decision tree. Read this when deciding how to translate an Agent(task=…).

  • references/trace-assisted.md — the optional "run it on Browserbase, read the logs, then rewrite" workflow for opaque/flaky scripts.

  • references/guide.md — the human migration guide: philosophy shift, feature mapping, the determinism spectrum, and a recommended migration path.

  • references/prompt.md — a self-contained, tool-agnostic version of this skill; paste it into any AI assistant along with a browser-use script.

  • EXAMPLES.md — before/after script pairs.

Workflow

1. Get the source

Obtain the browser-use script(s). If the user only described a script, ask for the file(s). Note the target: TypeScript Stagehand on Browserbase unless they say otherwise.

First, gate on scope — is this even migratable? Not every browser-use file is an Agent(task=…) script. If the source is browser-use running as an MCP server (uvx browser-use --mcp, a mcpServers config) there is no Stagehand equivalent — flag it as out of scope, don't invent one (see api-mapping §3.7b). If the browser-use call is embedded in a larger app (a class/tool wrapper, web route, queue task), convert only the browser-use surface and preserve the surrounding app glue — see api-mapping §3.8.

2. Detect the browser-use variant

Identify legacy (pre-0.12) vs stable vs Rust beta (only when imports come from browser_use.beta) — see api-mapping §1. Note: the classic top-level from browser_use import Agent, ChatBrowserUse surface is alive and well in 0.13.x — ChatBrowserUse alone is not a beta tell; only a browser_use.beta import is. All variants translate identically, so when unsure, proceed with the stable mapping. Normalize legacy names before translating. State which variant you found.

3. Inventory the script

Extract a structured inventory before writing any TypeScript:

  • Task(s) — the task= string(s); split each into its implied ordered steps.

  • Model — the Chat* provider + model id.

  • Browser config — local vs cdp_url/Browserbase; headless; proxies; user_data_dir/storage_state.

  • Structured output — any output_model_schema Pydantic models.

  • Secrets — sensitive_data, env-var usage, login flows.

  • Guardrails — allowed_domains, max_steps.

  • Custom actions — @tools.action / Controller functions, and whether each is a deterministic side-effect or an agent capability.

  • Setup — initial_actions, secondary models (page_extraction_llm, planner_llm).

4. Decide the determinism level per step

For each step from the inventory, apply the decision tree in determinism.md:

  • Navigate to a known URL → page.goto(url) on the Stagehand page (no AI).

  • On-page action → act("…"); if it repeats, observe() once then replay act(action) (no LLM call).

  • Reading data → extract("…", zodSchema).

  • Genuinely open-ended → keep stagehand.agent().execute(...) (tightened with maxSteps/systemPrompt).

Default to decomposition when the flow is known; keep agent() only where it isn't. For a first lift-and-shift, a faithful agent() translation is acceptable — say so and note the optimization path.

5. Produce the Stagehand v3 rewrite

First, verify the API. Before writing, confirm the exact signatures you're about to use against the installed package (node_modules/@browserbasehq/stagehand types) or https://docs.stagehand.dev/v3. The mappings below are a 3.6.x snapshot; if anything differs in the installed version, the installed version wins. Then emit runnable TypeScript. Always:

  • import { Stagehand } from "@browserbasehq/stagehand"; and import { z } from "zod"; when extracting.

  • Get the page via const page = stagehand.context.pages()[0];.

  • Call AI methods on the instance: stagehand.act(...), stagehand.extract(...), stagehand.observe(...) — never page.act(...).

  • Set the model as a "provider/model" string.

  • Default to env: "BROWSERBASE"; show env: "LOCAL" as the dev option.

  • Pass secrets via variables and process.env, never hardcoded.

  • await stagehand.init() at the start, await stagehand.close() in a finally.

Include the project setup so it runs (see the templates below).

6. Write the migration summary

Alongside the code, produce a short summary:

  • Variant detected and the determinism choices made (which steps became deterministic vs AI vs agent), with the reasoning.

  • Needs human review — anything that didn't map 1:1: lost allowed_domains guardrails, custom-action logic, secondary-model intent, ambiguous task strings.

  • Recommended next step — Browserbase Context for auth reuse, caching for production, or the trace-assisted path if the flow was opaque.

7. Offer the trace-assisted path (only if warranted)

If the source was one large opaque agent(task=…), was flaky, or your rewrite can't be confidently mapped, offer the trace-assisted workflow (trace-assisted.md): run the original on Browserbase, pull sessions.logs.list, and rewrite from observed behavior. Don't run anything without the user's go-ahead.

Output templates

package.json

{
  "name": "stagehand-migration",
  "type": "module",
  "scripts": { "start": "tsx index.ts" },
  "dependencies": {
    "@browserbasehq/stagehand": "^3.0.0",
    "dotenv": "^16.0.0",
    "zod": "^3.25.0"
  },
  "devDependencies": { "tsx": "^4.0.0", "typescript": "^5.0.0" }
}

Add "ai": "^5.0.0" (Vercel AI SDK) only if a custom browser-use action maps to an agent tool. Pin v5, not v4 — Stagehand 3.6.x bundles ai v5 and types agent({ tools }) as the v5 ToolSet, where a tool's schema field is inputSchema. The v4 tool() helper emits parameters instead and will fail to type-check against Stagehand's v5 ToolSet. If you can't control the hoisted ai version, skip the tool() helper and pass a plain object { description, inputSchema: zodSchema, execute } — it satisfies the v5 ToolSet regardless of which ai major resolves.

.env

BROWSERBASE_API_KEY=...
BROWSERBASE_PROJECT_ID=...
ANTHROPIC_API_KEY=...   # or the provider matching your model string

index.ts skeleton (decomposed, the preferred shape)

import "dotenv/config";
import { Stagehand } from "@browserbasehq/stagehand";
import { z } from "zod";

async function main() {
  const stagehand = new Stagehand({
    env: "BROWSERBASE",
    model: "anthropic/claude-sonnet-4-6",
  });
  await stagehand.init();
  try {
    const page = stagehand.context.pages()[0];

    await page.goto("https://example.com");          // deterministic skeleton
    await stagehand.act("…");                          // AI where the page varies
    const data = await stagehand.extract("…", z.object({ /* … */ }));  // structured reads

    console.log(data);
  } finally {
    await stagehand.close();
  }
}

main().catch((err) => { console.error(err); process.exit(1); });

Validation checklist (before declaring done)

  • [ ] AI methods are on the instance (stagehand.act/extract/observe), not the page.

  • [ ] Page obtained via stagehand.context.pages()[0].

  • [ ] Model is a "provider/model" string; the matching provider key is in .env.

  • [ ] extract uses a zod schema; zod is in dependencies.

  • [ ] Secrets use variables + process.env; nothing hardcoded.

  • [ ] init() / close() present; close() in finally.

  • [ ] Each browser-use step is accounted for, placed deliberately on the determinism spectrum.

  • [ ] Migration summary lists determinism choices and "needs human review" items.

Common mistakes to avoid

  • Copying v2 syntax (page.act(), stagehand.page, modelName/modelClientOptions, enableCaching) from old blog posts. Use v3 — see api-mapping "Version notes".

  • Translating every step into act() — navigate with page.goto and cache repeatable steps via observe→act; don't spend an LLM call on every action.

  • Defaulting everything to agent() — that just reproduces browser-use's non-determinism in a new framework. Decompose where the flow is known.

  • Silently dropping allowed_domains — Stagehand has no domain firewall; flag it for review.

  • Inventing Browserbase/Stagehand options — if unsure of a field, check https://docs.stagehand.dev/v3 / https://docs.browserbase.com rather than guessing.

Files

references/trace-assisted.md

Trace-assisted migration (optional, advanced)

A static read of a browser-use script tells you what it was asked to do. Running it once on Browserbase tells you what it actually did — the real URLs, network calls, and page transitions. For opaque or flaky scripts, that observed behavior makes the Stagehand rewrite far more accurate.

This is the optional path. Skip it for simple scripts; reach for it when the source is a large agent(task="…") blob whose actual flow is unclear, or when a migration's first rewrite doesn't reproduce the original behavior.

Sibling skill: this repo's browser-trace productizes CDP trace capture — the full DevTools firehose, screenshots, and DOM dumps, bisected into per-page searchable buckets, and able to attach to a live Browserbase session. Use it to capture the browser-use run, then feed the per-page summaries into the rewrite. The Session Logs API below is the lighter-weight alternative when you just need navigations + network calls.


Important reframe: what the "trace" actually is

The original idea was "attach a browser-trace as a CDP listener." On Browserbase, the machine-readable trace is the Session Logs API, not the session recording:

  • Session Logs API — bb.sessions.logs.list(sessionId) returns CDP events: network activity, console logs, and page lifecycle (navigations). This is the structured trace you parse to reconstruct the flow.

  • Session Recording / Replay — now H.264 video (HLS segments), not an rrweb/DOM event stream. Great for human QA ("did it do the right thing?"), not for programmatic diffing.

So: logs to drive the rewrite, video to eyeball it. Don't promise a DOM-event stream from the recording — it isn't that anymore.


The workflow

Step 1 — Run the existing browser-use script on Browserbase, unmodified

browser-use connects to any remote browser via cdp_url, and Browserbase is officially supported. Point the existing script at a Browserbase session; record it and tag it for later retrieval.

import os
from browserbase import Browserbase
from browser_use import Agent, Browser, BrowserProfile, ChatAnthropic

bb = Browserbase(api_key=os.environ["BROWSERBASE_API_KEY"])
session = bb.sessions.create(
    project_id=os.environ["BROWSERBASE_PROJECT_ID"],
    browser_settings={"record_session": True},      # keep recording on (default)
    user_metadata={"framework": "browser-use", "migration": "true"},
)
print(f"Session: https://www.browserbase.com/sessions/{session.id}")

# The ONLY change to the original script: hand it the Browserbase CDP endpoint
browser = Browser(browser_profile=BrowserProfile(cdp_url=session.connect_url))

agent = Agent(task="<the original task, unchanged>", llm=ChatAnthropic(model="claude-sonnet-4-6"), browser=browser)
await agent.run()
await browser.stop()

Notes:

  • You must connect promptly — a new session terminates if nothing connects within ~5 minutes.

  • Configure proxies/stealth/region on the Browserbase session, not on browser-use.

  • Keep session.id — it's how you pull logs and the recording next.

Step 2 — Pull the trace after the run
logs = bb.sessions.logs.list(session.id)        # CDP network / console / lifecycle events
recording = bb.sessions.recording.retrieve(session.id)   # video (for human QA)

TypeScript equivalent with @browserbasehq/sdk:

const logs = await bb.sessions.logs.list(sessionId);

From the logs, extract the spine of the flow:

  • Navigations (page lifecycle events) → the page.goto(...) calls in the rewrite, and the URLs to anchor each phase.

  • Network calls → which requests actually mattered (and whether some data could be read from an API response instead of scraped — sometimes a cleaner rewrite).

  • Console errors → fragile spots to handle explicitly.

You can also open the Session Inspector in the dashboard for an Events/Pages timeline and, if the run used Stagehand, act/extract results and token usage.

Step 3 — Author the Stagehand rewrite from observed behavior

Map what you observed onto the determinism spectrum (see determinism.md):

  • Observed fixed navigations → deterministic page.goto(...).

  • Observed interactions on varying markup → act("…"), or observe()→act() for repeatable steps.

  • Observed data reads → extract("…", schema).

  • Reuse the same browserbaseSessionCreateParams (region/proxies/context) so behavior matches the baseline run.

Step 4 — Validate against the baseline

Run the Stagehand rewrite under env: "BROWSERBASE" and compare its logs/recording to the browser-use baseline: same navigations, same end state, same extracted data. Reuse the same Context so auth carries over and you're comparing like with like.


When to use this vs. skip it

Use trace-assistedSkip (static rewrite is enough)
One giant agent(task="…") whose real flow is unclearScript already reads as clear, ordered steps
Script is flaky / behavior varies run to runDeterministic, well-understood script
First static rewrite doesn't reproduce the originalSimple task / extraction
Auth, redirects, or heavy network make the path opaqueNo login, single domain

Caveats

  • The recording is video, not DOM events — use the Logs API for anything programmatic.

  • Logs are retrieved after the run completes.

  • A live CDP listener attaches on your side of the connection and suits JS/TS automation; for a Python browser-use run, prefer the post-run Logs API (or the browser-trace skill) over wiring up live listeners.

  • Running the script incurs real LLM + browser cost — it's a deliberate, opt-in step.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Needs an MCP server, Needs an API key

The author says: The skill itself uses only Read/Write/Edit/Grep/Bash — no install step. The Stagehand code it generates needs Node 18+, `@browserbasehq/stagehand` (v3) and `zod`, plus `BROWSERBASE_API_KEY` / `BROWSERBASE_PROJECT_ID` and a model-provider key (e.g. `ANTHROPIC_API_KEY`) to run. The optional trace-assisted path uses the Browserbase SDK or the sibling `browser-trace` skill.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Browserbase
Publisher
Browserbase (Official)
Source
browserbase/skills · skills/browser-use-to-stagehand · commit 6811ca3
Licence
MIT License (redistribution allowed)
  • ATTRIBUTION.md (written by AutoGineer)
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