Reverse-engineer a website's internal API by recording browser traffic into a HAR file, then generate a standalone client or CLI that calls the endpoints directly, with no browser needed after the first recording. Use when asked to "derive a client", "build a CLI for <site>", "reverse engineer this site's API", "record network requests", "turn this site into an API", or when the same site will be automated repeatedly and direct HTTP calls would beat driving the browser every time.
npx skills add https://github.com/vercel-labs/agent-browser --skill derive-client
Driving a browser is the right tool for the first visit and the wrong tool for the hundredth. This skill records a site's network traffic once while you use it, then turns the captured requests into a standalone client (script, CLI, or library) that talks to the site's internal API directly.
The recording alone contains everything needed: agent-browser embeds text response bodies (JSON/HTML/JS) in the HAR by default, so endpoint shapes can be studied offline after the browser is closed.
1. Record Start HAR capture, drive the flows you want in the client
2. Identify Find the real API endpoints among the noise
3. Extract Pull request shapes, response schemas, and auth material
4. Generate Write the client, one function per flow
5. Verify Call every endpoint for real before declaring done
agent-browser network har start # embeds text response bodies by default
# ... drive the site: search, open a detail page, paginate, etc. ...
agent-browser network har stop /tmp/site.har
--content all embeds binary bodies too (base64); --content none disables embedding. Per-body cap is 2 MB.While the session is still open, agent-browser network requests and network request <id> give the same data interactively — but only the HAR survives navigation and browser close, so prefer it for anything multi-page.
Query the HAR with jq:
# All JSON API calls: method, URL, status
jq -r '.log.entries[]
| select(.response.content.mimeType | test("json"))
| "\(.request.method) \(.response.status) \(.request.url)"' /tmp/site.har
Ignore analytics and infrastructure noise: telemetry endpoints (/collect, /track, /beacon, /log), third-party domains (google-analytics, segment, sentry, datadog, intercom, hotjar), and static assets. The real API is usually first-party, JSON, and correlates with the actions you performed.
# Full detail for one endpoint: request headers, POST body, response body
jq '.log.entries[] | select(.request.url | test("api/search"))
| {request: {method: .request.method, headers: .request.headers,
postData: .request.postData.text},
response: .response.content.text}' /tmp/site.har
.response.content.text — this is the real payload, use it to derive types.authorization, cookie, x-csrf-token, x-api-key, and site-specific x-* headers. Replay only the ones that matter — test by omission in step 5.agent-browser cookies get --json > cookies.json for the client to load at runtime. Never hardcode cookie values into generated source.search(query), getItem(id)), typed from the observed response bodies.user-agent, referer, or x-requested-with.Call every generated function against the live API and compare the response shape with the recording. Common failures:
| Symptom | Cause | Fix |
|---------|-------|-----|
| 401/403 | Expired or missing session | Re-login via agent-browser, re-export cookies |
| 403/419 on writes | CSRF token is per-session or per-form | Fetch the token endpoint first, or keep that flow browser-driven |
| Works then breaks | Signed/expiring request params | Fall back to the browser for that step; derive the rest |
| Different shape than HAR | A/B tests or geo-dependent responses | Re-record and treat the union as optional fields |
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Vendor-agnostic lab automation framework. Use when controlling multiple equipment types (Hamilton, Tecan, Opentrons, plate readers, pumps) or needing unified programming across different vendors. Best for complex workflows, multi-vendor setups, simulation. For Opentrons-only protocols with official API, opentrons-integration may be simpler.
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
Take vercel-labs/derive-client from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.