Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/lftpadilla/agent-dev-kit/stagehandnpx skills add LFTPadilla/agent-dev-kit --skill stagehandgit clone --depth 1 https://github.com/LFTPadilla/agent-dev-kitWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00066 | $0.00513 |
| Opus 5 | $0.00033 | $0.00257 |
| Sonnet 5 | $0.00013 | $0.00103 |
| Haiku 4.5 | $0.00007 | $0.00051 |
Grade A, and why
stagehand scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
stagehand — self-healing NL automation on Playwright
Stagehand (Browserbase) is a TypeScript SDK over Playwright with three primitives. Natural-language steps resolve at runtime, so they survive markup changes that would break a hardcoded selector — the "self-healing" the volatile parts of a suite need.
page.act("click the Connect GitHub button")— perform an action.page.observe("the primary CTA")— find an element / preview an action.page.extract({ schema })— pull structured data from the page.
You still drop to raw Playwright for the deterministic 80%; Stagehand is for the
20% that keeps shifting. It's the same page, so they mix in one test.
When to use vs not
- Use on flows whose DOM/labels churn, or where specs break every release on selectors.
- Don't use for stable, hot-path regression — plain Playwright (
getByRole+ web-first assertions) is faster, free, and fully deterministic. NL steps cost an LLM call each.
Pilot (recommended first step)
npm i @browserbasehq/stagehand
import { Stagehand } from '@browserbasehq/stagehand'
const sh = new Stagehand({ env: 'LOCAL' }) // LOCAL = your machine; BROWSERBASE = cloud
await sh.init()
const page = sh.page // a Playwright Page, augmented
await page.goto(process.env.APP_URL!)
await page.act('open the onboarding wizard')
const { steps } = await page.extract({
instruction: 'list the visible wizard step titles',
schema: { type: 'object', properties: { steps: { type: 'array', items: { type: 'string' } } } },
})
await sh.close()
Run it against ONE flaky flow, compare maintenance cost vs the plain-Playwright version over a few releases, then decide whether to expand. Needs an LLM API key (set per its docs) — keep it in env, never commit.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 49 lines · 66 tokens per session scan A 512d9f392242
stagehand is a skill published in the GitHub repository LFTPadilla/agent-dev-kit (2 stars, last pushed 4d ago), licensed MIT. It adds 66 tokens to every session and 513 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…