verifier-setup — scaffold this repo's /verify skill

SkillWeb & browsing

Prepares a repository so engineering work can be proven to actually work before it ships. Once added, your AI investigates the repo, ensures a one-command development stack (dev-local) is in place, and gets verification ready to run either locally or in a sandbox.

Available today. Use it from your connected AI after setup.

After adding it, let it investigate your repository. It will set up the dev stack and ask whether you want verification to run locally or in a sandbox.

Then ask your AI: use the verifier-setup — scaffold this repo's /verify skill skill

What your AI can do with it

  • Investigate a repository to understand how it is set up
  • Ensure a one-command development stack (dev-local) exists
  • Ask whether verification should run locally or in a sandbox (crabbox)
  • Confirm or install the driver needed for verification, defaulting to the playwright-cli skill for web work

What this skill tells your AI

The instructions your AI receives, as published by ai-builder-club/skills in skills/verifier-setup/SKILL.md and read by ahel’s review.

Goal: leave the repo able to prove an engineering task works before it ships — run once, and it wires up everything the per-task /verify loop needs.

You are setting up — not verifying anything yourself right now. The /verify template lives at assets/verify.template.md (next to this skill). Parallels dev-local-setup (which generates a script + its skill doc): a setup skill that leaves behind reusable, repo-specific artifacts.

What this produces (the outputs)

Running verifier-setup end-to-end leaves the repo with:

  1. A /verify skill.claude/skills/verify/SKILL.md, the repo-tailored per-task verification SOP (spawn a verifier sub-agent → drive the app → screenshot/video proof → open a PR with the proof embedded). Generated in Step 5.
  2. A /dev-local skill + its scriptscripts/dev-local.sh and .claude/skills/dev-local/SKILL.md, via dev-local-setup (Step 2) if not already present. The one-command stack /verify depends on.
  3. The driver skill installed — the playwright-cli skill for web apps (Step 2); for non-web, the concrete exercise tool confirmed present.

Step 0 — Inventory what already exists (check before you add ANYTHING)

Before creating anything, take stock — the repo may already have some of this, under whatever name or layout its team chose. Look for the capability, not a specific filename; the paths below are only examples. For each, decide reuse as-is / adapt-extend / create fresh — never blindly overwrite working setup:

  • A way to start the app — a one-command dev launcher, a Makefile/Procfile target, docker-compose, package scripts (e.g. scripts/dev-local.sh, but any form counts).
  • A prior verification SOP/skill — from an earlier run of this skill or the team's own convention.
  • A driver for the app's interface — a browser automation tool already available (e.g. the playwright-cli skill), or the relevant API/CLI client.
  • An existing test/e2e suite or checks — however organized.
  • Sandbox/cloud-box config — anything giving isolated per-agent stacks.
  • An evidence/artifact convention — where proof lands and how a reviewable link gets published (a release, bucket, CI artifacts, etc.).

Every later step is conditional on this inventory: if a capability exists and works, reuse and adapt it (fill gaps, don't regenerate); only create what's missing.

Step 1 — Investigate the repo (don't guess)

Discover the real facts the generated skill will hardcode:

  1. How the app is exercised — is it a web app (has a browser UI + a dev server on a port), an API/service (HTTP endpoints, no UI), a CLI, or a desktop/mobile app? This picks the driver.
  2. Stack launcher — is there already a way to start the app (any form — see Step 0)? Note the up-command and the app URL/port. If none, Step 2 handles it.
  3. Auth — is the primary flow login-gated? Is there a session/auth helper the verifier can mint a session with (see e2e-setup)? Record it, or "n/a".
  4. Regression checks — the repo's fast codified checks (type-check, lint, unit, existing e2e commands) from package.json/Makefile/turbo.json/etc.
  5. Proof upload — how a reviewable video URL is produced (a pr-evidence GitHub prerelease via gh release upload is the default; a bucket/CI artifact works too).

Step 2 — Ensure the prerequisites exist (reuse-or-provide, per the Step 0 inventory)

For each, act on what Step 0 found — reuse if present, adapt if partial, create only if missing. Each check is idempotent; a no-op on what's already there:

  • Dev stack. If any working way to start the app already exists (a launcher script, Make/Procfile target, compose, package scripts), reuse it — read it for the up-command/port/services and move on (extend only if a needed service is missing). If there's none, scaffold one via dev-local-setup (don't hand-roll a launcher here). The generated /verify just needs a reliable one-command up.
  • Driver skill.
    • Web → install/confirm the playwright-cli skill (it documents + wraps the browser driver). Ensure its binary is callable too (npx --yes @playwright/cli --version; install it + the chrome channel if missing). This closes the usual local gap where the browser driver was assumed but never installed.
    • Non-web → confirm the concrete exercise tool exists (an HTTP client for an API, the built binary for a CLI). No browser skill needed.
  • Evidence dir. Ensure evidence/ is gitignored (proof output lands there).

Step 3 — Ask the user: local or sandbox?

Present the choice (default and recommend local — it's simpler to stand up):

  • Local — one dev stack on the machine (scripts/dev-local.sh up). Best for a single task at a time. Recommend this unless they need parallelism.
  • Sandbox (crabbox) — an isolated cloud box per agent, for concurrent loops or a fixed-port/single-instance stack. If chosen and not yet set up, scaffold via crabbox-setup; the generated skill drives the app in-box via cbx.sh pw.

Record the pick as the generated skill's default RUN_MODE (the other stays a documented fallback).

Step 4 — Confirm the driver

State the detected driver and confirm with the user (default playwright-cli for web apps). For non-web, name the concrete tool (e.g. curl/an HTTP script, the built CLI). This becomes DRIVER in the generated skill.

Step 5 — Generate .claude/skills/verify/SKILL.md

If a prior verification skill/SOP already exists (Step 0), update it in place — refresh the repo-specifics/placeholders, preserve any hand-edits the team added; don't clobber. Otherwise copy assets/verify.template.md → the repo's skills dir (.claude/skills/verify/ or the repo's convention) and fill every {{...}} placeholder from Steps 1–4: STACK_UP, APP_URL, RUN_MODE(+RUN_MODE_NOTE), DRIVER(+DRIVER_INSTRUCTION), AUTH_HELPER(+AUTH_INSTRUCTION), EXERCISE, REGRESSION_CMDS, EVIDENCE_UPLOAD, DATE. Delete branches that don't apply (e.g. drop the browser/video language for a non-web repo). Keep it to one screen — it's an SOP the agent follows, not an essay.

Step 6 — Hand off

Commit the generated skill (+ any .gitignore/dev-local changes). Tell the user:

  • how to run it — "/verify before opening a PR (or when asked to verify), on a branch with changes committed";
  • the run mode chosen and how to switch;
  • any prerequisite they must install/start once (e.g. Docker for infra, gh auth for evidence upload).

Principles

  • Check before you create; adapt, never clobber. Every artifact — dev-local, the driver skill, e2e, evidence gitignore, the verify skill itself — is inventoried first (Step 0) and reused/extended when it already exists. Only create what's genuinely missing; preserve working setup and team hand-edits.
  • Discover, don't assume. Stack command, port, auth, and checks come from the repo — the generated skill hardcodes real facts, not conventions.
  • Provision before you generate. The driver, launcher, and evidence/ exist before the /verify skill ships, so it never fails on a missing tool.
  • Right-sized. A web monorepo gets the full browser+video SOP; a CLI tool gets a stdout-assertion SOP. Match the template to the repo; cut what doesn't apply.
  • The output is a skill, not a run. verifier-setup scaffolds; /verify runs.

Signals

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Jul 2026
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skill
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verifier-setup
Source
github.com/ai-builder-club/skills