agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites,…
Run requested dogfooding through public product interfaces. Use existing QA journeys or qa-report to plan them; excludes routine code edits and CI-only verification.
$ npx -y skills add pedronauck/skills --skill qa-execution --agent claude-codeHow it fires
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/qa-executionContext preview
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Run requested dogfooding through public product interfaces. Use existing QA journeys or qa-report to plan them; excludes routine code edits and CI-only verification.
name: qa-execution description: "Run requested dogfooding through public product interfaces. Use existing QA journeys or qa-report to plan them; excludes routine code edits and CI-only verification." disable-model-invocation: true argument-hint: "[qa-docs-path]" metadata: author: Pedro Nauck github: https://github.com/pedronauck repository: https://github.com/pedronauck/skills
QA the product the way a real person meets it: a **persona** walks a journey through the product's public interfaces, feels the friction, hits the edges, and reports what happened. This is **dogfooding**, not a scripted test pass — the session is the work, and the living QA docs tree remembers it.
Three non-negotiables hold every session:
1. **In persona.** Every interaction and every verification goes through a surface a real user can reach — no dev-tools shortcut, no code-reading to decide what should happen, no patching over a stall. 2. **Proof, not optimism.** A `Pass` is the expected observable seen, confirmed through an independent read path, surviving a refresh, with evidence captured. Optimistic UI is not confirmation. 3. **Write back or it didn't happen.** Every session updates the tree — scenario-file verdicts, bug registry, and the dated report carrying the session debrief.
Choose the planned smoke/targeted/full scope. Read only the relevant procedure/schema sections and reuse current evidence for unchanged behavior. A small changed journey does not require all tours, edge categories, or a second full walk.
**Step 1 — Resolve the tree, scope, and preconditions**
**Step 2 — Build the matrix and create the report now**
**Step 3 — Walk each journey in persona**
**Step 4 — Run each tour and edge probe**
**Step 5 — Experiential lens pass**
**Step 6 — File findings into the registry**
A curated collection of 87 agent skills for Claude Code and compatible AI coding assistants — 40 original (⭐️), 34 hand-picked (💎), and 13 marketing & business (📣).
Repo: pedronauck/skills
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