mattpocock-qa
Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues.
Skill by hedysom
Chalk Labs
Need help deploying mattpocock-qa?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/hedysom-mattpocock-qa
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: documents, testing, agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/mattpocock-qa
What's inside
- Skill name
mattpocock-qa- Description
- Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
- License
- MIT
- Instructions
- 127 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# QA Session Run an interactive QA session. The user describes problems they're encountering. You clarify, explore the codebase for context, and file GitHub issues that are durable, user-focused, and use the project's domain language. ## For each issue the user raises ### 1. Listen and lightly clarify Let the user describe the problem in their own words. Ask **at most 2-3 short clarifying questions** focused on: - What they expected vs what actually happened - Steps to reproduce (if not obvious) - Whether it's consistent or intermittent Do NOT over-interview. If the description is clear enough to file, move on. ### 2. Explore the codebase in the background While talking to the user, kick off an Agent (subagent_type=Explore) in the background to understand the relevant area. The goal is NOT to find a fix — it's to: - Learn the domain language used in that area (check UBIQUITOUS_LANGUAGE.md) - Understand what the feature is supposed to do - Identify the user-facing behavior boundary This context helps you write a better issue — but the issue itself should NOT reference specific files, line numbers, or internal implementation details. ### 3. Assess scope: single issue or breakdown? Before filing, decide whether this is a **single issue** or needs to be **broken down** into multiple issues. Break down when: - The fix spans multiple independent areas (e.g. "the form validation is wrong AND the success message is missing AND the redirect is broken") - There are clearly separable concerns that different people could work on in parallel - The user describes something that has multiple distinct failure modes or symptoms Keep as a single issue when: - It's one behavior that's wrong in one place - The symptoms are all caused by the same root behavior ### 4. File the GitHub issue(s) Create issues with `gh issue create`. Do NOT ask the user to review first — just file and share URLs. Issues must be **durable** — they should still make sense after major refactors. Write from the user's perspective. #### For a single issue Use this template: ``` ## What happened [Describe the actual behavior the user experienced, in plain language] ## What I expected [Describe the expected behavior] ## Steps to reproduce 1. [Concrete, numbered steps a developer can follow] 2. [Use domain terms from the codebase, not internal module names] 3. [Include relevant inputs, flags, or configuration] ## Additional context [Any extra observations from the user or from codebase exploration that help frame the issue — e.g. "this only happens when using the Docker layer, not the filesystem layer" — use domain language but don't cite files] ``` #### For a breakdown (multiple issues) Create issues in dependency order (blockers first) so you can reference real issue numbers. Use this template for each sub-issue: ``` ## Parent issue #<parent-issue-number> (if you created a tracking issue) or "Reported during QA session" ## What's wrong [Describe this specific behavior problem — just this slice, not the whole report] ## What I expected [Expected behavior for this specific slice] ## Steps to reproduce 1. [Steps specific to THIS issue] ## Blocked by - #<issue-number> (if this issue can't be fixed until another is resolved) Or "None — can start immediately" if no blockers. ## Additional context [Any extra observations relevant to this slice] ``` When creating a breakdown: - **Prefer many thin issues over few thick ones** — each should be independently fixable and verifiable - **Mark blocking relationships honestly** — if issue B genuinely can't be tested until issue A is fixed, say so. If they're independent, mark both as "None — can start immediately" - **Create issues in dependency order** so you can reference real issue numbers in "Blocked by" - **Maximize parallelism** — the goal is that multiple people (or agents) can grab different issues simultaneously #### Rules for all issue bodies - **No file paths or line numbers** — these go stale - **Use the project's domain language** (check UBIQUITOUS_LANGUAGE.md if it exists) - **Describe behaviors, not code** — "the sync service fails to apply the patch" not "applyPatch() throws on line 42" - **Reproduction steps are mandatory** — if you can't determine them, ask the user - **Keep it concise** — a developer should be able to read the issue in 30 seconds
From hedysom/pi-mattpocock-skills, MIT.
More from hedysom/pi-mattpocock-skills
- 0.474score
mattpocock-setup-pre-commit
hedysom
Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo.
SkillCFreshness: CClaude Code +9 - 0.474score
mattpocock-obsidian-vault
hedysom
Search, create, and manage notes in the Obsidian vault with wikilinks and index notes.
SkillCFreshness: CClaude Code +9 - 0.474score
mattpocock-scaffold-exercises
hedysom
Create exercise directory structures with sections, problems, solutions, and explainers that pass linting.
SkillCFreshness: CClaude Code +9 - 0.455score
mattpocock-diagnose
hedysom
Disciplined diagnosis loop for hard bugs and performance regressions.
SkillCFreshness: CClaude Code +9 - 0.455score
mattpocock-git-guardrails-claude-code
hedysom
Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute.
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-setup-matt-pocock-skills
hedysom
Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local…
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-caveman
hedysom
Ultra-compressed communication mode.
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-grill-with-docs
hedysom
Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as…
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-improve-codebase-architecture
hedysom
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/.
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-migrate-to-shoehorn
hedysom
Migrate test files from `as` type assertions to @total-typescript/shoehorn.
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-request-refactor-plan
hedysom
Create a detailed refactor plan with tiny commits via user interview, then file it as a GitHub issue.
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-ubiquitous-language
hedysom
Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms.
SkillCFreshness: CClaude Code +9
Signals
- Stars
- 0
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Apr 28, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/hedysom/pi-mattpocock-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from hedysom
- 0.474score
mattpocock-setup-pre-commit
hedysom
Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo.
SkillCFreshness: CClaude Code +9 - 0.474score
mattpocock-obsidian-vault
hedysom
Search, create, and manage notes in the Obsidian vault with wikilinks and index notes.
SkillCFreshness: CClaude Code +9 - 0.474score
mattpocock-scaffold-exercises
hedysom
Create exercise directory structures with sections, problems, solutions, and explainers that pass linting.
SkillCFreshness: CClaude Code +9 - 0.455score
mattpocock-git-guardrails-claude-code
hedysom
Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute.
SkillCFreshness: CClaude Code +9 - 0.455score
mattpocock-diagnose
hedysom
Disciplined diagnosis loop for hard bugs and performance regressions.
SkillCFreshness: CClaude Code +9 - 0.450score
mattpocock-improve-codebase-architecture
hedysom
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/.
SkillCFreshness: CClaude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get mattpocock-qa running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
mattpocock-qa skill. Agent Mart. https://agentmart.dev/skills/hedysom-mattpocock-qa (last updated 2026-10-24)