Agent skill

QA Review

by PackmindHub in PackmindHub/packmind

Review a user story implementation against its Example Mapping (EM) specification.

Apache-2.0Auto-check passedProduct & Project Management

Install QA Review

skills CLI
$ npx skills add PackmindHub/packmind --skill qa-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install PackmindHub/packmind qa-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/PackmindHub/packmind.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/qa-review .claude/skills/qa-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qa-review
GitHub stars
317
Token cost
~1.9k tokens
SKILL.md length
791 words
Files
5
Skills in repo
35
Repo updated
First seen
Licence
Apache-2.0

At a glance

Review a user story implementation against its Example Mapping (EM) specification.

  • Works in 7 steps: Parse the EM Spec → Select Target Domains → Validate Implementation Exists → …
  • Tasks that involve User stories
  • SKILL.md covers Reference, 1. Parse the EM Spec, 2. Select Target Domains and 3. Validate Implementation…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

QA Review is an agent skill from PackmindHub/packmind. Review a user story implementation against its Example Mapping (EM) specification.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `agents/code-map-agent.md`, `agents/code-review-agent.md` and `agents/functional-coverage-agent.md`).

It sits in Product & Project Management, covering User stories. The repository describes itself as: Packmind seamlessly captures your engineering playbook and turns it into AI context, guardrails, and governance. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve User stories

Example prompts

  • “/qa-review”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Parse the EM Spec
  2. Select Target Domains
  3. Validate Implementation Exists
  4. Build Code Map
  5. Pre-filter Packmind Standards
  6. Launch Parallel Sub-Agents
  7. Combine & Write Report

What it can do on your machine

Read from SKILL.md and the folder at commit 8a10541. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

QA Review loads about 1.9k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 791 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from PackmindHub/packmind at commit 8a10541, republished under its Apache-2.0 licence (© PackmindHub). 791 words, ~1,933 tokens.

Download SKILL.mdSave it as .claude/skills/qa-review/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
qa-review
description
Review a user story implementation against its Example Mapping (EM) specification.

QA Review

Audit a user story implementation against its Example Mapping specification. Reads the EM markdown, finds all implementing code in the codebase, then runs two parallel agents — one for functional coverage, one for code review. Produces a single compact report.

This skill only detects issues — it does not fix them.

Reference

A ready-to-fill EM template is available at em_template.md (in this skill's directory). Share it with the user when they need to write a new spec from scratch.

1. Parse the EM Spec

Read the markdown file at the provided path. Extract a structured summary with these sections:

What to extract
  1. User Story title — the first line or heading describing the US
  2. Rules — each # Rule N: <title> block. For each rule, extract:
    • Rule number and title
    • Each ## Example N with its setup/action/outcome narrative (preserve the full text)
  3. Technical Rules — bullet points under a # Technical rules heading (implementation-focused constraints)
  4. User Events — content under # User Events heading: event names, properties, schemas
  5. Check Also items — bullet points after "Check also" markers (additional rules/constraints, often separated by dashes)
  6. Code References — all backtick-quoted terms across the entire spec (class names, field names, event names like ConflictDetector, space_created, decision)
  7. Domain Keywords — key nouns and verbs from rule titles and examples (e.g., "space", "create", "slug", "rename", "conflict")
Handling ambiguity

If a spec item is ambiguous or explicitly deferred (e.g., "TBD", "on verra plus tard", "later"), flag it in the Parsed Spec Summary but exclude it from coverage assessment. Note it in the report as "Deferred — not assessed."

Compile everything into a Parsed Spec Summary formatted as below. The "Full Examples" section preserves the complete raw text of every example — sub-agents need this full context to accurately assess coverage.

## Parsed Spec Summary

### User Story
{title}

### Rules and Examples
Rule 1: {title}
  Example 1: {one-line summary of scenario}
  Example 2: {one-line summary of scenario}
Rule 2: {title}
  Example 1: {one-line summary of scenario}
[...]

### Full Examples (raw text)
{Copy the complete text of every example verbatim from the spec, preserving setup/action/outcome narratives. Do not summarize here — this section is passed to sub-agents so they can assess nuanced behaviors.}

### Technical Rules
- {rule text}
[...]

### Deferred Items
- {item text} — Deferred, not assessed
[...]

### User Events
- {event_name}: {properties}
[...]

### Check Also
- {constraint text}
[...]

### Code References (from backticks)
{list of all backtick-quoted terms}

### Domain Keywords
{list of distinctive nouns/verbs extracted from rules}

2. Select Target Domains

Ask the user which domains this user story touches. Use AskUserQuestion with multiSelect: true:

OptionDirectories
CLI (apps/cli)apps/cli/src/**
API (apps/api)apps/api/src/**
Packages (packages/*)packages/*/src/**, packages/types/src/**
Frontend (apps/frontend)apps/frontend/app/**, apps/frontend/src/**

Packages is always included, even if the user does not select it — it contains domain logic, contracts, events, and infra that all other layers depend on.

Store the user's selection as {target_domains} — a list of domain labels and their directory patterns. All subsequent steps use this to scope their searches.

3. Validate Implementation Exists

Grep 2–3 of the most distinctive backtick-quoted terms from the spec, scoped to the {target_domains} directories only. If fewer than 3 implementing files are found, stop and ask the user to confirm that the US has been fully implemented. Do not proceed with a full review on a partially-implemented or not-yet-started US — the report would be misleading.

4. Build Code Map

Launch a Code Map Agent (subagent_type: general-purpose) using the prompt from agents/code-map-agent.md. Replace:

  • {parsed_spec_summary} with the Parsed Spec Summary from step 1
  • {target_domains} with the selected domains and their directory patterns from step 2

The agent will search only within the target domain directories, then return a structured Code Map organized by architectural layer. Only layers matching the selected domains will appear in the output.

Wait for the agent to complete before proceeding to step 5.

Show full SKILL.md (277 more words)Show less

5. Pre-filter Packmind Standards

Before launching the review agents, collect the applicable Packmind coding standards:

  1. Glob for **/.claude/rules/packmind/*.md across the repository
  2. Read the YAML frontmatter of each file to extract its paths glob patterns
  3. Match the Code Map file paths against each standard's paths patterns
  4. For each standard that matches at least one Code Map file, read its full content

Compile the applicable standards into {applicable_standards} — the full text of each matching standard, prefixed with its name. If no standards match, set {applicable_standards} to "None".

6. Launch Parallel Sub-Agents

Launch two sub-agents in parallel (same turn), each receiving the Parsed Spec Summary (including the Full Examples section with raw text), Code Map, and target domains as context:

  1. Functional Coverage Agent (subagent_type: general-purpose) — prompt built from agents/functional-coverage-agent.md. Replace {parsed_spec_summary}, {code_map}, and {target_domains}.
  2. Code Review Agent (subagent_type: general-purpose) — prompt built from agents/code-review-agent.md. Replace {parsed_spec_summary}, {code_map}, {target_domains}, and {applicable_standards}.

Launch both agents simultaneously. The full raw example text is critical — sub-agents need the complete setup/action/outcome narratives to assess nuanced behaviors, not just one-line summaries.

Sequential Fallback

If the Agent tool is unavailable, perform both reviews sequentially yourself, following the instructions from each agent prompt file.

7. Combine & Write Report

Once both agents complete, merge their outputs into a single report.

Output path

Derive from the input path: if input is path/to/my-spec.md, output is path/to/my-spec-report.md.

Report template
markdown
# QA Review Report

**Spec**: {filename} | **Date**: {date} | **Branch**: {branch} | **Commit**: {short-sha}
**Rules**: {N} | **Examples**: {N} | **Tech Rules**: {N} | **Events**: {N}

## Summary

| Metric | Count |
|--------|-------|
| Covered | N |
| Partially Covered | N |
| Not Covered | N |
| Code Findings | N (Critical: X, High: Y, Medium: Z) |
| Standards Violations | N |

## Functional Coverage

### Coverage Matrix

{coverage matrix table from functional coverage agent}

### Gaps

{reproduction steps from functional coverage agent — omit this subsection if all items are Covered}

## Code Review

### Findings

{findings from code review agent — omit this section if no issues found}

## Deferred Items

{list of items marked as deferred/TBD in the spec — not assessed in this review}

---
*Static analysis only. No code was executed during this review.*

Omit any section that has zero content. Only include sections with actual results.

Print Summary

After writing the report, print a brief summary to the console:

  • Total rules/examples in the spec
  • Coverage stats (Covered / Partially / Not Covered counts)
  • Code review findings count by severity
  • The report file path

© PackmindHub, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in .agents/skills/qa-review of PackmindHub/packmind.

  • SKILL.md
  • agents/code-map-agent.md
  • agents/code-review-agent.md
  • agents/functional-coverage-agent.md
  • em_template.md

Open the folder on GitHubat commit 8a10541

Compare with similar skills

QA Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

QA Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
QA Review this skillPackmindHub/packmind317—~1.9kAutomated safety check: PassApache-2.0
User Story Writerdeanpeters/Product-Manager-Skills7.2k2 repos~2.9kAutomated safety check: PassCustom licence
Ralph Tui Create Beadssubsy/ralph-tui2.5k1 repos~2.6kAutomated safety check: PassMIT
Agile Product Owneralirezarezvani/claude-skills28k3 repos~3.2kAutomated safety check: PassMIT
Ralph Tui Create Beads Rustsubsy/ralph-tui2.5k1 repos~2.8kAutomated safety check: PassMIT
To Specbestofjs/bestofjs3.1k22 repos~757Automated safety check: PassMIT

Similar skills

  • User Story Writer

    deanpeters/Product-Manager-Skills

    Writes user stories in Mike Cohn's format with Gherkin acceptance criteria, turning user needs into development-ready work with testable conditions.

    7.2k GitHub starsUsed in 2 repos~2.9k tokens
    Product & Project ManagementAuto-check passed
  • Ralph Tui Create Beads

    subsy/ralph-tui

    Convert PRDs to beads for ralph-tui execution. An agent skill from subsy/ralph-tui.

    2.5k GitHub starsUsed in 1 repo~2.6k tokens
    Product & Project ManagementAuto-check passed
  • Agile Product Owner

    alirezarezvani/claude-skills

    Writes INVEST-checked user stories with acceptance criteria, splits epics, plans sprints from velocity and ranks the backlog with a weighted score.

    28k GitHub starsUsed in 3 repos~3.2k tokens
    Product & Project ManagementAuto-check passed
  • Convert PRDs to beads for ralph-tui execution using beads-rust (br CLI).

    2.5k GitHub starsUsed in 1 repo~2.8k tokens
    Product & Project ManagementAuto-check passed
  • To Spec

    bestofjs/bestofjs

    Turn the current conversation into a spec and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.

    3.1k GitHub starsUsed in 22 repos~757 tokens
    Product & Project ManagementAuto-check passed
  • Ralph Tui Create JSON

    subsy/ralph-tui

    Convert PRDs to prd.json format for ralph-tui execution. An agent skill from subsy/ralph-tui.

    2.5k GitHub starsUsed in 1 repo~2.6k tokens
    Product & Project ManagementAuto-check passed

More from PackmindHub/packmind

All 35 skills in this repo
  • Michel CLI Demo Recorder

    PackmindHub/packmind

    Produce proof-of-execution demos of the Packmind CLI (packmind-cli) as terminal-styled images (colors and formatting preserved exactly), for embedding in a GitHub PR.

    317 GitHub stars~3.4k tokensUpdated yesterday
    Auto-check passed
  • Michel UI Demo Recorder

    PackmindHub/packmind

    Record polished UI demo videos and screenshots of a running web app using Playwright MCP — for client deliverables, release notes, feature walkthroughs, or bug repros.

    317 GitHub stars~6.4k tokensUpdated yesterday
    Auto-check passed
  • Packmind Create Skill

    PackmindHub/packmind

    Guide for creating effective skills. An agent skill from PackmindHub/packmind.

    317 GitHub stars~3.5k tokensUpdated yesterday
    Auto-check: notes
  • Doc Audit

    PackmindHub/packmind

    Audit Packmind end-user documentation (apps/doc/) for broken links, outdated CLI references, non-existent concepts, misleading information, and missing coverage.

    317 GitHub stars~2.4k tokensUpdated yesterday
    Auto-check passed
  • Feature Sprint

    PackmindHub/packmind

    Execute the implementation plan produced by /feature-spec. An agent skill from PackmindHub/packmind.

    317 GitHub stars~1.9k tokensUpdated yesterday
    Auto-check passed
  • Review an implemented GitHub issue the way a senior Packmind engineer would — the human-judgment checks that ESLint, the TypeScript compiler, and e2e tests cannot catch (authorization scoping…

    317 GitHub stars~2.7k tokensUpdated yesterday
    Auto-check passed

Questions about QA Review

What does QA Review do?

Review a user story implementation against its Example Mapping (EM) specification. QA Review is an agent skill from PackmindHub/packmind. Review a user story implementation against its Example Mapping (EM) specification.

When should I use QA Review?

QA Review fits situations like: tasks that involve User stories.

How do I install QA Review in Claude Code?

Run `npx skills add PackmindHub/packmind --skill qa-review -a claude-code`. Or copy the skill folder (.agents/skills/qa-review in PackmindHub/packmind) into .claude/skills/qa-review in your project. Claude Code loads it when a task matches its description.

How do I install QA Review in Codex?

Run `npx skills add PackmindHub/packmind --skill qa-review -a codex`. Or copy the skill folder (.agents/skills/qa-review in PackmindHub/packmind) into .agents/skills/qa-review in your project. Codex loads it when a task matches its description.

Can I use QA Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add PackmindHub/packmind --skill qa-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qa-review, .gemini/skills/qa-review, .github/skills/qa-review and .opencode/skills/qa-review in your project.

What does QA Review need to run?

SKILL.md names no scripts, command-line tools or credentials: QA Review is instructions for the agent only.

Does QA Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is QA Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does QA Review use?

QA Review is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does QA Review use?

About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to QA Review?

Skills that share tags, products or a category with QA Review: User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars), Ralph Tui Create Beads (subsy/ralph-tui, 2.5k stars), Agile Product Owner (alirezarezvani/claude-skills, 28k stars) and Ralph Tui Create Beads Rust (subsy/ralph-tui, 2.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains QA Review?

PackmindHub (a GitHub organization) maintains it in PackmindHub/packmind, which has 317 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on October 8, 2026.

Source: PackmindHub/packmind on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.