Borrowing it
Nothing to install: this file belongs to PackmindHub/packmind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/PackmindHub/packmind/main/.agents/skills/qa-review/SKILL.mdgit clone --depth 1 https://github.com/PackmindHub/packmindWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/packmindhub/packmind/qa-review)<a href="https://agentmods.dev/skills/packmindhub/packmind/qa-review"><img src="https://agentmods.dev/badge/skills/packmindhub/packmind/qa-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/packmindhub/packmind/qa-review"><img src="https://agentmods.dev/badge/skills/packmindhub/packmind/qa-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00017 | $0.01772 |
| Opus 5.5 | $0.00007 | $0.00709 |
| Sonnet 5.5 | $0.00003 | $0.00354 |
| Haiku 4.5 | $0.00002 | $0.00177 |
Grade A, and why
qa-review 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- User Story title — the first line or heading describing the US
- Rules — each
# Rule N: <title>block. For each rule, extract:- Rule number and title
- Each
## Example Nwith its setup/action/outcome narrative (preserve the full text)
- Technical Rules — bullet points under a
# Technical rulesheading (implementation-focused constraints) - User Events — content under
# User Eventsheading: event names, properties, schemas - Check Also items — bullet points after "Check also" markers (additional rules/constraints, often separated by dashes)
- Code References — all backtick-quoted terms across the entire spec (class names, field names, event names like
ConflictDetector,space_created,decision) - 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.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 191 lines · 17 tokens per session scan A bdde4b22e913
qa-review is a skill published in the GitHub repository PackmindHub/packmind (319 stars, last pushed 4d ago), licensed Apache-2.0. It adds 17 tokens to every session and 1,772 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-22.
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