Borrowing it
Nothing to install: this file belongs to compozy/skeeper. 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/compozy/skeeper/main/.agents/skills/qa-report/SKILL.mdgit clone --depth 1 https://github.com/compozy/skeeperWrote 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/compozy/skeeper/qa-report)<a href="https://agentmods.dev/skills/compozy/skeeper/qa-report"><img src="https://agentmods.dev/badge/skills/compozy/skeeper/qa-report/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/compozy/skeeper/qa-report"><img src="https://agentmods.dev/badge/skills/compozy/skeeper/qa-report.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 | $0.00083 | $0.02555 |
| Opus 5.5 | $0.00033 | $0.01022 |
| Sonnet 5.5 | $0.00017 | $0.00511 |
| Haiku 4.5 | $0.00008 | $0.00255 |
Grade A, and why
qa-report 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Test Planner
Plan and document QA deliverables — test plans, test cases, regression suites, Figma validations, and bug reports — in a structured format compatible with qa-execution execution.
Required Inputs
- qa-output-path (optional): Directory where all QA artifacts are stored. When provided, create the directory if it does not exist. When omitted, use the current working directory. This path must match the same argument passed to
qa-executionwhen both skills are used together.
Shared Output Structure
All artifacts follow this directory layout, shared with qa-execution:
<qa-output-path>/qa/
├── test-plans/ # Test plan documents
├── test-cases/ # Individual test case files (TC-*.md)
├── issues/ # Bug reports (BUG-*.md)
├── screenshots/ # Visual evidence and Figma comparisons
└── verification-report.md # Generated by qa-execution
Procedures
Step 1: Resolve Output Directory
- If the user provided a
qa-output-pathargument, use that path. - Otherwise, default to the current working directory.
- Create the
qa/subdirectory under the resolved path, then createqa/test-plans/,qa/test-cases/,qa/issues/, andqa/screenshots/if they do not exist.
Step 2: Identify the Deliverable Type
Parse the user request to determine which deliverable to generate:
| Request Pattern | Deliverable | Output Path |
|---|---|---|
| "Create test plan for..." | Test Plan | test-plans/ |
| "Generate test cases for..." | Test Cases | test-cases/ |
| "Build regression suite..." | Regression Suite | test-plans/ |
| "Compare with Figma..." | Figma Validation | test-cases/ (TC-UI-*) |
| "Document bug..." | Bug Report | issues/ |
Step 3: Generate Test Plans
- Read
references/test_case_templates.mdfor the test plan structure. - Generate a test plan document with these mandatory sections:
- Executive summary with objectives and key risks.
- Scope definition (in-scope and out-of-scope).
- Test strategy and approach.
- Automation strategy covering which flows should become E2E, which remain manual-only, and which are blocked by environment gaps.
- Environment requirements (OS, browsers, devices).
- Entry criteria (what must be true before testing begins).
- Exit criteria (what must be true before testing ends, including pass-rate thresholds and automation follow-up expectations for critical flows).
- Risk assessment table (Risk, Probability, Impact, Mitigation).
- Timeline and deliverables.
- Write the plan to
<qa-output-path>/qa/test-plans/<feature-slug>-test-plan.md.
What ships with it
7 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 · 197 lines · 83 tokens per session scan A 2e1de5b2491a
qa-report is a skill published in the GitHub repository compozy/skeeper (89 stars, last pushed 4mo ago), licensed MIT. It adds 83 tokens to every session and 2,555 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
qa-test-planner
Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.
critique
Adversarial design critique of the current work — render it, look at it, and argue for rejection. Run after the gates are green, never instead of them.
visual-validation
Autonomous screenshot verification — captures, compares, and AI-evaluates UI changes for visual regressions.
design-ship
One-shot pipeline turning a claude.ai/design link into a pull request: scaffold via /ork:design-import, stories and specs via /ork:cover, browser verification via /ork:expect, then open the PR. Use when a design link should come back as a PR with no intermediate steps; if all you need is the components written to…
testing-coach
How to test: screen readers, keyboard passes, automated checks and CI.
shaft-accessibility-testing
Use when testing web or mobile accessibility for WCAG conformance, keyboard and focus behavior, semantics, errors, or user impact.