Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ashermahonin/agentic-skills/qa-evalnpx skills add ashermahonin/agentic-skills --skill qa-evalgit clone --depth 1 https://github.com/ashermahonin/agentic-skillsWrote 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/ashermahonin/agentic-skills/qa-eval)<a href="https://agentmods.dev/skills/ashermahonin/agentic-skills/qa-eval"><img src="https://agentmods.dev/badge/skills/ashermahonin/agentic-skills/qa-eval.svg" alt="Measured on agentmods" 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 | $0.00080 | $0.00417 |
| Opus 5 | $0.00040 | $0.00209 |
| Sonnet 5 | $0.00016 | $0.00083 |
| Haiku 4.5 | $0.00008 | $0.00042 |
Grade A, and why
qa-eval 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 6d 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.
What it actually says
QA and Eval
Purpose
Prove the important behavior works and the important risks are covered. Make verification practical, visible, and tied to acceptance criteria.
Change context
- Collect requirements, acceptance criteria, changed files, and risk notes.
- Identify the minimum test set that covers the behavior and highest risks.
- Separate automated checks from manual smoke checks.
- Decide what cannot be verified in this environment and how to report it honestly.
Change method
- Map each acceptance criterion to a validation method.
- Run existing tests before inventing new ones when that gives useful signal.
- Add focused tests when behavior changed and no existing test covers it.
- For UI work, verify real rendering and main workflows when possible.
- For migrations or data changes, verify rollback or safe failure behavior.
- Summarize pass/fail evidence with commands, scenarios, and residual risk.
Engineering constraints
- Use Context7 MCP for current library, framework, platform, API, CLI, and configuration documentation whenever the task depends on external technology behavior.
Evidence
- Validation plan
- Commands run
- Acceptance evidence
- Bugs or regressions found
- Release readiness recommendation
Ready when
- Do not treat compilation as full QA.
- Do not hide skipped checks.
- Tie every critical risk to a test, smoke check, or explicit residual risk.
- Keep bug reports reproducible.
Handoff
Hand off evidence, failures, skipped checks, and release recommendation to PR review or release docs.
References
references/eval-plan.md: Use this for test and eval planning.
What ships with it
2 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.
- 6d ago First seen · 54 lines · 80 tokens per session scan A 447865a7ff7c
qa-eval is a skill published in the GitHub repository ashermahonin/agentic-skills (10 stars, last pushed 12d ago), licensed MIT. It adds 80 tokens to every session and 417 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
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