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 skills add petrkindlmann/qa-skills --skill ai-test-generationgit clone --depth 1 https://github.com/petrkindlmann/qa-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/petrkindlmann/qa-skills/ai-test-generation)<a href="https://agentmods.dev/skills/petrkindlmann/qa-skills/ai-test-generation"><img src="https://agentmods.dev/badge/skills/petrkindlmann/qa-skills/ai-test-generation/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/petrkindlmann/qa-skills/ai-test-generation"><img src="https://agentmods.dev/badge/skills/petrkindlmann/qa-skills/ai-test-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 49 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 50 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 205 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00169 | $0.04451 |
| Opus 5 | $0.00084 | $0.02226 |
| Sonnet 5 | $0.00034 | $0.00890 |
| Haiku 4.5 | $0.00017 | $0.00445 |
Grade A, and why
ai-test-generation 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 11d 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before starting: Check for .agents/qa-project-context.md in the project root. It carries tech stack, test frameworks, naming conventions, selector strategy, and known risk areas that dramatically improve generated test quality.
Quick Route
The pipeline is the same for every input; only the Step 1 extraction emphasis changes. Jump to the matching row, then run Steps 2-7 unchanged.
| Input type | Step 1 extracts | Watch for |
|---|---|---|
| PRD / feature spec | Entities, business rules, acceptance criteria, NFRs, stated assumptions | Implicit requirements inferred from "seamless"/"fast" language |
| User story + AC | Each AC → ≥1 happy + ≥1 negative scenario | ACs that hide multiple behaviors in one line |
Code diff (git diff main...HEAD) |
New/changed code paths, modified conditionals, removed behavior | Regression scope: test the changed paths, not the whole module |
| Bug report | Repro steps, expected vs actual, environment | Write a test asserting expected — fails now, passes after fix |
| OpenAPI / GraphQL SDL | Endpoints, schemas, required fields, enums, auth | Validation, auth-failure, and edge cases per endpoint, not just 200s |
Playwright projects also pick an agent integration mode — see Discovery Q2.
Discovery Questions
Check .agents/qa-project-context.md first — if it exists, use it and skip anything already answered there. Then clarify:
- What is the input source? PRD / spec, user story + AC, code diff, bug report, or API schema. Determines Step 1 extraction emphasis (see Quick Route). For an LLM/AI feature spec, stop — generate eval datasets in
ai-system-testing, not Playwright specs.
What ships with it
1 file 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.
- 11d ago First seen · 250 lines · 169 tokens per session scan A e675c3e58f7c
ai-test-generation is a skill published in the GitHub repository petrkindlmann/qa-skills (118 stars, last pushed 3mo ago), licensed MIT. It adds 169 tokens to every session and 4,451 once invoked, about $0.0008 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 2026-08-30.
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