Borrowing it
Nothing to install: this file belongs to vlad-ryzhkov/AI-QA-workshop-feb19. 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/vlad-ryzhkov/AI-QA-workshop-feb19/main/.agents/skills/test-cases/SKILL.mdgit clone --depth 1 https://github.com/vlad-ryzhkov/AI-QA-workshop-feb19Wrote 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/vlad-ryzhkov/ai-qa-workshop-feb19/test-cases)<a href="https://agentmods.dev/skills/vlad-ryzhkov/ai-qa-workshop-feb19/test-cases"><img src="https://agentmods.dev/badge/skills/vlad-ryzhkov/ai-qa-workshop-feb19/test-cases/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/vlad-ryzhkov/ai-qa-workshop-feb19/test-cases"><img src="https://agentmods.dev/badge/skills/vlad-ryzhkov/ai-qa-workshop-feb19/test-cases.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 | $0.00016 | $0.00124 |
| Opus 5 | $0.00008 | $0.00062 |
| Sonnet 5 | $0.00003 | $0.00025 |
| Haiku 4.5 | $0.00002 | $0.00012 |
Grade A, and why
test-cases 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.
What it actually says
INSTRUCTIONS
You are acting as the QA Automation Lead.
Read AGENTS.md to understand the project philosophy and tech stack.
LOGIC SOURCE
Execute the full instruction set defined in: .claude/skills/test-cases/SKILL.md
CRITICAL REMINDERS
- Cover positive, negative, edge cases and security scenarios.
- Output as Markdown table for use as input to
$api-tests. - Do NOT generate test code — use
$api-testsfor that.
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 · 19 lines · 16 tokens per session scan A 9d9e5ddd6afc
test-cases is a skill published in the GitHub repository vlad-ryzhkov/AI-QA-workshop-feb19 (25 stars, last pushed 6mo ago), licensed Unlicense. It adds 16 tokens to every session and 124 once invoked, about $0.0001 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.
Other skills, from other repositories
agents-checker
Verifies structural integrity and compliance of .claude/agents/ and .claude/qaagent.md against init-agent standards. Use after modifying agent files. Do not use for SKILL.md audit — use /skill-audit.
update-ai-setup
Scans project AI files and updates the docs/ai-setup.md Registry with current data. Use to synchronize the Registry after adding/removing Skills, patterns, or configs. Do not use to create a Registry from scratch — create docs/ai-setup.md manually instead.
curate-lessons
Curates pending lessons from .ai-lessons/pending.md into context files. Use when pending.md has ≥3 entries to deduplicate and promote lessons. Do not use to create rules from scratch.
tdd-implementation
Use Test-Driven Development for features that benefit from upfront behavior specification.
fix-from-logs
Diagnoses bugs from raw error logs, stack traces, or CI failure output — triages and clusters errors, localizes root cause (file → function → line), enters plan mode with a structured fix + test proposal for human approval, writes a typed pytest regression test using mocks first, then implements a targeted code fix…
auto-research
Autonomously optimizes any Claude skill (SKILL.md) or CLAUDE.md file through a closed hypothesis→test→evaluate→keep/discard loop, producing an updated skill file and an iteration dashboard (baseline score, each hypothesis, keep/discard decision, improvement delta). Use when a user wants to improve a skill's output…