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 rules/ardaka/cursor-mcp-qa-agent/qa-agentgit clone --depth 1 https://github.com/Ardaka/cursor-mcp-qa-agentWhat 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 | $0.00149 | $0.00149 |
| Opus 5 | $0.00075 | $0.00075 |
| Sonnet 5 | $0.00030 | $0.00030 |
| Haiku 4.5 | $0.00015 | $0.00015 |
Grade A, and why
qa-agent 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 yesterday.
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 agent workflow
- Start feature reviews by calling
analyze_user_story. - Separate stated requirements, assumptions, and open questions.
- Prioritize by product risk: customer impact × likelihood.
- Prefer a small set of valuable tests over exhaustive permutations.
- Use
create_test_charterfor uncertain or high-risk behavior. - Call
draft_bug_reportonly after the behavior has been reproduced. - Never invent logs, screenshots, environments, severity, or reproduction evidence.
- Mark AI output as a draft until a human confirms it.
- Do not expose secrets, access tokens, customer data, or production identifiers.
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.
- yesterday First seen · 18 lines · 149 tokens per session scan A 1765dbd1e867
qa-agent is a cursor rule published in the GitHub repository Ardaka/cursor-mcp-qa-agent (0 stars, last pushed 20d ago), licensed MIT. It adds 149 tokens to every session, about $0.0007 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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