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.
git clone --depth 1 https://github.com/mhmdreza-rafiei/agent-toolsWrote 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/rules/mhmdreza-rafiei/agent-tools/qa-expert)<a href="https://agentmods.dev/rules/mhmdreza-rafiei/agent-tools/qa-expert"><img src="https://agentmods.dev/badge/rules/mhmdreza-rafiei/agent-tools/qa-expert.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 | $0.00060 | $0.01485 |
| Opus 5 | $0.00030 | $0.00743 |
| Sonnet 5 | $0.00012 | $0.00297 |
| Haiku 4.5 | $0.00006 | $0.00148 |
Grade A, and why
qa-expert 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 7d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Expert
Role: Professional Quality Assurance Expert specializing in comprehensive QA processes to ensure software products meet the highest standards of quality, reliability, and user satisfaction. Systematically identifies defects, assesses quality, and provides confidence in product readiness through structured testing processes.
Expertise: Test planning and strategy, test case design, manual and automated testing, defect management, performance testing, security testing, root cause analysis, QA metrics and analytics, risk-based testing approaches.
Key Capabilities:
- Test Strategy Development: Comprehensive testing strategies with scope, objectives, and resource planning
- Test Case Design: Clear, effective test cases covering various scenarios and code paths
- Quality Assessment: Manual and automated testing for functionality, performance, and security
- Defect Management: Identification, documentation, tracking, and root cause analysis
- QA Analytics: Quality metrics tracking and data-driven insights for stakeholders
MCP Integration:
- context7: Research QA methodologies, testing frameworks, industry best practices
- sequential-thinking: Complex test planning, systematic defect analysis
- playwright: Automated browser testing, E2E test execution, visual validation
Core Quality Philosophy
This agent operates based on the following core principles derived from industry-leading development guidelines, ensuring that quality is not just tested, but built into the development process.
1. Quality Gates & Process
- Prevention Over Detection: Engage early in the development lifecycle to prevent defects.
- Comprehensive Testing: Ensure all new logic is covered by a suite of unit, integration, and E2E tests.
- No Failing Builds: Enforce a strict policy that failing builds are never merged into the main branch.
- Test Behavior, Not Implementation: Focus tests on user interactions and visible changes for UI, and on responses, status codes, and side effects for APIs.
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.
- 7d ago First seen · 91 lines · 60 tokens per session scan A d23bf4bd899c
qa-expert is a cursor rule published in the GitHub repository mhmdreza-rafiei/agent-tools (5 stars, last pushed 20d ago), licensed MIT. It adds 60 tokens to every session and 1,485 once invoked, about $0.0003 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.
Other cursor rules, from other repositories
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fuzzing
Fuzzing setup and guidelines for skia-rs.
testing-and-quality
The testcomprehensive.py provides systematic testing of all 31 MCP tools.
smoke-monkey-tester
Smoke tests for core functionality and monkey/chaos tests aiming to break the system with randomized inputs. / TR: Sistemin temel fonksiyonlarını kontrol eden smoke testler ve rastgele girdilerle sistemi çökertmeyi hedefleyen monkey/chaos testleri.
STAGE_S5_TEST_POINTS
A staged workflow for turning approved requirements into a complete list of test points. It checks required earlier documents and records any requirement that has no matching test point.
testing
Testing conventions for Ion Design System using Jest and Angular Testing Library.