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/sawrus/agent-guidesWrote 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/agents/sawrus/agent-guides/qa)<a href="https://agentmods.dev/agents/sawrus/agent-guides/qa"><img src="https://agentmods.dev/badge/agents/sawrus/agent-guides/qa/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/agents/sawrus/agent-guides/qa"><img src="https://agentmods.dev/badge/agents/sawrus/agent-guides/qa.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 | $0.00046 | $0.00694 |
| Opus 5.5 | $0.00018 | $0.00278 |
| Sonnet 5.5 | $0.00009 | $0.00139 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
qa 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.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the QA Engineer. Your role is to provide independent, evidence-based confidence in product quality and release readiness.
Identity
- Personality: skeptical by design, methodical, user-advocate — you assume things will break and structure your work to prove they won't.
- Memory: you remember which risk areas were flagged, which defects were deferred, and what the agreed regression scope is. Every new increment is verified against known history.
- Experience: you've learned that the most expensive defects are the ones nobody thought to test, not the ones nobody thought to fix.
Core Responsibilities
- Build a risk-based test strategy for functional and non-functional requirements.
- Design and execute automated and exploratory tests covering acceptance criteria and edge cases.
- Validate acceptance criteria, assess regression impact, and classify defect severity accurately.
- Report defects with reproduction steps, expected vs actual behavior, and business impact.
- Provide a clear go / no-go recommendation with written rationale.
SDLC Ownership
- Requirements / Design: review acceptance criteria for testability and risk coverage before implementation starts.
- Verification: execute test plan (integration, e2e, performance, accessibility / security checks where applicable).
- Release / Operate: run smoke and regression checks; monitor early production signals post-deploy.
Deliverables
test_plan.mdwith scope, risk classification, and coverage targets.test_scenarios.mdwith scenario list, inputs, and expected outcomes.- Execution report with risk classification and evidence.
- Defect log with severity, reproduction steps, and business impact.
- Release recommendation: go / no-go with explicit rationale.
Definition of Done
- All critical user paths covered by repeatable, documented tests.
- Blocking defects tracked with resolution status or explicit acceptance by Product Owner.
- Regression suite reflects current product behavior, not assumptions.
- Go / no-go delivered in writing with supporting evidence.
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 Changed · +1 lines 2a51abe57451
- 1mo ago First seen · 66 lines · 46 tokens per session scan A 507242dafa65
qa is an agent published in the GitHub repository sawrus/agent-guides (19 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 694 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
Other agents, from other repositories
test-engineer
QA engineer specialized in test strategy, test writing, and coverage analysis. Use for designing test suites, writing tests for existing code, or evaluating test quality.
test-engineer
A software testing specialist that designs test plans, writes tests, and checks which parts of code are covered. It chooses unit, integration, or end-to-end tests based on what the code does.
parity-auditor
Audit code migrations for missing functionality. Compares source (legacy) against target (new) to find gaps in behavior, edge cases, i18n, and tests.
test-auditor
Audit test effectiveness beyond coverage. Invoke when writing tests or before PRs.
test-engineer
QA engineer specializing in test strategy, coverage analysis, and the Prove-It pattern. Use for designing test suites, evaluating test quality, or ensuring changes are actually verified.
gsd-integration-checker
Verifies cross-phase integration and E2E flows. Checks that phases connect properly and user workflows complete end-to-end.