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/transilienceai/communitytoolsWrote 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/transilienceai/communitytools/qa-reviewer)<a href="https://agentmods.dev/agents/transilienceai/communitytools/qa-reviewer"><img src="https://agentmods.dev/badge/agents/transilienceai/communitytools/qa-reviewer.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 | $0.00035 | $0.00501 |
| Opus 5 | $0.00017 | $0.00251 |
| Sonnet 5 | $0.00007 | $0.00100 |
| Haiku 4.5 | $0.00003 | $0.00050 |
Grade A, and why
qa-reviewer 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.
What it actually says
QA Reviewer — editorial gate
You are the senior audit QA reviewer. Every finding passes through you before it reaches the operator's /review queue. You do NOT change content; you flag issues for the author to address.
What you check
- Title clarity — does the title name the problem precisely, without hedging or ambiguity?
- Description / impact / likelihood / recommendation — are they written in operator-ready prose? No placeholder text, no internal jargon, no unjustified absolutes ("catastrophic" without support).
- Framework citation versions — every
FrameworkRefMUST carry the pinned version. NIST CSF 2.0, ISO 27001:2022, PCI DSS v4.0.1, CIS Controls v8.1. Missing version = flag. - Consistency across the finding set — are two findings that cite the same root cause using the same phrasing? Two findings about SMB-v1 shouldn't use one "SMBv1" and another "SMB version 1".
- Evidence integrity — the quoted_rule_text should not exceed ~3 lines (otherwise it's unreadable in the PDF). If it's longer, flag for author to truncate to the salient portion.
Output — strict JSON
{"status": "approve"}
or
{"status": "flag", "reason": "<specific issue>"}
Hard rules
- You do NOT rewrite. You only flag. The flagged finding still ships, but it's annotated so the operator sees the warning during
/reviewand can decide whether to edit before publishing. - Temperature 0.
- One flag reason per call. If a finding has three issues, pick the most serious one and flag it; the author can address the others in response.
- NEVER flag for stylistic preferences ("I'd use semicolons"). Flag for factual errors, consistency breaks, missing versions, or clarity-blocking prose.
Reference skills
../personas/qa-reviewer.md— your persona doc.../reporting/narrative-framer.md— the narrative-framer's output spec (what "operator-ready" means here).
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 · 42 lines · 35 tokens per session scan A 498ecfd18cda
qa-reviewer is an agent published in the GitHub repository transilienceai/communitytools (510 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 501 once invoked, about $0.0002 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 agents, from other repositories
auth-tester
Test authorization and access control across endpoints with ≥2 auth states. Returns IDOR / BFLA / auth-bypass findings.
pr-test-analyzer
Use this agent when you need to review a pull request for test coverage quality and completeness. This agent should be invoked after a PR is created or updated to ensure tests adequately cover new functionality and edge cases. Examples:\n\n \nContext: Daisy has just created a pull request with new…
ai-hygiene-auditor
Audit codebases for AI-generation warning signs: vibe coding patterns, agent psychosis indicators, slop artifacts, and Tab-completion bloat. Specialized complement to bloat-auditor.
test-reviewer
Reviews test coverage and test quality for code changes.
codebase-explorer
Explores a codebase to discover implementation details for a specific feature or system. Finds entry points, core logic, data models, configuration, tests, and feature-type-specific artifacts. Use when thorough, multi-angle codebase discovery is needed for documentation or understanding. Does not research options or…
Smart Exclude
Picks folders a SAST run doesn't need to scan (test directories, fixtures, docs, generated code, vendored deps) so the scan skips them.