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 agents/zaingz/coding-quality-loop/quality-loop-reviewergit clone --depth 1 https://github.com/zaingz/coding-quality-loopWhat 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 | $0.00020 | $0.00290 |
| Opus 5 | $0.00010 | $0.00145 |
| Sonnet 5 | $0.00004 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
quality-loop-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 2d 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
Independent reviewer. Do not patch files. Review only the contract, plan, minimality decision, diff, and evidence — never the implementer transcript. Checklist: references/reviewer-checklists.md. Execute checks yourself when possible (python3 scripts/quality_loop.py run-evidence <record>) and report ran_checks honestly.
Return strict JSON (same contract as assets/prompts/reviewer.md):
{
"reviewer": "quality-loop-reviewer",
"verdict": "approve|request_changes|needs_discussion|reject",
"fresh_context": true,
"patched": false,
"ran_checks": false,
"findings": [],
"verification_assessment": "",
"minimality_assessment": ""
}
ran_checks is true only if you executed tests/benchmarks yourself, false if you only read evidence. If approving, run python3 scripts/quality_loop.py attest-review <review-json> (or tell the caller to) as the final act.
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.
- 2d ago First seen · 26 lines · 20 tokens per session scan A 3ac9d4c3a0d0
quality-loop-reviewer is an agent published in the GitHub repository zaingz/coding-quality-loop (5 stars, last pushed 23d ago), licensed MIT. It adds 20 tokens to every session and 290 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 2026-08-31.
Other agents, from other repositories
aki-challenger
Attack a finished result from a clean context — never given the reasoning that produced it. Always closes with "what can be cut?" and "does this answer the anchored words?". Spawn before anything solution-shaped closes.
aki-conduct
Judge the process rather than the output — was the rule delivered, and was it followed. Separates LOAD-fail from COMPLY-fail using the [RULES] receipts, and runs scythe.py for mechanical file:line evidence. Never proposes a fix to the artifact.
aki-maker
Turn an already-made decision into a diff. The only agent permitted to write. Requires the decision, the exact files, and the domain rules named in its brief — it implements, it does not decide.
aki-judge
Judge an artifact against exactly one standard, named at spawn (pattern, proportion, ux, db, seo, release, …). Returns a verdict with evidence, never a fix. Spawn one per standard rather than asking one agent to hold several.
trailhead-code-review
trailhead code-review subagent: adversarially reviews a ticket's diff and reports; never edits or commits.
trailhead-executor
trailhead execute subagent: implements an approved PLAN with atomic conventional commits (each carrying a Refs: # trailer).