Borrowing it
Nothing to install: this file belongs to roderik/ai-rules. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/roderik/ai-rules/main/.claude/skills/rr-system/assets/ai-configs/agents/quality-control.mdgit clone --depth 1 https://github.com/roderik/ai-rulesWrote 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/roderik/ai-rules/quality-control)<a href="https://agentmods.dev/agents/roderik/ai-rules/quality-control"><img src="https://agentmods.dev/badge/agents/roderik/ai-rules/quality-control/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/roderik/ai-rules/quality-control"><img src="https://agentmods.dev/badge/agents/roderik/ai-rules/quality-control.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 | $0.00000 | $0.01213 |
| Opus 5.5 | $0.00000 | $0.00485 |
| Sonnet 5.5 | $0.00000 | $0.00243 |
| Haiku 4.5 | $0.00000 | $0.00121 |
Grade A, and why
quality-control 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 1mo 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 1mo ago First seen · 97 lines · 0 tokens per session scan A 1d4e6959b31b
quality-control is an agent published in the GitHub repository roderik/ai-rules (54 stars, last pushed yesterday), with no licence file. It costs nothing until one of its globs matches a file; then it loads 1,213 tokens. 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
spec-tdd-impl-agent
Execute implementation tasks using Test-Driven Development methodology.
test-case-result-validator
Compares old vs new instruction outputs against original codebase, scores 8 quality categories, emits pass/fail JSON verdict for CI/CD validation pipeline.
kingdee-qa-engineer
QA & Test Engineer for the kingdee-mcp project. Authors evals/ and tests/ cases, reproduces bugs against the live K3Cloud environment, and runs regression scans via bin/kmcp test.
e2e-runner
End-to-end testing specialist using Playwright — selector discipline, POM, and flake avoidance with explicit browser-output isolation. Use when qa-engineer delegates E2E authoring/debugging or task explicitly requires Playwright specs; opt-in via holistic caller — not a daily entry point.
qa
Use this agent for quality verification, test strategy, defect classification, and release go/no-go decisions. Invoke after the developer delivers an increment. This agent produces test plans, executes verification, and issues a written release recommendation.
analyst
Use this agent for system analysis: requirements, user and system scenarios, API/data contracts, testable acceptance criteria, and UX states. Invoke during planning to produce the analysis specification, and during verification to confirm requirements and contract coverage.