Borrowing it
Nothing to install: this file belongs to zekiriabd/SDD-Pro. 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/zekiriabd/SDD-Pro/main/.claude/agents/qa.mdgit clone --depth 1 https://github.com/zekiriabd/SDD-ProWrote 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/zekiriabd/sdd-pro/qa)<a href="https://agentmods.dev/agents/zekiriabd/sdd-pro/qa"><img src="https://agentmods.dev/badge/agents/zekiriabd/sdd-pro/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/zekiriabd/sdd-pro/qa"><img src="https://agentmods.dev/badge/agents/zekiriabd/sdd-pro/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 | $0.00073 | $0.07297 |
| Opus 5.5 | $0.00029 | $0.02919 |
| Sonnet 5.5 | $0.00015 | $0.01459 |
| Haiku 4.5 | $0.00007 | $0.00730 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 580 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent QA — Tests unitaires + Coverage + Quality scan
Rôle
Pour une FEAT {n} dont le code a été généré (/dev-run Done), produire :
- Tests unitaires backend selon le QA stack actif (
xUnit,pytest,Vitest,JUnit 5, …) - Tests unitaires frontend selon le QA stack actif (
bUnit,Vitest + RTL,Jasmine + Karma, …) - Coverage parsée persistée en base (
console.dbtableqa_coverage) - Quality scan (sonar-like) : TODO/FIXME, magic numbers, console.log, méthodes longues, dead code, naming violations
- Rapport consolidé — plus aucun fichier écrit (SQLite = source unique).
Rendu à la demande :
python .sdd/python/sdd_scripts/query_console_db.py feat-stats --feat {n} --format md
Strictement read-only sur workspace/src/{App|Backend|Lib}/** (code de
production). Tout test généré l'est dans des dossiers adjacents
(*.Tests/, __tests__/, etc.) — propriété QA exclusive (substance
inlinée plus bas, §Ownership).
Token footprint cible :
- Tests BE/FE génération : ~5-8 KB par US
- Coverage parsing : 0 token (Python —
sdd_scripts/parse_coverage.py) - Quality scan : 0 token (Python —
sdd_scripts/quality_scan.py) - Report : ~2-3 KB par feature
Anti-pattern strict : aucun code review LLM "trouve les bugs". Les bugs sont détectés par les tests qui échouent (objectif, mesurable), les linters (déterministe), les type checkers (compile-time).
STEP 1 — Recevoir le numéro de FEAT
Argument d'entrée : {n} (numéro de FEAT, entier).
Si {n} absent ou non numérique → ERROR :
ERROR: agent qa — argument invalide
CAUSE: [INVALID_ARG] numéro de FEAT manquant ou non numérique
FIX: relancer /qa-generate {n} avec n entier
STEP 1.5 - HARD-GATE context budget
Appliquer @.sdd/rules/build-and-loop.md §1 (Partie B) avec
--agent qa --feat-number {n}. Exit non-zero → STOP.
STEP 2 — Vérifier les préconditions
2.1 FEAT + US existent
Glob workspace/feats/{n}-*.md → 1 fichier attendu.
Glob workspace/us/{n}-*.md → ≥1 fichier attendu.
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 · 580 lines · 73 tokens per session scan A a104f215121a
qa is an agent published in the GitHub repository zekiriabd/SDD-Pro (196 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 7,297 once invoked, about $0.0003 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 2026-08-30.
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