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 skills add parisgroup-ai/imersao-ia-setup --skill test-rigor-auditgit clone --depth 1 https://github.com/parisgroup-ai/imersao-ia-setupWrote 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/skills/parisgroup-ai/imersao-ia-setup/test-rigor-audit)<a href="https://agentmods.dev/skills/parisgroup-ai/imersao-ia-setup/test-rigor-audit"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/test-rigor-audit/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/skills/parisgroup-ai/imersao-ia-setup/test-rigor-audit"><img src="https://agentmods.dev/badge/skills/parisgroup-ai/imersao-ia-setup/test-rigor-audit.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 | $0.00152 | $0.03524 |
| Opus 5.5 | $0.00061 | $0.01410 |
| Sonnet 5.5 | $0.00030 | $0.00705 |
| Haiku 4.5 | $0.00015 | $0.00352 |
Grade A, and why
test-rigor-audit 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 21d 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Rigor Audit
Audita uma suite de testes pra encontrar testes que não fazem trabalho real — testes que passam (ou poderiam passar) independentemente do código sob teste estar correto. Cobre vitest/jest, pytest, Playwright e bats.
Core Principle
Um teste faz trabalho real se, e somente se, ele FALHA quando o código sob teste quebra de forma significativa.
Tudo o que esta skill detecta é uma violação dessa regra: assertion tautológica, ausência de assertion, mock que cobre o próprio SUT, exception silenciosamente engolida, skip sem tracker. O sintoma comum é: "o teste estava verde, mas não pegou a regressão". Esta skill encontra esses testes antes da regressão.
A skill é audit-only. Não aplica fix automático — cada anti-pattern tem decisão humana (deletar vs fortalecer vs investigar SUT). Pra os achados graves, gera body de TaskNote pronto pra criar via pnpm task:new.
Quando usar
- Antes de refatorar um SUT. Os testes precisam pegar regressão pro refactor ser seguro. Audit primeiro, refactor depois.
- Pós-merge de PR grande. Cluster de testes novos é o momento de pegar weak tests com contexto fresco.
- Onboarding em codebase legado. Suite verde é informação enganosa se 30% dos testes não asseguram nada.
- Quando uma regressão escapou. Se o teste devia ter pego e não pegou, a suite tem um padrão sistêmico — audit acha os parentes do teste falho.
- Periodicamente em projetos com >1k testes. Drift de rigor acumula silenciosamente.
Não é o caso de uso pra Quality Gate diário — isto é uma skill de deep audit, lenta e meticulosa. Pra gates contínuos, use coverage-check + lint rules específicas (ex: eslint-plugin-vitest expect-expect).
Workflow
┌──────────────────────────────────────────────────────────────────────┐
│ 1. ESCOPO — file/dir/pattern do alvo + framework detection │
│ 2. GREP — mechanical sweep (grep recipes por framework) │
│ 3. READ — leitura dos arquivos sinalizados pra análise contextual│
│ 4. CLASSIFY — categorize por anti-pattern + severidade │
│ 5. REPORT — markdown report agrupado por arquivo │
│ 6. TASKNOTE — bodies prontos pros achados HIGH severity │
└──────────────────────────────────────────────────────────────────────┘
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 21d ago First seen · 254 lines · 152 tokens per session scan A 1430a1b83aff
test-rigor-audit is a skill published in the GitHub repository parisgroup-ai/imersao-ia-setup (1 stars, last pushed 20d ago), licensed MIT. It adds 152 tokens to every session and 3,524 once invoked, about $0.0006 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 2026-10-06.
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