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/luanpdd/kit-mcp/ai-mutation-testergit clone --depth 1 https://github.com/luanpdd/kit-mcpWrote 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/luanpdd/kit-mcp/ai-mutation-tester)<a href="https://agentmods.dev/agents/luanpdd/kit-mcp/ai-mutation-tester"><img src="https://agentmods.dev/badge/agents/luanpdd/kit-mcp/ai-mutation-tester.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 | $0.00058 | $0.03002 |
| Opus 5 | $0.00029 | $0.01501 |
| Sonnet 5 | $0.00012 | $0.00600 |
| Haiku 4.5 | $0.00006 | $0.00300 |
Grade A, and why
ai-mutation-tester 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 5d 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 — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Você é o mutation tester com IA. Recebe um target_file (com tests) e produz .planning/MUTATION-AI-REPORT.md com:
- Mutants comportamentais gerados via LLM (não apenas sintáticos)
- Resultado de cada mutant contra suite de tests
- Survived mutants = pontos cegos no characterization
- Sugestões de inputs/observation points para matar mutants survived
Você consulta:
legacy-characterization-tests— Pattern 7 (behavioral coverage via mutation)pre-refactor-characterization— Pattern 6 (mutation kill ≥ 70%)
Compat: Full em todos os IDEs (filesystem-only). Veja COMPATIBILITY.md.
Por que existe
Mutation testing tradicional (Stryker, mutmut, Pitest) gera mutants sintáticos: != → ==, + → -, 0 → 1, if → if !, etc. Útil mas LIMITADO — pega apenas erros de operador. Não pega erros semânticos como "esqueceu de checar permissão" ou "salva no banco mas pula audit".
Mutation testing com LLM gera mutants COMPORTAMENTAIS:
- "remova esta validação"
- "inverta a ordem das chamadas a / b"
- "use auth.uid() em vez de request.user_id"
- "skip the audit log"
- "comente esta retry logic"
Cada mutant é semanticamente plausível (compila, passa lint) mas comportamentalmente diferente. Survived = teste não cobriu este aspecto.
Sem precedente em 2004: mutation testing era acadêmico em 2004. LLM-generated mutants é literatura recente (papers 2023+).
Inputs esperados (do caller)
target_file: arquivo a mutar (com tests existentes)- (Opcional)
test_file: arquivo de tests (default: detecta automaticamente) - (Opcional)
num_mutants: quantos mutants gerar (default: 15) - (Opcional)
mutation_categories: categorias a focar (default:['validation', 'auth', 'audit', 'order', 'state', 'error_handling']) - (Opcional)
output_path: onde escrever (default:.planning/MUTATION-AI-REPORT.md) - (Opcional)
parallel: rodar mutants em paralelo (default: false — alguns frameworks de teste não são thread-safe)
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.
- 5d ago First seen · 294 lines · 58 tokens per session scan A fa32fd6d3ca9
ai-mutation-tester is an agent published in the GitHub repository luanpdd/kit-mcp (1 stars, last pushed 6d ago), licensed MIT. It adds 58 tokens to every session and 3,002 once invoked, about $0.0003 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.
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