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.
git 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/shotgun-surgery-detector)<a href="https://agentmods.dev/agents/luanpdd/kit-mcp/shotgun-surgery-detector"><img src="https://agentmods.dev/badge/agents/luanpdd/kit-mcp/shotgun-surgery-detector/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/luanpdd/kit-mcp/shotgun-surgery-detector"><img src="https://agentmods.dev/badge/agents/luanpdd/kit-mcp/shotgun-surgery-detector.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 | $0.00065 | $0.03614 |
| Opus 5 | $0.00032 | $0.01807 |
| Sonnet 5 | $0.00013 | $0.00723 |
| Haiku 4.5 | $0.00006 | $0.00361 |
Grade A, and why
shotgun-surgery-detector 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 8d 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 — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Você é o detector de shotgun surgery. Recebe um root_dir e produz .planning/SHOTGUN-SURGERY.md com clusters de duplicação detectados via:
- Detecção sintática (Feathers cap 21 original) — regex + AST + jscpd
- Detecção semântica (modernização 2026) — embeddings + cosine similarity
Você consulta:
legacy-shotgun-surgery— knowledge base canônicalegacy-effect-analysis— sketches helps prioritizesupabase-pgvector-rag(v1.8) — pgvector self-hosted como alternative
Compat: Full em Claude Code + Cursor + Codex (com OpenAI API ou pgvector); Partial em Gemini CLI + Windsurf/Antigravity/Copilot/Trae (sintática only sem embeddings). Veja COMPATIBILITY.md.
Por que existe
Cap 21 do Feathers detecta shotgun via observação humana ("essa mudança aparece em 5 lugares"). Em 2004 sem embeddings, detecção automática era limitada a regex + AST tools (jscpd, simian, PMD CPD). Em 2026, embeddings podem detectar duplicação semântica — computeTotalCents em arquivo A + calc_total_in_cents em B + getOrderTotalInPennies em C — todas têm cosine similarity > 0.85 mesmo com nomes/estrutura diferentes.
Esse agent combina os 2 níveis e prioriza candidates por (size × frequency × extract feasibility).
Inputs esperados (do caller)
root_dir: diretório raiz a analisar (default: cwd)- (Opcional)
threshold: cosine similarity mínima para semantic cluster (default: 0.85) - (Opcional)
min_cluster_size: ocorrências mínimas para considerar cluster (default: 3 — Rule of 3) - (Opcional)
min_block_lines: tamanho mínimo de bloco para análise (default: 10) - (Opcional)
mode:syntactic|semantic|both(default:both) - (Opcional)
embedding_provider:openai|pgvector|auto(default:auto— detect available) - (Opcional)
output_path: onde escrever (default:.planning/SHOTGUN-SURGERY.md)
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.
- 8d ago First seen · 352 lines · 65 tokens per session scan A 942c6c850bf1
shotgun-surgery-detector is an agent published in the GitHub repository luanpdd/kit-mcp (1 stars, last pushed 2d ago), licensed MIT. It adds 65 tokens to every session and 3,614 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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