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noordeen123/culprit

by Various

Superpowers your agent's debugging: what introduced this bug, and is my fix actually complete? Deterministic, offline, read-only, MCP-native.

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noordeen123/culprit

Added 8 Sept 2026

#ai-agents#ci#claude-code#cli#code-review#coding-agents#developer-tools#git
Catalogue record, not a reviewed recommendation. This record can include automatically collected descriptions and setup details. Confirm important claims with the original source. Explore source-reviewed tools.

Overview

A deterministic, offline, read-only debugging tool for AI agents. It identifies which change introduced a bug and assesses whether a proposed fix is complete. Built as an MCP-native Python tool, it integrates with agent workflows without modifying the codebase.

Best for

Best for
Developers using AI agents who need reliable, non-intrusive debugging assistance.

Use cases

  • Pinpoint the commit or change that introduced a regression
  • Verify a fix addresses the root cause completely
  • Provide read-only debugging context to AI coding agents

How to use

Install

uvx culprit                     # run from PyPI on demand

Tools exposed

  • verify_fix
  • find_suspects
  • check_completeness
  • get_intent
  • get_evolution
  • get_risk_score
  • get_blast_radius
  • get_test_impact
  • classify_change
  • from_trace

Clients listed in this record (not verified here)

Claude Code, Cursor, Windsurf, Cline, Continue, VS Code

Notes

6 stars on GitHub. Last updated 2026-08-26. Licensed MIT.

Pros

  • Deterministic and offline, ensuring privacy and reproducibility
  • Read-only design avoids unintended side effects on the codebase
  • MCP-native integration simplifies use with agent frameworks

Cons

  • Limited adoption (6 stars) suggests early-stage maturity
  • Requires MCP-compatible environment to leverage its features
  • Scope may be narrow, focusing on bug introduction and fix completeness
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