systematic-debugging

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Use when encountering any bug, test failure, or unexpected behavior. 4-phase root cause investigation — NO fixes without understanding the problem first.

AI & Automation 173,893 stars 29465 forks Updated today MIT

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# Systematic Debugging ## Overview Random fixes waste time and create new bugs. Quick patches mask underlying issues. **Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure. **Violating the letter of this process is violating the spirit of debugging.** ## The Iron Law ``` NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST ``` If you haven't completed Phase 1, you cannot propose fixes. ## When to Use Use for ANY technical issue: - Test failures - Bugs in production - Unexpected behavior - Performance problems - Build failures - Integration issues **Use this ESPECIALLY when:** - Under time pressure (emergencies make guessing tempting) - "Just one quick fix" seems obvious - You've already tried multiple fixes - Previous fix didn't work - You don't fully understand the issue **Don't skip when:** - Issue seems simple (simple bugs have root causes too) - You're in a hurry (rushing guarantees rework) - Someone wants it fixed NOW (systematic is faster than thrashing) ## The Four Phases You MUST complete each phase before proceeding to the next. --- ## Phase 1: Root Cause Investigation **BEFORE attempting ANY fix:** ### 1. Read Error Messages Carefully - Don't skip past errors or warnings - They often contain the exact solution - Read stack traces completely - Note line numbers, file paths, error codes **Action:** Use `read_file` on the relevant source files. Use `search_files` to find the error string in the codebase. ### 2. Rep...

Details

Author
NousResearch
Repository
NousResearch/hermes-agent
Created
10 months ago
Last Updated
today
Language
Python
License
MIT

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