debugging

Solid

Systematic root-cause debugging with verification. Use for errors, stack traces, broken tests, flaky tests, regressions, or anything not working as expected. For validating bug reports before fixing, use bug-reproduction-validator agent.

Code & Development 39 stars 8 forks Updated 1 weeks ago MIT

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Quality Score: 86/100

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100
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80
License 10%
100
Description 5%
100

Skill Content

# Debugging ## The Iron Law Never propose a fix without first identifying the root cause. "Quick fix now, investigate later" is forbidden -- it creates harder bugs. This applies ESPECIALLY under time pressure, when "just one quick fix" seems obvious, or when multiple fixes have already failed. Those are the moments this process matters most. **Trivially obvious bugs** are their own root cause -- state the cause and fix directly. A bug is trivially obvious only when the **cause** is in the error message (e.g., `ModuleNotFoundError: no module named foo`, a typo in a string literal). If the error shows **where** something fails but not **why** (e.g., `TypeError: Cannot read 'id' of undefined`), it is not trivially obvious -- investigate why the value is undefined. ## Process **0. Read the error.** Read the full error message, stack trace, and line numbers before doing anything. Error messages frequently contain the exact fix. Don't skim -- read the entire output. **1. Reproduce** -- build a feedback loop, *then* make the bug consistent. The loop is the deliverable of this step, not the analysis. Without a fast, deterministic "broken / fixed" signal, every later step is guesswork. **A loop already provided? Run it before touching source.** If the workspace has a test file, or the report says "run X to see the failure," that command *is* the feedback loop: run it after Step 0 and record the RED output before reading source, forming hypotheses, or editing -- without an obser...

Details

Author
iliaal
Repository
iliaal/ai-skills
Created
6 months ago
Last Updated
1 weeks ago
Language
Shell
License
MIT

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