debug
SolidInvestigation-first debugging — gather evidence, form confirmed root-cause hypothesis, hand off to fix mode with diagnosis file. TRIGGER when: user reports a symptom or failing test with Python traceback, or asks to investigate a runtime/CI failure with reproducible evidence; phrases: "debug this failure", "why is X broken", "find the root cause of <error>", "investigate this CI failure". SKIP when: pure config quality issues (use `/foundry:audit`); broad system-wide diagnosis without traceback (use `/foundry:investigate`); user already knows the fix (use `/develop:fix`); non-Python project.
Install
Quality Score: 87/100
Skill Content
Details
- Author
- Borda
- Repository
- Borda/AI-Rig
- Created
- 5 months ago
- Last Updated
- today
- Language
- Python
- License
- Apache-2.0
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
fix
Reproduce-first bug resolution — capture bug in failing regression test, apply minimal fix, run quality stack and review loop. TRIGGER when: user reports a bug, regression, or unexpected behaviour in Python code with a traceback, failing test, or issue number; phrases: "fix this bug", "repair X", "broken since Y", "test failing". SKIP when: CI-only failures without local traceback (use `/develop:debug` first); new features (use `/develop:feature`); `.claude/` config issues (use `/foundry:audit`); non-Python projects.
debug
Diagnose Kandev bugs, running-instance issues, UI/browser failures, and runtime behavior. Use when the user reports unexpected behavior, asks to investigate, asks to add logs/instrumentation, or when a fix needs root-cause evidence before implementing. Triage first, gather evidence safely, then hand off to /fix for code changes.
debug
Root cause analysis for bugs and unexpected behavior. Traces errors through code, uses structured reasoning, and hands off to fix when cause is found. Core of the debug↔fix mesh. When the diagnosed cause is a memory leak in a long-running process, escalates to perf for cost-impact framing (leaks drive OOM-restart → cold-start → autoscaler spend, often 20-40% bill inflation).