troubleshoot
Isolate root causes and propose targeted fixes with clear validation steps.
Best use case
troubleshoot is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Isolate root causes and propose targeted fixes with clear validation steps.
Teams using troubleshoot should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/troubleshoot/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How troubleshoot Compares
| Feature / Agent | troubleshoot | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Isolate root causes and propose targeted fixes with clear validation steps.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Troubleshoot ## Objective - Reproduce and isolate the issue. - Identify the most probable root cause and next actions. ## When to use - A bug or failure is reported or observed. - Symptoms are unclear and need narrowing down. ## Inputs - User-reported symptoms, logs, or reproduction steps. - AGENTS.md, rules, relevant code/tests. - Environment details if available. ## Process 1) Confirm and restate the symptom; note missing repro info. 2) Form quick hypotheses; prioritize simplest checks. 3) Collect minimal evidence (logs/tests/inputs) to confirm/deny hypotheses. 4) Identify the likely root cause or narrow to top candidates. 5) Propose next actions (fix path or deeper check) and validation steps. ## Outputs - Likely root cause (or narrowed hypotheses). - Evidence collected and what’s still unknown. - Proposed fix direction and validation plan. ## Edge cases - If repro is missing, request exact steps or data. - Avoid broad changes; focus on evidence-driven narrowing.
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