
debugging-protocol
by irahardianto
Self-hosted RAG engine for AI coding assistants. Ingests technical docs & code repositories locally with structure-aware chunking. Serves grounded context via MCP to prevent hallucinations in software development workflows.
SKILL.md
name: debugging-protocol description: Comprehensive protocol for validating root causes of software issues. Use when you need to systematically debug a complex bug, flaky test, or unknown system behavior by forming hypotheses and validating them with specific tasks.
Debugging Protocol
Overview
This skill provides a rigorous framework for debugging complex software issues. It moves beyond ad-hoc troubleshooting to a structured process of hypothesis generation and validation.
Use this skill to:
- Formalize a debugging session.
- Systematically eliminate potential root causes.
- Document findings for future reference or team communication.
Protocol Workflow
To run a structured debugging session, follow these steps:
1. Initialize the Session
Create a new debugging document using the provided template. This serves as the "source of truth" for the investigation.
Template location: assets/debugging-session-template.md
2. Define the Problem
Clearly articulate the System Context and Problem Statement.
- Symptom: What is the observable behavior? How does it differ from expected behavior?
- Scope: Which components are involved?
3. Formulate Hypotheses
List distinct, testable hypotheses.
- Avoid vague guesses.
- Differentiate between layers (e.g., "Frontend Hypothesis" vs "Backend Hypothesis").
- Example: "Race condition in UI state update" vs "Database schema misconfiguration".
4. Design Validation Tasks
For each hypothesis, design a specific validation task.
- Objective: What are you trying to prove or disprove?
- Steps: Precise, reproducible actions.
- Code Pattern: Provide the exact code or command to run (e.g., a specific SQL query, a Python script using the client library, a
curlcommand). - Success Criteria: Explicitly state what output confirms the hypothesis.
5. Execute and Document
Run the tasks in order. For each task, record:
- Status: ✅ VALIDATED, ❌ FAILED, or ⚠️ INCONCLUSIVE.
- Findings: Key observations and raw evidence (logs, screenshots).
- Conclusion: Does this support or refute the hypothesis?
6. Determine Root Cause
Synthesize the findings into a Root Cause Analysis.
- Identify the Primary Root Cause.
- Assign a Confidence Level.
- Propose specific fixes.
Best Practices
- Be Specific: Don't just say "check the logs." Say "grep for 'Error 500' in
/var/log/nginx/access.log". - Isolate Variables: Change one thing at a time.
- Validate Assumptions: Verify configuration and versions first (e.g., "Task 1: Validate Current Schema").
- Preserve Evidence: Keep the specific trace IDs, log timestamps, or reproduction scripts.
Score
Total Score
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