smart-bug-fix
Smart Bug Fix
Purpose
Systematically debug and fix bugs using root cause analysis, multi-model reasoning, and automated testing.
Specialist Agent
I am a debugging specialist using systematic problem-solving methodology.
Methodology (Root Cause + Fix + Validate Pattern):
- Deep root cause analysis (5 Whys, inverse reasoning)
- Multi-model reasoning for fix approaches
- Codex auto-fix in isolated sandbox
- Comprehensive testing with iteration
- Regression validation
- Performance impact analysis
Models Used:
- Claude (RCA): Deep root cause analysis
- Codex (Fix): Rapid fix implementation
- Claude (Validation): Comprehensive testing
- Gemini (Context): Large codebase analysis if needed
Output: Fixed code with test validation and impact analysis
Input Contract
input:
bug_description: string (required)
context_path: string (directory or file, required)
reproduction_steps: string (optional)
error_logs: string (optional)
depth: enum[shallow, normal, deep] (default: deep)
Output Contract
output:
root_cause: object
identified: string
contributing_factors: array[string]
evidence: array[string]
fix_applied: object
changes: array[file_change]
reasoning: string
alternatives_considered: array[string]
validation: object
tests_passed: boolean
regression_check: boolean
performance_impact: string
confidence: number (0-1)
Execution Flow
#!/bin/bash
set -e
BUG_DESC="$1"
CONTEXT_PATH="$2"
echo "=== Smart Bug Fix Workflow ==="
# PHASE 1: Root Cause Analysis
echo "[1/6] Performing deep root cause analysis..."
npx claude-flow agent-rca "$BUG_DESC" \
--context "$CONTEXT_PATH" \
--depth deep \
--output rca-report.md
# PHASE 2: Context Analysis (if large codebase)
LOC=$(find "$CONTEXT_PATH" -name "*.js" -o -name "*.ts" | xargs wc -l | tail -1 | awk '{print $1}')
if [ "$LOC" -gt 10000 ]; then
echo "[2/6] Large codebase detected - analyzing with Gemini MegaContext..."
gemini "Analyze patterns related to: $BUG_DESC" \
--files "$CONTEXT_PATH" \
--model gemini-2.0-flash \
--output context-analysis.md
else
echo "[2/6] Standard codebase - skipping mega-context analysis"
fi
# PHASE 3: Alternative Solutions (multi-model reasoning)
echo "[3/6] Generating fix approaches..."
# Claude approach (from RCA)
CLAUDE_FIX=$(cat rca-report.md | grep "Solution" -A 10)
# Codex alternative approach
codex --reasoning-mode "Alternative approaches to fix: $BUG_DESC" \
--context rca-report.md \
--output codex-alternatives.md
# PHASE 4: Implement Fix with Codex Auto
echo "[4/6] Implementing fix with Codex Auto..."
codex --full-auto "Fix bug: $BUG_DESC based on RCA findings" \
--context rca-report.md \
--context "$CONTEXT_PATH" \
--sandbox true \
--network-disabled \
--output fix-implementation/
# PHASE 5: Comprehensive Testing with Iteration
echo "[5/6] Testing fix with Codex iteration..."
npx claude-flow functionality-audit fix-implementation/ \
--model codex-auto \
--max-iterations 5 \
--sandbox true \
--regression-check true \
--output test-results.json
# Check if tests passed
TESTS_PASSED=$(cat test-results.json | jq '.all_passed')
if [ "$TESTS_PASSED" != "true" ]; then
echo "⚠️ Tests failed after 5 iterations - escalating to user"
exit 1
fi
# PHASE 6: Performance Impact Analysis
echo "[6/6] Analyzing performance impact..."
npx claude-flow analysis performance-report \
--compare-before-after \
--export performance-impact.json
# Display summary
echo ""
echo "================================================================"
echo "Bug Fix Complete!"
echo "================================================================"
echo ""
echo "Root Cause: $(cat rca-report.md | grep 'Primary Root Cause' -A 2 | tail -1)"
echo "Tests: ✓ All passing"
echo "Regression: ✓ No regressions detected"
echo "Performance Impact: $(cat performance-impact.json | jq '.impact_summary')"
echo ""
echo "Files changed:"
find fix-implementation/ -name "*.js" -o -name "*.ts" | head -10
echo ""
Integration Points
Cascades
- Part of
/bug-triage-workflowcascade - Used by
/production-incident-responsecascade - Invoked by
/fix-bugcommand
Commands
- Uses:
/agent-rca,/gemini-megacontext,/codex-auto,/functionality-audit - Chains with:
/style-audit,/performance-report
Other Skills
- Input to
regression-validatorskill - Used by
incident-responseskill - Integrates with
code-review-assistant
Advanced Features
Automatic RCA Depth Selection
function selectRCADepth(bugDescription, errorLogs) {
if (errorLogs.includes("intermittent") || errorLogs.includes("race condition")) {
return "deep"; // Complex issues need deep analysis
} else if (errorLogs.includes("TypeError") || errorLogs.includes("undefined")) {
return "normal"; // Common errors need normal analysis
} else {
return "shallow"; // Simple issues
}
}
Multi-Model Fix Approach
fix_strategy:
1. Claude RCA → Deep understanding
2. Codex alternatives → Multiple approaches
3. Codex auto-fix → Rapid implementation
4. Claude validation → Comprehensive testing
Codex Iteration Loop
Test → FAIL → Codex fix → Test → FAIL → Codex fix → Test → PASS → Apply
↑ ↓
└────────────────── Max 5 iterations ──────────────────────────────┘
Usage Example
# Fix bug with description
smart-bug-fix "API timeout under load" src/api/
# Fix with reproduction steps
smart-bug-fix "Login fails on Firefox" src/auth/ \
--reproduction-steps "1. Open Firefox 2. Try login 3. See error"
# Fix with error logs
smart-bug-fix "Database connection fails" src/db/ \
--error-logs "logs/error.log"
Failure Modes
- RCA inconclusive: Request more context, run additional diagnostics
- Codex fix fails tests: Try alternative approach, escalate if max iterations reached
- Regression detected: Rollback fix, analyze conflicting requirements
- Performance degradation: Optimize fix, consider alternative approach
More from dnyoussef/ai-chrome-extension
agent-creator
Creates specialized AI agents with optimized system prompts using the official 4-phase SOP methodology from Desktop .claude-flow, combined with evidence-based prompting techniques and Claude Agent SDK implementation. Use this skill when creating production-ready agents for specific domains, workflows, or tasks requiring consistent high-quality performance with deeply embedded domain knowledge.
3github-project-management
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
3prompt-architect
Comprehensive framework for analyzing, creating, and refining prompts for AI systems. Use when creating prompts for Claude, ChatGPT, or other language models, improving existing prompts, or applying evidence-based prompt engineering techniques. Applies structural optimization, self-consistency patterns, and anti-pattern detection to transform prompts into highly effective versions.
3pptx-generation
Enterprise-grade PowerPoint deck generation system using evidence-based prompting techniques, workflow enforcement, and constraint-based design. Use when creating professional presentations (board decks, reports, analyses) requiring consistent visual quality, accessibility compliance, and integration of complex data from multiple sources. Implements html2pptx workflow with spatial layout optimization, validation gates, and multi-chat architecture for 30+ slide decks.
3style-audit
Audits code against CI/CD style rules, quality guidelines, and best practices, then rewrites code to meet standards without breaking functionality. Use this skill after functionality validation to ensure code is not just correct but also maintainable, readable, and production-ready. The skill applies linting rules, enforces naming conventions, improves code organization, and refactors for clarity while preserving all behavioral correctness verified by functionality audits.
3swarm-advanced
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
3