parse-ai-analysis

name	parse-ai-analysis
description	Parse GitHub AI analysis comment sections for architectural alignment, technical feasibility, implementation suggestions, and testing strategy

Parse AI Analysis

Purpose

Extract structured data from GitHub AI issue analysis comments generated by github-actions bot for use in architecture planning and implementation.

When to Use

• After fetching issue with fetch-github-issue-analysis skill
• When AI analysis found in issue comments
• During conductor Phase 1 (architecture planning)
• When extracting specific sections for delegation

AI Analysis Format

The AI analysis comment contains these sections:

# AI Issue Analysis

## Architectural Alignment
[How this issue aligns with current architecture]

## Technical Feasibility
[Assessment of implementation difficulty and approach]

## Implementation Suggestions
[Specific implementation recommendations]

## Files/Components Affected
[List of files that will need changes]

## Testing Strategy
[Recommended testing approach]

## Dependencies
[Related issues or features]

## Estimated Complexity
[Simple/Medium/Complex assessment]

Instructions

Step 1: Validate Input

AI_ANALYSIS=$1  # Full AI analysis comment text

if [ -z "$AI_ANALYSIS" ]; then
  echo "❌ Error: No AI analysis provided"
  exit 1
fi

# Check if contains expected heading
if ! echo "$AI_ANALYSIS" | grep -q "AI Issue Analysis"; then
  echo "⚠️ Warning: Unexpected format - may not be AI analysis"
fi

Step 2: Extract Architectural Alignment

# Extract section between "## Architectural Alignment" and next "##"
ARCH_ALIGNMENT=$(echo "$AI_ANALYSIS" | \
  sed -n '/## Architectural Alignment/,/^## /p' | \
  sed '$d' | \
  sed '1d' | \
  sed '/^$/d')

if [ -n "$ARCH_ALIGNMENT" ]; then
  echo "✅ Architectural Alignment: $(echo "$ARCH_ALIGNMENT" | wc -l) lines"
else
  echo "⚠️ Architectural Alignment section not found"
  ARCH_ALIGNMENT="Not provided"
fi

Step 3: Extract Technical Feasibility

TECH_FEASIBILITY=$(echo "$AI_ANALYSIS" | \
  sed -n '/## Technical Feasibility/,/^## /p' | \
  sed '$d' | \
  sed '1d' | \
  sed '/^$/d')

if [ -n "$TECH_FEASIBILITY" ]; then
  echo "✅ Technical Feasibility: $(echo "$TECH_FEASIBILITY" | wc -l) lines"
else
  TECH_FEASIBILITY="Not provided"
fi

Step 4: Extract Implementation Suggestions

IMPL_SUGGESTIONS=$(echo "$AI_ANALYSIS" | \
  sed -n '/## Implementation Suggestions/,/^## /p' | \
  sed '$d' | \
  sed '1d' | \
  sed '/^$/d')

if [ -n "$IMPL_SUGGESTIONS" ]; then
  echo "✅ Implementation Suggestions: $(echo "$IMPL_SUGGESTIONS" | wc -l) lines"
else
  IMPL_SUGGESTIONS="Not provided"
fi

Step 5: Extract Files/Components Affected

FILES_AFFECTED=$(echo "$AI_ANALYSIS" | \
  sed -n '/## Files\/Components/,/^## /p' | \
  sed '$d' | \
  sed '1d' | \
  sed '/^$/d')

# Convert to array
if [ -n "$FILES_AFFECTED" ]; then
  FILES_ARRAY=$(echo "$FILES_AFFECTED" | \
    grep -oP '`[^`]+`' | \
    sed 's/`//g' | \
    jq -R -s -c 'split("\n") | map(select(length > 0))')

  echo "✅ Files Affected: $(echo "$FILES_ARRAY" | jq '. | length') files"
else
  FILES_ARRAY="[]"
fi

Step 6: Extract Testing Strategy

TESTING_STRATEGY=$(echo "$AI_ANALYSIS" | \
  sed -n '/## Testing Strategy/,/^## /p' | \
  sed '$d' | \
  sed '1d' | \
  sed '/^$/d')

if [ -n "$TESTING_STRATEGY" ]; then
  echo "✅ Testing Strategy: $(echo "$TESTING_STRATEGY" | wc -l) lines"
else
  TESTING_STRATEGY="Not provided"
fi

Step 7: Extract Dependencies

DEPENDENCIES=$(echo "$AI_ANALYSIS" | \
  sed -n '/## Dependencies/,/^## /p' | \
  sed '$d' | \
  sed '1d' | \
  sed '/^$/d')

# Extract issue numbers
if [ -n "$DEPENDENCIES" ]; then
  DEPS_ARRAY=$(echo "$DEPENDENCIES" | \
    grep -oP '#\d+' | \
    sed 's/#//' | \
    jq -R -s -c 'split("\n") | map(select(length > 0) | tonumber)')
else
  DEPS_ARRAY="[]"
fi

Step 8: Extract Complexity

COMPLEXITY=$(echo "$AI_ANALYSIS" | \
  sed -n '/## Estimated Complexity/,/^## /p' | \
  sed '$d' | \
  sed '1d' | \
  sed '/^$/d' | \
  grep -oP '(Simple|Medium|Complex)' | \
  head -1)

if [ -z "$COMPLEXITY" ]; then
  COMPLEXITY="Unknown"
fi

echo "✅ Complexity: $COMPLEXITY"

Step 9: Return Structured Output

{
  "status": "success",
  "sections": {
    "architecturalAlignment": "$ARCH_ALIGNMENT",
    "technicalFeasibility": "$TECH_FEASIBILITY",
    "implementationSuggestions": "$IMPL_SUGGESTIONS",
    "filesAffected": $FILES_ARRAY,
    "testingStrategy": "$TESTING_STRATEGY",
    "dependencies": $DEPS_ARRAY,
    "complexity": "$COMPLEXITY"
  },
  "raw": "$AI_ANALYSIS"
}

Output Format

Complete Parse

{
  "status": "success",
  "sections": {
    "architecturalAlignment": "Aligns with component-based architecture. Requires state management updates.",
    "technicalFeasibility": "High - uses existing React patterns. No new dependencies required.",
    "implementationSuggestions": "1. Add darkMode to WorldContext\n2. Create DarkModeToggle component\n3. Persist to localStorage",
    "filesAffected": [
      "src/context/WorldContext.tsx",
      "src/components/Settings/DarkModeToggle.tsx",
      "src/styles/theme.ts"
    ],
    "testingStrategy": "Unit tests for toggle component, integration tests for persistence, visual regression tests",
    "dependencies": [135, 140],
    "complexity": "Medium"
  }
}

Partial Data

{
  "status": "partial",
  "sections": {
    "architecturalAlignment": "Provided",
    "technicalFeasibility": "Not provided",
    "implementationSuggestions": "Provided",
    "filesAffected": [],
    "testingStrategy": "Not provided",
    "dependencies": [],
    "complexity": "Unknown"
  },
  "warnings": ["Technical Feasibility section missing", "No files specified"]
}

Integration with Conductor

Used in conductor Phase 1 after fetching issue:

### Phase 1: Issue Discovery and Planning

**Step 1: Issue Selection**

Use `fetch-github-issue-analysis` to get issue + AI analysis

If AI analysis found:
  Use `parse-ai-analysis` skill to extract structured sections:
  - Input: AI analysis comment text
  - Output: Structured sections

  **Provide to architect agent**:
  - Architectural alignment insights
  - Technical feasibility assessment
  - Suggested implementation approach

  **Provide to implementation agent**:
  - Implementation suggestions
  - Files that need changes

  **Provide to test planning**:
  - Testing strategy recommendations

Related Skills

• fetch-github-issue-analysis - Get AI analysis from GitHub
• Architect agent - Uses architectural alignment data
• Implementation agent - Uses implementation suggestions

Error Handling

Missing Sections

{
  "status": "warning",
  "message": "Some sections missing",
  "missingSections": ["Technical Feasibility", "Testing Strategy"]
}

Invalid Format

{
  "status": "error",
  "error": "AI analysis format unrecognized",
  "suggestion": "Manually review comment"
}

Best Practices

1. Always validate input - Check for expected format
2. Handle missing sections - AI analysis may be incomplete
3. Extract issue numbers - Parse dependencies for workflow planning
4. Preserve raw text - Include original for reference
5. Return structured data - JSON for easy consumption

Notes

• AI analysis format may vary by issue type
• Not all sections may be present
• Section headings must match exactly for parsing
• Use raw text as fallback if parsing fails