parse-ai-analysis
Parse GitHub AI analysis comment sections for architectural alignment, technical feasibility, implementation suggestions, and testing strategy
$ 安裝
git clone https://github.com/BerryKuipers/claude-code-toolkit /tmp/claude-code-toolkit && cp -r /tmp/claude-code-toolkit/.claude/skills/github-integration/parse-ai-analysis ~/.claude/skills/claude-code-toolkit// tip: Run this command in your terminal to install the skill
SKILL.md
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-analysisskill - 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
- Always validate input - Check for expected format
- Handle missing sections - AI analysis may be incomplete
- Extract issue numbers - Parse dependencies for workflow planning
- Preserve raw text - Include original for reference
- 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
Repository

BerryKuipers
Author
BerryKuipers/claude-code-toolkit/.claude/skills/github-integration/parse-ai-analysis
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Updated3d ago
Added1w ago