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Zhongwei Li
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commands/quality-analysis/full-analysis.md
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commands/quality-analysis/full-analysis.md
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## Operation: Full Quality Analysis
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Execute comprehensive quality analysis orchestrating all sub-operations to generate complete assessment.
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### Parameters from $ARGUMENTS
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Extract these parameters from `$ARGUMENTS`:
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- **path**: Target path to analyze (required)
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- **context**: Path to validation context JSON file with prior results (optional)
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- **format**: Report output format - markdown|json|html (default: markdown)
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- **output**: Output file path for report (optional)
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### Full Analysis Workflow
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This operation orchestrates all quality-analysis sub-operations to provide a complete quality assessment.
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**1. Load Validation Context**
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```
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IF context parameter provided:
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Read validation results from JSON file
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Extract:
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- Errors count
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- Warnings count
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- Missing fields count
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- Validation layer results
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- Detailed issue list
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ELSE:
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Use default values:
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- errors: 0
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- warnings: 0
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- missing: 0
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```
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**2. Calculate Base Score**
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```
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Read calculate-score.md operation instructions
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Execute scoring with validation results:
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python3 .scripts/scoring-algorithm.py \
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--errors $errors \
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--warnings $warnings \
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--missing $missing \
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--format json
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Capture:
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- Quality score (0-100)
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- Rating (Excellent/Good/Fair/Needs Improvement/Poor)
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- Star rating (⭐⭐⭐⭐⭐)
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- Publication readiness status
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```
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**3. Prioritize All Issues**
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```
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Read prioritize-issues.md operation instructions
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IF context has issues:
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Write issues to temporary JSON file
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Execute issue prioritization:
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bash .scripts/issue-prioritizer.sh $temp_issues_file
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Capture:
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- P0 (Critical) issues with details
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- P1 (Important) issues with details
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- P2 (Recommended) issues with details
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ELSE:
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Skip (no issues to prioritize)
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```
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**4. Generate Improvement Suggestions**
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```
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Read suggest-improvements.md operation instructions
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Generate actionable recommendations:
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Target score: 90 (publication-ready)
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Current score: $calculated_score
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Generate suggestions for:
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- Quick wins (< 30 min, high impact)
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- This week improvements (< 2 hours)
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- Long-term enhancements
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Include:
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- Score impact per suggestion
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- Effort estimates
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- Priority assignment
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- Detailed fix instructions
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```
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**5. Generate Comprehensive Report**
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```
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Read generate-report.md operation instructions
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Execute report generation:
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python3 .scripts/report-generator.py \
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--path $path \
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--format $format \
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--context $aggregated_context \
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--output $output
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Report includes:
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- Executive summary
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- Quality score and rating
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- Validation layer breakdown
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- Prioritized issues (P0/P1/P2)
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- Improvement recommendations
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- Detailed findings
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```
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**6. Aggregate and Display Results**
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```
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Combine all outputs into unified assessment:
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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COMPREHENSIVE QUALITY ANALYSIS
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Target: <path>
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Type: <marketplace|plugin>
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Analyzed: <timestamp>
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QUALITY SCORE: <0-100>/100 <⭐⭐⭐⭐⭐>
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Rating: <rating>
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Publication Ready: <Yes|No|With Changes>
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CRITICAL ISSUES: <P0 count>
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IMPORTANT ISSUES: <P1 count>
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RECOMMENDATIONS: <P2 count>
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[Executive Summary - 2-3 sentences on readiness]
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[If not publication-ready, show top 3 quick wins]
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[Report file location if output specified]
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```
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### Workflow Steps
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1. **Initialize Analysis**
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```
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Validate path exists
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Load validation context if provided
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Set up temporary files for intermediate results
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```
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2. **Execute Operations Sequentially**
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```
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Step 1: Calculate Score
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└─→ Invoke scoring-algorithm.py
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└─→ Store result in context
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Step 2: Prioritize Issues (if issues exist)
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└─→ Invoke issue-prioritizer.sh
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└─→ Store categorized issues in context
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Step 3: Generate Suggestions
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└─→ Analyze score gap
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└─→ Create actionable recommendations
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└─→ Store in context
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Step 4: Generate Report
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└─→ Invoke report-generator.py
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└─→ Aggregate all context data
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└─→ Format in requested format
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└─→ Output to file or stdout
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```
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3. **Present Summary**
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```
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Display high-level results
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Show publication readiness
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Highlight critical blockers (if any)
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Show top quick wins
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Provide next steps
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```
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### Examples
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```bash
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# Full analysis with validation context
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/quality-analysis full-analysis path:. context:"@validation-results.json"
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# Full analysis generating HTML report
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/quality-analysis full-analysis path:. format:html output:quality-report.html
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# Full analysis with JSON output
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/quality-analysis full-analysis path:. context:"@results.json" format:json output:analysis.json
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# Basic full analysis (no prior context)
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/quality-analysis full-analysis path:.
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```
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### Error Handling
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- **Missing path**: Request target path parameter
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- **Invalid context file**: Continue with limited data, show warning
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- **Script execution failures**: Show which operation failed, provide fallback
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- **Output write errors**: Fall back to stdout with warning
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- **No issues found**: Congratulate on perfect quality, skip issue operations
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### Output Format
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**Terminal Output**:
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```
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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COMPREHENSIVE QUALITY ANALYSIS
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Target: /path/to/plugin
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Type: Claude Code Plugin
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Analyzed: 2025-10-13 14:30:00
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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QUALITY SCORE
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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85/100 ⭐⭐⭐⭐ (Good)
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Publication Ready: With Minor Changes
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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ISSUES SUMMARY
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Critical (P0): 0 ✅
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Important (P1): 3 ⚠️
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Recommended (P2): 5 💡
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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EXECUTIVE SUMMARY
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Your plugin is nearly ready for publication! No critical blockers
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found. Address 3 important issues to reach excellent status (90+).
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Quality foundation is solid with good documentation and security.
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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TOP QUICK WINS
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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1. [+10 pts] Add CHANGELOG.md (15 minutes)
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Impact: Improves version tracking
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Fix: Create CHANGELOG.md with version history
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2. [+3 pts] Add 2 more keywords (5 minutes)
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Impact: Better discoverability
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Fix: Add relevant keywords to plugin.json
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3. [+2 pts] Add repository URL (2 minutes)
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Impact: Professional appearance
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Fix: Add repository field to plugin.json
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After Quick Wins: 100/100 ⭐⭐⭐⭐⭐ (Excellent)
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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DETAILED REPORT
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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Full report saved to: quality-report.md
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Next Steps:
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1. Review detailed report for all findings
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2. Implement quick wins (22 minutes total)
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3. Re-run validation to verify improvements
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4. Submit to OpenPlugins marketplace
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Questions? Consult: docs.claude.com/plugins
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```
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### Integration Notes
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This operation is the **primary entry point** for complete quality assessment.
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**Invoked by**:
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- `validation-orchestrator` after comprehensive validation
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- `marketplace-validator` agent for submission readiness
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- Direct user invocation for full assessment
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**Orchestrates**:
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- `calculate-score.md` - Quality scoring
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- `prioritize-issues.md` - Issue categorization
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- `suggest-improvements.md` - Actionable recommendations
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- `generate-report.md` - Comprehensive reporting
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**Data Flow**:
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```
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Validation Results
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↓
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Calculate Score → score, rating, stars
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↓
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Prioritize Issues → P0/P1/P2 categorization
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↓
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Suggest Improvements → actionable recommendations
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↓
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Generate Report → formatted comprehensive report
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↓
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Display Summary → user-friendly terminal output
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```
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### Performance
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- **Execution Time**: 2-5 seconds (depending on issue count)
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- **I/O Operations**: Minimal (uses temporary files for large datasets)
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- **Memory Usage**: Low (streaming JSON processing)
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- **Parallelization**: Sequential (each step depends on previous)
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### Quality Assurance
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**Validation Steps**:
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1. Verify all scripts are executable
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2. Check Python 3.6+ availability
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3. Validate JSON context format
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4. Verify write permissions for output
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5. Ensure scoring algorithm consistency
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**Testing**:
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```bash
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# Test with perfect plugin
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/quality-analysis full-analysis path:./test-fixtures/perfect-plugin
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# Test with issues
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/quality-analysis full-analysis path:./test-fixtures/needs-work
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# Test report formats
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/quality-analysis full-analysis path:. format:json
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/quality-analysis full-analysis path:. format:html
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/quality-analysis full-analysis path:. format:markdown
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```
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**Request**: $ARGUMENTS
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Reference in New Issue
Block a user