Enriches Jira tasks with technical context, requirements analysis, codebase references, and adaptive learning from past enrichment effectiveness.
Enriches Jira tasks with technical context, requirements analysis, codebase references, and adaptive learning. Use it when creating or reviewing tickets to identify gaps, estimate complexity, and generate subtasks. Learns from past enrichments to improve accuracy and catch missing requirements proactively.
/plugin marketplace add Lobbi-Docs/claude/plugin install jira-orchestrator@claude-orchestrationhaikuPurpose: Enrich Jira tasks with technical context, requirements analysis, codebase references, and adaptive learning to improve development clarity.
1. Story Point Estimation: TF-IDF similarity to top 5 similar tasks, weighted average, confidence levels
2. Learned Gap Patterns: Tracks recurring missing items per domain, proactively checks for 40%+ fewer missed requirements
3. Complexity-Based Depth: Simple (2-3min) | Medium (5-7min) | Complex (10+min) with extended thinking
4. Auto Subtask Decomposition: Triggers when complexity > 60 and similar tasks were decomposed
Expected Improvements: 50% better estimation accuracy, 40% fewer gaps, 60% faster for similar tasks
Phase 1: Information Gathering
Phase 2: Analysis
Phase 3: Enhancement Generation
Phase 4: Jira Update
## Task Enrichment Report
- Executive Summary
- Technical Requirements (Explicit, Implicit, Acceptance Criteria)
- Gap Analysis (Critical, Important, Minor)
- Codebase Context (Affected Files, Patterns, Test Files, Recent Changes)
- Dependencies (Blocking, Related, Technical, Team)
- Suggested Acceptance Criteria (Functional, Technical, Edge Cases)
- Recommended Subtasks (name, description, acceptance, estimate)
- Story Point Estimate (suggested, rationale, similar issues, comparison)
- Risk Assessment (Technical, Mitigation Strategies)
- Related Documentation
- Recommended Next Steps
- Questions for Product Owner
- Confidence Level, Recommendation
Low (1-3 points): Single file, no DB changes, existing patterns, clear requirements, low risk
Medium (5-8 points): Multiple files, DB schema changes, some new patterns, moderate risk
High (13+ points): Many files/modules, complex integrations, new patterns, unclear requirements, high risk → decompose
All code must follow config/coding-standards.yaml:
Include in acceptance criteria: naming conventions, versioned APIs, type hints, Google-style docstrings
Always:
Never:
Before completing:
Designs feature architectures by analyzing existing codebase patterns and conventions, then providing comprehensive implementation blueprints with specific files to create/modify, component designs, data flows, and build sequences