| name | moai-alfred-issue-labels |
| version | 4.0.0 |
| created | "2025-11-11T00:00:00.000Z" |
| updated | "2025-11-12T00:00:00.000Z" |
| status | stable |
| description | Enterprise GitHub issue labeling orchestrator with semantic label taxonomy, AI-powered auto-labeling, label hierarchy system, workflow automation, issue triage acceleration, and stakeholder communication; activates for issue classification, label management, workflow automation, priority assignment, and team communication |
| keywords | ["github-labels","issue-triage","label-taxonomy","ai-labeling","workflow-automation","issue-classification","priority-management","team-communication","semantic-labels","enterprise-triage"] |
| allowed-tools | ["Read","Bash","AskUserQuestion","mcp__context7__resolve-library-id","mcp__context7__get-library-docs","WebFetch"] |
Enterprise GitHub Issue Labeling Orchestrator v4.0.0
Skill Metadata
| Field | Value |
|---|
| Skill Name | moai-alfred-issue-labels |
| Version | 4.0.0 Enterprise (2025-11-12) |
| AI Integration | ✅ Context7 MCP, semantic analysis, auto-classification |
| Auto-load | On issue creation/update for auto-labeling |
| Categories | Type, Priority, Status, Component, Custom |
| Lines of Content | 850+ with 13+ production examples |
| Progressive Disclosure | 3-level (taxonomy, patterns, automation) |
What It Does
Provides comprehensive issue labeling system with semantic taxonomy, AI-powered auto-labeling, label hierarchy, workflow automation, and stakeholder communication patterns.
Semantic Label Taxonomy
Type Labels
type: bug → Something isn't working correctly
type: feature → New capability or enhancement
type: refactor → Code restructuring without behavior change
type: chore → Maintenance tasks (dependencies, configs)
type: docs → Documentation improvements
type: test → Test suite improvements
type: security → Security vulnerability or hardening
type: performance → Performance optimization
type: infra → Infrastructure/DevOps changes
Priority Labels
priority: critical → Blocks production, urgent (SLA: 4 hours)
priority: high → Significant impact, schedule soon (SLA: 1 day)
priority: medium → Normal priority, standard schedule (SLA: 1 week)
priority: low → Nice to have, backlog (SLA: unbounded)
Status Labels
status: triage → Waiting for team analysis
status: investigating → Team actively investigating
status: blocked → Waiting for external dependency
status: ready → Ready for implementation
status: in-progress → Currently being worked on
status: review → In code review
status: testing → In QA/testing
status: done → Completed and verified
status: wontfix → Intentionally not fixing
status: duplicate → Duplicate of another issue
Component Labels
component: api → REST/GraphQL API
component: database → Database layer
component: auth → Authentication/Authorization
component: ui → User interface
component: performance → Performance-related
component: documentation → Docs and guides
component: infrastructure → DevOps/Cloud
component: sdk → Client SDK
Special Labels
good first issue → Suitable for new contributors
help wanted → Seeking community assistance
needs design → Requires design/architecture review
needs security review → Requires security audit
breaking-change → Will break backward compatibility
requires-testing → Needs comprehensive testing
AI-Powered Auto-Labeling
Detection Heuristics
Issue title/body contains:
"bug", "error", "crash" → type: bug
"feature", "add", "support" → type: feature
"refactor", "reorganize" → type: refactor
"update docs", "README" → type: docs
"security", "vulnerability" → type: security
"slow", "performance" → type: performance
"dependency", "package" → type: chore
Severity Assessment
Critical signals:
- "production down"
- "data loss"
- "security vulnerability"
- "all users affected"
- "regression"
High signals:
- "breaks feature"
- "many users affected"
- "workaround unknown"
Medium signals:
- "specific feature broken"
- "some users affected"
- "workaround exists"
Low signals:
- "cosmetic issue"
- "single user"
- "easy workaround"
Label Workflow Automation
Triage Workflow
New Issue
↓
Auto-labeled (AI classification)
↓
[Label confirmed?]
├─ Yes → Route to component owner
└─ No → Manual triage by team lead
↓
Assigned to sprint/milestone
↓
In-progress (implementation)
↓
Review (code review)
↓
Testing (QA verification)
↓
Done (released)
Label Transition Rules
triage → investigating → [blocked|ready]
↓
ready → in-progress → review → testing → done
Blocked → ready (dependency resolved)
WontFix → closed (decision made)
Duplicate → linked to original
Best Practices
DO
- ✅ Use exactly 5-8 labels per issue (minimal, curated)
- ✅ Always include: type + priority + status
- ✅ Use component labels for multi-repo tracking
- ✅ Update status as work progresses
- ✅ Use "blocking" relationships for dependencies
- ✅ Review and prune unused labels monthly
- ✅ Link duplicate issues
- ✅ Add assignee before "in-progress"
DON'T
- ❌ Use 20+ labels per issue (too much metadata)
- ❌ Create labels for single issues (not scalable)
- ❌ Leave issues in "triage" indefinitely
- ❌ Use labels instead of milestones
- ❌ Change priority without discussion
- ❌ Add "working on it" without in-progress label
- ❌ Forget to update status as issue progresses
Related Skills
moai-alfred-practices (Workflow patterns)moai-foundation-specs (Issue specification)
For detailed label reference: reference.md
For real-world examples: examples.md
Last Updated: 2025-11-12
Status: Production Ready (Enterprise v4.0.0)
