Notre avis
Analyse les issues GitHub non labellisées et propose des recommandations d'étiquettes via un workflow interactif de validation par lots.
Points forts
- Automatise le tri des issues sans lecture manuelle
- Interface de révision avec explications pour chaque recommandation
- Validation explicite avant application (sûreté)
- Utilise l'IA pour analyser le contenu et le contexte du dépôt
Limites
- Nécessite l'outil gh CLI avec accès write aux issues
- Ne fonctionne que sur des dépôts GitHub
- Peut nécessiter un lotissement pour les grands dépôts
Idéal pour les projets avec de nombreuses issues non étiquetées nécessitant un tri cohérent et rapide.
Éviter si l'équipe préfère un étiquetage manuel ou si le dépôt est très petit (moins de quelques dizaines d'issues).
Analyse de sécurité
SûrThe skill uses gh and bash to analyze issues and apply labels only after explicit approval, with dry-run and audit logging. No destructive, exfiltrating, or obfuscated commands are present.
Aucun point d'attention détecté
Exemples
Run the issue labeler on owner/repo to analyze all unlabeled issues and show me the recommendations.Launch the review UI for the issue labeler recommendations on owner/repo so I can approve each one.Apply the approved labels from the issue labeler recommendations on owner/repo.name: issue-labeler description: Analyze unlabeled GitHub issues and generate label recommendations for review. Supports batch submission after approval. license: MIT compatibility: Requires gh CLI authenticated with repo access. metadata: author: patrick version: "1.0" allowed-tools: bash gh jq
Issue Labeler
Generate label recommendations for unlabeled GitHub issues, review them, then submit in batch.
When to Use
- Repository has many unlabeled or poorly labeled issues
- You want to triage issues without manually reading each one
- Need consistent labeling based on issue content
Workflow
Step 1: Generate Recommendations
# Fetch unlabeled issues and analyze them
./scripts/analyze.sh owner/repo
This creates recommendations.json with suggested labels for each issue.
Step 2: Review Recommendations
# Launch the review UI
./scripts/serve.sh
The UI shows:
- Issue title and preview
- Current labels (if any)
- Recommended labels with confidence
- Checkbox to approve/reject each recommendation
Step 3: Submit Approved Labels
After reviewing in the UI, export approved recommendations and run:
# Apply approved labels
./scripts/apply.sh recommendations-approved.json
Or use the "Submit All" button in the UI to apply via gh CLI.
Label Categories
The analyzer suggests labels from these categories:
| Category | Labels |
|----------|--------|
| Type | bug, enhancement, question, documentation |
| Priority | priority-1, priority-2, priority-3 |
| Status | triage, needs-info, investigating, confirmed |
| Area | (detected from content: auth, cli, api, ui, etc.) |
How Analysis Works
For each unlabeled issue, the LLM analyzes:
- Title keywords - error, feature, how to, crash, etc.
- Body content - stack traces, repro steps, feature requests
- Existing patterns - what labels similar issues have
- Repository context - available labels in the repo
Files
issue-labeler/
├── SKILL.md # This file
├── review.html # Review UI for recommendations
├── scripts/
│ ├── analyze.sh # Fetch and generate recommendations
│ ├── apply.sh # Apply approved labels
│ └── serve.sh # Launch review UI
├── recommendations.json # Generated recommendations (git-ignored)
└── approved.json # Approved recommendations (git-ignored)
Example Recommendation
{
"number": 123,
"title": "App crashes when clicking submit",
"current_labels": [],
"recommended_labels": ["bug", "priority-2", "needs-info"],
"confidence": 0.85,
"reasoning": "Title indicates crash (bug). No repro steps provided (needs-info). User-facing issue (priority-2).",
"approved": null
}
Safety
- No labels applied without explicit approval
- Review UI shows reasoning for each recommendation
- Dry-run mode available:
./scripts/apply.sh --dry-run - All actions logged for audit
Notes
- Requires
ghCLI authenticated with write access to issues - Run
gh auth statusto verify permissions - For large repos, analyze in batches using
--limitflag
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