Étiqueteuse de problèmes GitHub

VérifiéSûr

Analyse les issues GitHub non étiquetées et génère des recommandations d'étiquettes. Examinez les suggestions dans une interface utilisateur, puis soumettez les étiquettes approuvées en lot via gh CLI. Aide à trier rapidement de nombreuses issues sans les lire manuellement.

Spar Skills Guide Bot
DeveloppementIntermédiaire
13002/06/2026
Claude Code
#issue-triage#github-labels#automation#cli

Recommandé pour

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
Quand l'utiliser

Idéal pour les projets avec de nombreuses issues non étiquetées nécessitant un tri cohérent et rapide.

Quand l'éviter

Éviter si l'équipe préfère un étiquetage manuel ou si le dépôt est très petit (moins de quelques dizaines d'issues).

Analyse de sécurité

Sûr
Score qualité95/100

The 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

Tag unlabeled issues for triage
Run the issue labeler on owner/repo to analyze all unlabeled issues and show me the recommendations.
Review and approve labels for a batch
Launch the review UI for the issue labeler recommendations on owner/repo so I can approve each one.
Apply approved labels after review
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:

  1. Title keywords - error, feature, how to, crash, etc.
  2. Body content - stack traces, repro steps, feature requests
  3. Existing patterns - what labels similar issues have
  4. 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 gh CLI authenticated with write access to issues
  • Run gh auth status to verify permissions
  • For large repos, analyze in batches using --limit flag
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