curator-repo-learn

Curator Repo-Learn Skill (v3.1.0)

Single Repository Pattern Extraction - Learn from a specific GitHub repository.

Role & Priorities

Priorities (ordered): accuracy → relevance → speed → coverage

Scope: Clone repository, analyze structure, extract patterns, update procedural memory.

Agent Teams Integration (v2.88)

Optimal Scenario: B (Custom Subagents)

Why Scenario B for Repo-Learn

• Independent operation: Single repo, single task
• High specialization need: Pattern recognition requires expertise
• Low coordination need: No multi-stage pipeline
• Efficient execution: Direct spawn, no team overhead

Scenario Analysis

Workflow (Scenario B)

# Direct Subagent Spawn
Task(subagent_type="ralph-researcher", prompt="""
Analyze repository ${REPO_URL}:

1. Clone repository (shallow)
2. Detect domain and language
3. Scan for:
   - Function/method patterns
   - Class/interface definitions
   - Configuration patterns
   - Error handling patterns
   - Testing patterns
4. Extract rules with:
   - domain: <detected>
   - category: <detected>
   - confidence: 0.75-0.95
   - source_repo: ${REPO_URL}
   - source_file: <path>
5. Update .claude/rules/learned/ (MemPalace taxonomy)
6. Create manifest with files[] array

Return: patterns extracted, rules added, domain detected
""")

Usage

Basic Usage

/repo-learn https://github.com/owner/repo

With Domain Override

/repo-learn https://github.com/nestjs/nest --domain backend

With Language Hint

/repo-learn https://github.com/vercel/next.js --lang typescript

Process Flow

┌─────────────────────────────────────────────────────────────┐
│                    REPO-LEARN PIPELINE                       │
├─────────────────────────────────────────────────────────────┤
│                                                              │
│  1. VALIDATE URL                                             │
│     ├── Check GitHub format                                  │
│     └── Verify repository exists                             │
│                                                              │
│  2. CLONE REPOSITORY                                         │
│     ├── Shallow clone (--depth 1)                           │
│     └── Store in .claude/corpus/learning/                  │
│                                                              │
│  3. DETECT METADATA                                          │
│     ├── Domain (backend, frontend, etc.)                    │
│     ├── Language (typescript, python, etc.)                 │
│     └── Framework indicators                                  │
│                                                              │
│  4. SCAN FILES                                               │
│     ├── Source files (*.ts, *.py, etc.)                     │
│     ├── Configuration files                                  │
│     └── Documentation files                                  │
│                                                              │
│  5. EXTRACT PATTERNS                                         │
│     ├── Function signatures                                  │
│     ├── Class structures                                     │
│     ├── Import patterns                                      │
│     ├── Error handling patterns                              │
│     └── Configuration patterns                               │
│                                                              │
│  6. CREATE RULES                                             │
│     ├── rule_id: unique identifier                          │
│     ├── domain: detected or specified                       │
│     ├── category: sub-domain                                 │
│     ├── confidence: 0.75-0.95                               │
│     ├── source_repo: repository URL                         │
│     ├── source_file: file path                              │
│     └── behavior: pattern description                       │
│                                                              │
│  7. UPDATE PROCEDURAL MEMORY                                 │
│     ├── Backup existing rules.json                          │
│     ├── Merge new rules (unique_by rule_id)                 │
│     └── Update manifest                                      │
│                                                              │
│  8. CREATE MANIFEST (GAP-C01 FIX)                            │
│     ├── files[]: processed file list                        │
│     ├── patterns_extracted: count                           │
│     ├── detected_domain: domain                             │
│     └── detected_language: language                         │
│                                                              │
└─────────────────────────────────────────────────────────────┘

Domain Detection (GAP-C02 FIX)

Automatic domain detection from repository content:

# Domain Keywords
backend:    api, server, rest, graphql, controller, service
frontend:   react, vue, angular, component, hook, state
database:   sql, query, schema, migration, orm, prisma
security:   auth, jwt, token, encrypt, hash, csrf
testing:    test, spec, jest, vitest, mock, coverage
devops:     docker, kubernetes, ci, deploy, pipeline
hooks:      hook, lifecycle, callback, trigger, event
general:    config, util, helper, common, shared

Output Example

{
  "repository": "https://github.com/nestjs/nest",
  "learned_at": "2026-02-14T22:00:00Z",
  "detected_domain": "backend",
  "detected_language": "typescript",
  "files": [
    "packages/core/nest-application.ts",
    "packages/core/nest-factory.ts",
    "packages/common/services/logger.service.ts"
  ],
  "patterns_extracted": 12,
  "rules_added": [
    {
      "rule_id": "rule-backend-1739566800-abc123",
      "domain": "backend",
      "category": "backend",
      "source_repo": "https://github.com/nestjs/nest",
      "source_file": "packages/core/nest-application.ts",
      "behavior": "Classes: class NestApplication. Functions: async initialize, async dispose.",
      "confidence": 0.85
    }
  ]
}

Error Handling

Integration with Curator Pipeline

# Quick learning without full pipeline
/curator quick --repo owner/repo

# Full pipeline for comprehensive learning
/curator full --type backend --lang typescript

# Single repo learning (this skill)
/repo-learn https://github.com/owner/repo

Related Skills

• /curator - Full pipeline (Scenario C)
• /smart-fork - Pattern extraction and forking
• /research - Repository research

Files

Action Reporting (v2.93.0)

Esta skill genera reportes automáticos completos para trazabilidad:

Reporte Automático

Cuando esta skill completa, se genera automáticamente:

1. En la conversación de Claude: Resultados visibles
2. En el repositorio: docs/actions/curator-repo-learn/{timestamp}.md
3. Metadatos JSON: .claude/metadata/actions/curator-repo-learn/{timestamp}.json

Contenido del Reporte

Cada reporte incluye:

• ✅ Summary: Descripción de la tarea ejecutada
• ✅ Execution Details: Duración, iteraciones, archivos modificados
• ✅ Results: Errores encontrados, recomendaciones
• ✅ Next Steps: Próximas acciones sugeridas

Ver Reportes Anteriores

# Listar todos los reportes de esta skill
ls -lt docs/actions/curator-repo-learn/

# Ver el reporte más reciente
cat $(ls -t docs/actions/curator-repo-learn/*.md | head -1)

# Buscar reportes fallidos
grep -l "Status: FAILED" docs/actions/curator-repo-learn/*.md

Generación Manual (Opcional)

source .claude/lib/action-report-lib.sh
start_action_report "curator-repo-learn" "Task description"
# ... ejecución ...
complete_action_report "success" "Summary" "Recommendations"

Referencias del Sistema

• Action Reports System - Documentación completa

• action-report-lib.sh - Librería helper

• action-report-generator.sh - Generador

• Learning System Audit

• Learning System Scenarios