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

Criterion	Weight	Score	Rationale
Coordination Need	25%	2/10	Independent operation
Specialization Need	25%	9/10	Requires pattern recognition
Quality Gate Need	20%	6/10	Moderate validation needed
Tool Restriction Need	15%	3/10	Standard tools sufficient
Scalability	15%	2/10	Single repo focus
Total	100%	5.2/10	Scenario B optimal

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

Error	Recovery
Invalid URL	Show usage, exit
Repository not found	Suggest alternatives, exit
Clone failure	Retry with different depth
No patterns found	Log warning, return empty
Rules merge failure	Restore from backup

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

File	Purpose
.claude/scripts/curator-learn.sh	Pattern extraction (GAP-C01, GAP-C02 fixed)
.claude/scripts/curator-ingest.sh	Repository cloning
.claude/scripts/backfill-domains.sh	Domain backfill for existing rules
.claude/rules/learned/	Procedural memory (MemPalace taxonomy)

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