Registry Update

registry.update

Purpose

The registry.update skill centralizes all changes to /registry/skills.json. Instead of each skill writing to the registry directly, they call this skill to ensure consistency, policy enforcement, and audit logging.

Usage

Basic Usage

python skills/registry.update/registry_update.py <path_to_skill.yaml>

Arguments

Behavior

1. Policy Enforcement: Runs policy.enforce skill (if available) to validate the manifest against organizational policies
2. Load Manifest: Reads and parses the skill manifest YAML
3. Update Registry: Adds or updates the skill entry in /registry/skills.json
4. Thread-Safe: Uses file locking to ensure safe concurrent updates
5. Audit Trail: Records all registry modifications

Outputs

Success Response

{
  "ok": true,
  "status": "success",
  "errors": [],
  "path": "skills/api.validate/skill.yaml",
  "details": {
    "skill_name": "api.validate",
    "version": "0.1.0",
    "action": "updated",
    "registry_file": "/registry/skills.json",
    "policy_enforced": true
  }
}

Failure Response (Policy Violation)

{
  "ok": false,
  "status": "failed",
  "errors": [
    "Policy violations detected:",
    "  - Skill name must follow domain.action pattern",
    "  - Description must be at least 20 characters"
  ],
  "path": "skills/bad-skill/skill.yaml"
}

Policy Enforcement

Before updating the registry, this skill runs policy.enforce (if available) to validate:

• Naming Conventions: Skills follow domain.action pattern
• Required Fields: All mandatory fields present and valid
• Dependencies: Referenced dependencies exist in registry
• Version Conflicts: No version conflicts with existing skills

If policy enforcement fails, the registry update is blocked and errors are returned.

Thread Safety

The skill uses file locking via safe_update_json to ensure:

• Multiple concurrent updates don't corrupt the registry
• Atomic read-modify-write operations
• Proper error handling and rollback on failure

Integration

With skill.define

skill.define automatically calls registry.update after validation:

# This validates AND updates registry
python skills/skill.define/skill_define.py skills/my.skill/skill.yaml

With skill.create

skill.create scaffolds a skill and registers it:

python skills/skill.create/skill_create.py my.skill "Does something"
# Internally calls skill.define which calls registry.update

Direct Usage

For manual registry updates:

python skills/registry.update/registry_update.py skills/custom.skill/skill.yaml

Registry Structure

The /registry/skills.json file has this structure:

{
  "registry_version": "1.0.0",
  "generated_at": "2025-10-23T12:00:00Z",
  "skills": [
    {
      "name": "api.validate",
      "version": "0.1.0",
      "description": "Validate OpenAPI specifications",
      "inputs": ["spec_path", "guideline_set"],
      "outputs": ["validation_report", "valid"],
      "dependencies": ["context.schema"],
      "status": "active",
      "entrypoints": [...],
      "tags": ["api", "validation"]
    }
  ]
}

Files Modified

• Registry: /registry/skills.json – Updated with skill entry
• Logs: Registry updates logged to Betty's logging system

Exit Codes

• 0: Success (registry updated)
• 1: Failure (policy violation or update failed)

Common Errors

Best Practices

1. Use via skill.define: Don't call directly unless needed
2. Policy Compliance: Ensure skills pass policy checks before registration
3. Version Control: Keep registry changes in git for full history
4. Atomic Updates: The skill handles thread safety automatically

See Also

• skill.define – Validates manifests before calling registry.update (skill.define SKILL.md)
• policy.enforce – Enforces organizational policies (if configured)
• Betty Architecture – Five-Layer Model

Status

Active – Production-ready, core infrastructure skill

Version History

• 0.1.0 (Oct 2025) – Initial implementation with policy enforcement and thread-safe updates