This skill should be used when the user asks to "generate repository metadata", "create catalog-info.yaml", "add repo metadata", "document repository structure", or mentions generating structured metadata for service catalog or architecture documentation.
Content & Writing
85 Stars
2 Forks
Updated Jan 19, 2026, 04:39 AM
Why Use This
This skill provides specialized capabilities for aiskillstore's codebase.
Use Cases
Developing new features in the aiskillstore repository
Refactoring existing code to follow aiskillstore standards
Understanding and working with aiskillstore's codebase structure
---
name: repo-metadata
description: This skill should be used when the user asks to "generate repository metadata", "create catalog-info.yaml", "add repo metadata", "document repository structure", or mentions generating structured metadata for service catalog or architecture documentation.
version: 1.0.0
---
# Repository Metadata
Generate structured `catalog-info.yaml` metadata for repositories using industry-standard conventions (based on Backstage catalog format). This metadata enables cross-repository architecture analysis and service catalog functionality.
## Purpose
Create and maintain `catalog-info.yaml` files that describe a repository's role in the broader architecture. This metadata feeds into architectural views, dependency graphs, and service groupings across the entire organization.
## When to Use
Trigger this skill when:
- User asks to "generate repo metadata" or "create catalog-info.yaml"
- User wants to document a repository for a service catalog
- User needs to prepare a repository for cross-repo architecture analysis
- User mentions "service catalog" or "component metadata"
## Metadata Schema
The `catalog-info.yaml` file follows Backstage conventions with Astrabit-specific extensions:
```yaml
apiVersion: astrabit.io/v1
kind: Component
metadata:
name: service-name # Required: Unique identifier
description: Brief description
tags:
- backend
- user-management
spec:
# Service Classification
type: service # Required: service, gateway, worker, library, frontend, database
category: backend # Broader category
domain: trading # Business domain
owner: platform-team # Team responsible
# Dependencies (Upstream)
dependsOn:
- component: auth-service
type: service
- component: user-db
type: database
# APIs Provided
providesApis:
- name: User API
type: REST
definition: ./openapi.yaml
# APIs Consumed
consumesApis:
- name: Auth API
providedBy: auth-service
# Events Produced
eventProducers:
- name: user-events
type: kafka
topic: user.created
schema: avro
# Events Consumed
eventConsumers:
- name: order-events
type: kafka
topic: order.placed
group: user-service-group
# HTTP Routes (for gateways/services)
routes:
- path: /api/users/*
methods: [GET, POST, PUT, DELETE]
handler: this
- path: /api/auth/*
methods: [POST]
forwardsTo: auth-service
# Infrastructure
runtime: nodejs # nodejs, python, go, java, etc.
framework: nestjs # nestjs, fastapi, spring, etc.
```
## Generation Workflow
### Phase 1: Analyze Repository
Gather information about the repository:
1. **Use existing analysis scripts:**
```bash
python skills/repo-docs/scripts/analyze-repo-structure.py /path/to/repo
python skills/repo-docs/scripts/find-integration-points.py /path/to/repo
```
2. **Read existing documentation:**
- Check for `INTEGRATIONS.md` - contains upstream/downstream relationships
- Check for `ARCHITECTURE.md` - contains service role and dependencies
- Check for `README.md` - contains basic description and tech stack
3. **Detect from code:**
- Language from file extensions and package files
- Framework from dependencies
- Integration points from import patterns
### Phase 2: Generate Metadata
Based on analysis, generate `catalog-info.yaml` with detected values:
| Field | Detection Method |
|-------|------------------|
| `name` | Repo name or `package.json` `name` field |
| `description` | README title/description or generated from code |
| `type` | Inferred from code patterns (gateway has routes, worker has consumers only) |
| `runtime` | From package files (`package.json`, `pyproject.toml`, `go.mod`) |
| `framework` | From dependencies (`nestjs`, `fastapi`, `spring-boot`, etc.) |
| `dependsOn` | From integration point scanning |
| `eventProducers` | From `kafka.producer` or similar patterns |
| `eventConsumers` | From `@KafkaListener`, `@EventListener`, or similar patterns |
| `routes` | From `@Controller`, `@GetMapping`, router definitions |
### Phase 3: Present and Refine
Present the generated metadata to the user in a table format:
```markdown
Generated catalog-info.yaml:
| Field | Value | Source |
|-------|-------|--------|
| name | user-service | repo name |
| type | service | detected: has routes and consumers |
| runtime | nodejs | package.json |
| framework | nestjs | dependencies |
| domain | unknown | ❌ needs input |
| owner | unknown | ❌ needs input |
| dependsOn | auth-service, user-db | integration scan |
```
Prompt user to review and fill in missing fields (marked with ❌).
### Phase 4: Write Metadata File
Write `catalog-info.yaml` to the repository root.
### Phase 5: Update Related Documentation
Offer to update related docs to reference the new metadata file:
- Add link to `catalog-info.yaml` in `README.md`
- Update `INTEGRATIONS.md` to be consistent with metadata
## Service Type Detection
| Type | Indicators |
|------|------------|
| **gateway** | Has `routes` with `forwardsTo`, handles external requests, minimal business logic |
| **service** | Has both `providesApis` and `consumesApis`, business logic |
| **worker** | Only `eventConsumers`, no HTTP routes, background processing |
| **library** | No APIs consumed, only provides, shared utilities |
| **frontend** | `type: frontend` in package.json, has build artifacts |
| **database** | Contains migrations, schemas, no application code |
## Script Usage
Use `scripts/generate-metadata.py` to automate metadata generation:
```bash
# Generate from current directory
python skills/repo-metadata/scripts/generate-metadata.py
# Generate from specific repo
python skills/repo-metadata/scripts/generate-metadata.py /path/to/repo
# Output as JSON for inspection
python skills/repo-metadata/scripts/generate-metadata.py --format json
```
The script:
1. Runs repo structure analysis
2. Scans for integration points
3. Reads existing docs
4. Outputs `catalog-info.yaml` content
## Additional Resources
### Reference Files
- **`references/schema.md`** - Complete catalog-info.yaml schema reference
- **`references/detection-patterns.md`** - Patterns for detecting service characteristics
### Example Templates
- **`examples/catalog-info-template.yaml`** - Full template with all fields
- **`examples/catalog-info-gateway.yaml`** - Example gateway service
- **`examples/catalog-info-worker.yaml`** - Example worker service
- **`examples/catalog-info-library.yaml`** - Example shared library
## Quality Checklist
Before finalizing metadata, verify:
- [ ] `name` is unique across the organization
- [ ] `type` correctly classifies the service
- [ ] `domain` and `owner` are filled (not auto-detected)
- [ ] `dependsOn` lists all upstream dependencies
- [ ] `eventProducers` and `eventConsumers` are complete
- [ ] Routes are documented if this is a gateway/service
- [ ] File is valid YAML
- [ ] File is at repository root (`catalog-info.yaml`)