tools-only API Operations
Production deployment, CI/CD integration, security hardening, monitoring, and troubleshooting for the Skill Scanner API server. For endpoint documentation, see API Endpoints Detail.
CI/CD Integration
GitHub Actions
name: Scan Skills via API
on: [push]
jobs:
scan:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Start API Server
run: |
pip install cisco-ai-skill-scanner
skill-scanner-api &
sleep 5
- name: Scan Skills
run: |
curl -X POST http://localhost:8000/scan-batch \
-H "Content-Type: application/json" \
-d '{"skills_directory": "./skills"}' \
> scan_id.json
SCAN_ID=$(jq -r '.scan_id' scan_id.json)
# Poll for results
while true; do
STATUS=$(curl http://localhost:8000/scan-batch/$SCAN_ID | jq -r '.status')
if [ "$STATUS" = "completed" ]; then
break
fi
sleep 10
done
# Get results
curl http://localhost:8000/scan-batch/$SCAN_ID > results.json
# Check for critical findings
CRITICAL=$(jq '.result.summary.findings_by_severity.critical' results.json)
if [ "$CRITICAL" -gt 0 ]; then
echo "Critical findings detected!"
exit 1
fi
Docker
FROM python:3.11-slim
WORKDIR /app
COPY pyproject.toml .
COPY skill_scanner/ ./skill_scanner/
RUN pip install . && \
adduser --disabled-password --no-create-home appuser
USER appuser
EXPOSE 8000
CMD ["skill-scanner-api", "--host", "0.0.0.0", "--port", "8000"]
# Build and run
docker build -t skill-scanner-api .
docker run -p 8000:8000 \
-e SKILL_SCANNER_LLM_API_KEY=your_key \
-e SKILL_SCANNER_LLM_MODEL=anthropic/claude-sonnet-4-20250514 \
skill-scanner-api
Security
Authentication
Add API key authentication:
import os
from fastapi import Security, HTTPException
from fastapi.security import APIKeyHeader
API_KEY_NAME = "X-API-Key"
api_key_header = APIKeyHeader(name=API_KEY_NAME)
async def get_api_key(api_key: str = Security(api_key_header)):
if api_key != os.getenv("API_KEY"):
raise HTTPException(status_code=403, detail="Invalid API Key")
return api_key
@app.post("/scan")
async def scan_skill(request: ScanRequest, api_key: str = Depends(get_api_key)):
# ... scan logic
Rate Limiting
from slowapi import Limiter
from slowapi.util import get_remote_address
limiter = Limiter(key_func=get_remote_address)
app.state.limiter = limiter
@app.post("/scan")
@limiter.limit("10/minute")
async def scan_skill(request: Request, scan_request: ScanRequest):
# ... scan logic
HTTPS
Run behind reverse proxy (nginx, Caddy) with TLS:
server {
listen 443 ssl;
server_name api.skill_scanner.com;
ssl_certificate /path/to/cert.pem;
ssl_certificate_key /path/to/key.pem;
location / {
proxy_pass http://localhost:8000;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
}
}
Monitoring
Health Checks
curl http://localhost:8000/health
# Monitor continuously
watch -n 5 'curl -s http://localhost:8000/health | jq'
Logging
import logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)
Metrics
Integrate with Prometheus:
from prometheus_fastapi_instrumentator import Instrumentator
Instrumentator().instrument(app).expose(app)
Troubleshooting
Server won't start
# Check if port is already in use
lsof -i :8000
# Try different port
skill-scanner-api --port 8080
LLM analyzer not available
# Reinstall scanner package and ensure provider dependencies are present
pip install -U cisco-ai-skill-scanner
# Set model credentials
export SKILL_SCANNER_LLM_API_KEY=your_key
export SKILL_SCANNER_LLM_MODEL=anthropic/claude-sonnet-4-20250514
Slow performance
- Enable caching for repeated scans
- Use batch endpoints instead of individual scans
- Consider horizontal scaling