A registry of Claude Code skills for automation. Operations teams use it to discover, share, and deploy skills. Connects to Claude agents for workflow automation.
git clone https://github.com/majiayu000/claude-skill-registry.gitA registry of Claude Code skills for automation. Operations teams use it to discover, share, and deploy skills. Connects to Claude agents for workflow automation.
1. **Identify your automation need**: Clearly define the task you want to automate (e.g., log analysis, deployment, monitoring) and your target environment (e.g., AWS, Kubernetes, on-prem). 2. **Search the registry**: Use the prompt template to query the claude-skill-registry with your specific requirements. Include tags like 'Python', 'Terraform', or 'Kubernetes' to narrow results. 3. **Evaluate results**: Review the top 3-5 skills based on community ratings, recent updates, and compatibility with your stack. Check the usage examples and installation commands. 4. **Install and test**: Use the provided installation command (e.g., `claude install skill-name`) and test the skill in a staging environment before deploying to production. 5. **Contribute back**: If you modify a skill or create a new one, publish it to the registry with clear documentation and tag it appropriately for others to discover.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/majiayu000/claude-skill-registryCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Search the claude-skill-registry for [SKILL_TYPE] skills that automate [TASK_NAME] in [ENVIRONMENT]. Filter by [TAGS_IF_ANY] and return the top 3 results with their descriptions, usage examples, and installation commands. Prioritize skills with the highest community ratings.
Here are the top 3 skills from the claude-skill-registry that automate log file analysis in AWS CloudWatch environments, filtered by Python and high community ratings: 1. **skill-log-analyzer-aws** (Community Rating: 4.9/5) Description: Automates parsing, filtering, and alerting for CloudWatch log groups. Supports regex-based pattern matching and integrates with Slack for notifications. Usage Example: `claude skill-log-analyzer-aws --log-group /aws/lambda/my-function --pattern "ERROR" --notify slack://alerts-channel` Installation: `claude install skill-log-analyzer-aws` 2. **skill-cloudwatch-metrics-exporter** (Community Rating: 4.7/5) Description: Extracts custom metrics from CloudWatch logs and exports them to Prometheus for visualization in Grafana. Supports multi-account AWS setups. Usage Example: `claude skill-cloudwatch-metrics-exporter --log-group /aws/ec2/performance --metric-name "CPUUtilization" --prometheus-endpoint http://localhost:9091` Installation: `pip install skill-cloudwatch-metrics-exporter && claude install skill-cloudwatch-metrics-exporter` 3. **skill-log-retention-optimizer** (Community Rating: 4.5/5) Description: Automates log retention policy enforcement across AWS accounts, reducing storage costs by 30-50% while ensuring compliance with retention requirements. Usage Example: `claude skill-log-retention-optimizer --log-groups "/aws/lambda/*,/aws/ec2/*" --retention-days 30 --dry-run` Installation: `claude install skill-log-retention-optimizer` All skills are MIT-licensed and have active maintainers. The registry shows 12 similar skills with lower ratings. Would you like me to fetch installation instructions or detailed changelogs for any of these?
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