fast-agent

https://fast-agent.ai

[{"step":"Define the agent's purpose and rules","action":"Use the prompt template to specify the agent's name, task, and rules. Replace [AGENT_NAME], [TASK], and [RULE_1/2/3] with your specific requirements. For example, automate order processing with rules like 'validate customer data,' 'check inventory,' and 'generate shipping label.'","tip":"Be specific with rules to avoid ambiguous behavior. Test edge cases during definition."},{"step":"Provide sample inputs for testing","action":"Include 2-3 sample inputs in the prompt. These should cover typical cases, edge cases, and potential errors. For example, if testing a data validation agent, include valid data, malformed data, and missing fields.","tip":"Use real-world data snippets from your systems to ensure relevance. Include both happy paths and failure scenarios."},{"step":"Execute the agent in your MCP-enabled environment","action":"Run the agent in your local or staging environment using your MCP server (e.g., `mcp-server-shopify` or `mcp-server-sap`). Use tools like `fast-agent` CLI or integrate with Python scripts for automation.","tip":"Start with a small subset of data to validate the agent's behavior before scaling up."},{"step":"Analyze performance and iterate","action":"Review the agent's output for success rate, errors, and suggested improvements. Adjust rules, retry logic, or error handling based on the results. Repeat testing until the agent meets your requirements.","tip":"Log all agent executions and errors to track performance over time. Use tools like Prometheus or Grafana for monitoring if available."},{"step":"Deploy and monitor","action":"Deploy the agent to production once testing is complete. Set up alerts for failures or performance degradation. Schedule periodic reviews to ensure the agent remains effective as systems evolve.","tip":"Document the agent's purpose, rules, and dependencies for future reference. Include contact information for the agent's owner in case of issues."}]