agent-advisor

Choosing the right agent involves analyzing your task description and consulting a mental model. Recommendations include primary and secondary agents, rationale, and invocation snippets for your engineering workflow.

Agent selection is based on task descriptions and mental model analysis. It provides structured recommendations with primary agents, secondary agents, and the rationale for each agent choice.

Yes, you can get agent recommendations without a mental model. The system supports a fallback to embedded knowledge to provide recommendations when the mental model is unavailable.

Yes, agent recommendation works for code review and system design tasks. It analyzes your specific task description to recommend the most suitable agent for various engineering workflows like metadata maintenance.

The best way to find an agent for metadata maintenance is to describe the task directly for analysis. The system maps the task description to an ideal agent and generates invocation snippets to execute the workflow.

You need primary and secondary agents for engineering workflows to ensure comprehensive task coverage. Primary agents handle the main task while secondary agents provide supplementary support based on task analysis rationale.