agent-designer

Design effective question-asking mechanisms for AI agents. Covers structured elicitation tools, multi-option UIs, plan-mode integration, and reducing friction in human-agent communication.

Design layered context strategies for AI agents. Avoid prompt stuffing by letting agents discover information incrementally through skill files, recursive references, subagents, and search tools.

Design search tools and context-building strategies for AI agents. Covers the evolution from RAG to agent-driven search, grep/glob patterns, and how to let agents build their own context.

Audit and refine an agent's tool set as model capabilities evolve. Identify tools that are now constraining the model, tools that should be merged or split, and opportunities to replace tools with progressive disclosure.

Design the right action space for an AI agent. Helps choose between bash-only, specialized tools, and hybrid approaches. Uses the "math problem" framework — match tools to the model's abilities.