| name | agent-coding |
| description | Use when designing or implementing tool-using agents for research or software workflows and you need an explicit architecture, tool contract, prompt strategy, and evaluation plan. |
Purpose
Build agent systems as engineering artifacts rather than vague autonomous demos.
When To Use
- designing coding agents, research agents, or tool-using assistants
- defining prompts, state, memory, and tool interfaces
- integrating agents into an existing repository or workflow
- evaluating agent reliability, failure modes, and recovery logic
Inputs
- target workflow or user job to automate
- available tools, APIs, files, or repo context
- product constraints such as latency, cost, privacy, and reliability
Outputs
- agent architecture and control loop
- tool contract and state model
- prompt strategy and decision policy
- evaluation cases and failure taxonomy
- implementation plan with milestones
Workflow
- Define the task boundary before choosing the agent pattern.
- Specify observation, memory, action, and recovery paths.
- Design tool interfaces that are explicit and testable.
- Add evaluation cases for success, refusal, and recovery behavior.
- Keep the first implementation narrow and measurable.
Constraints
- avoid agent designs that hide state transitions
- prefer explicit tool contracts over free-form improvisation
- separate capability demos from production-ready workflows
- define failure handling before scaling complexity
