agent-coding

Design tool-using agent architectures with contracts and evaluation plans.

3|Updated Mar 11, 2026
One-click install
npx skills add https://github.com/JunMA98/Computer-science-claude-skills --skill agent-coding
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agent-coding
Source: https://github.com/JunMA98/Computer-science-claude-skills/tree/main/skills/agent-coding
Command: npx skills add https://github.com/JunMA98/Computer-science-claude-skills --skill agent-coding

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Designing and implementing tool-using agents for research or software workflows requires explicit architectures, tool contracts, and evaluation plans to ensure reliability and reuse.

Core Features & Use Cases

  • Explicit architecture and tool contracts to bind actions and interface expectations.
  • Prompt strategy, decision policy, and memory management for robust agent behavior.
  • Evaluation plans including failure modes, safety checks, and incremental milestones.

Quick Start

Design a tool-using agent architecture for a research workflow with a clear tool contract, prompt strategy, and evaluation plan.

Frequently Asked Questions about agent-coding

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a tool-using agent for research automation workflows?

To build a tool-using agent, you need an explicit architecture, a defined tool contract to bind interface expectations, a prompt strategy, and an actionable evaluation plan to ensure reliability and reuse.

What is a tool contract in agent architecture?

A tool contract in agent architecture explicitly defines the bindings between agent actions and interface expectations. It ensures the tool-using agent interacts with external tools reliably and safely according to the defined prompt strategy.

How do I design an evaluation plan for a coding assistant agent?

Designing an evaluation plan for a coding assistant involves defining failure modes, establishing safety checks, and setting incremental milestones to measure robust agent behavior and prompt strategy effectiveness.

When do I need explicit architecture and memory management for workflow automation agents?

You need explicit architecture and memory management for workflow automation when building robust agent behavior across teams. It ensures the agent's decision policy and prompt strategy handle complex experiment orchestration reliably.

Can I use this approach for experiment orchestration across multiple teams?

Yes, applying explicit architecture, defined tool contracts, and robust prompt strategy supports research-and-software workflows like experiment orchestration across teams, delivering a production-ready agent with clear interface expectations.

What's the best way to define a decision policy and prompt strategy for agents?

The best way to define a decision policy and prompt strategy is to align them with an explicit architecture and tool contract, ensuring robust agent behavior and clear evaluation plans for failure modes and safety checks.