How do I install the Agent Design skill?

Run npx skillmds@latest add pluginagentmarketplace/agent-design in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Agent Design skill do?

AI agent design and tool-use prompting patterns It is listed under AI & ML on SkillMD.

Is Agent Design safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Agent Design?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Agent Design free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Agent Design?

pluginagentmarketplace (@pluginagentmarketplace) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Agent Design by pluginagentmarketplace

Name: Agent Design
Author: pluginagentmarketplace

File contents

Agent Design Skill

Bonded to: react-pattern-agent

Quick Start

Skill("custom-plugin-prompt-engineering:agent-design")

Parameter Schema

parameters:
  agent_type:
    type: enum
    values: [react, plan_execute, reflexion, multi_agent]
    default: react

  memory_type:
    type: enum
    values: [none, short_term, long_term, episodic]
    default: short_term

  tool_count:
    type: integer
    range: [1, 20]
    default: 5

Agent Architectures

Architecture	Strengths	Use Case
ReAct	Simple, effective	General tasks
Plan-Execute	Structured approach	Complex multi-step
Reflexion	Self-improvement	Learning tasks
Multi-Agent	Specialization	Large systems

Core Patterns

ReAct Agent

## Agent Configuration
You are an AI assistant with access to tools.

## Available Tools
[Tool list with descriptions]

## Behavior
1. Think about what to do
2. Take an action using a tool
3. Observe the result
4. Repeat until task complete

Plan-Execute Agent

## Planning Phase
1. Analyze the task
2. Break into subtasks
3. Identify tools needed
4. Create execution plan

## Execution Phase
1. Execute each step
2. Validate results
3. Adjust if needed
4. Report completion

Tool Definition Template

tool:
  name: "tool_name"
  description: "When and why to use this tool"
  parameters:
    param1:
      type: string
      description: "What this parameter does"
      required: true
  returns: "Description of return value"
  errors:
    - "ERROR_TYPE: How to handle"

Memory Patterns

memory_types:
  working_memory:
    scope: current_conversation
    implementation: context_window

  long_term_memory:
    scope: persistent
    implementation: vector_store

  episodic_memory:
    scope: experience_based
    implementation: structured_logs

Troubleshooting

Issue	Cause	Solution
Wrong tool	Vague descriptions	Improve descriptions
Loops forever	No exit condition	Add max iterations
Forgets context	Memory overflow	Summarize periodically
Poor planning	Complex task	Add decomposition step

References

See agent frameworks: LangChain, AutoGen, CrewAI

---name: agent-designdescription: AI agent design and tool-use prompting patterns---# Agent Design Skill**Bonded to:** `react-pattern-agent`---## Quick Start```bashSkill("custom-plugin-prompt-engineering:agent-design")```---## Parameter Schema```yamlparameters: agent_type: type: enum values: [react, plan_execute, reflexion, multi_agent] default: react memory_type: type: enum values: [none, short_term, long_term, episodic] default: short_term tool_count: type: integer range: [1, 20] default: 5```---## Agent Architectures| Architecture | Strengths | Use Case ||-------------|-----------|----------|| ReAct | Simple, effective | General tasks || Plan-Execute | Structured approach | Complex multi-step || Reflexion | Self-improvement | Learning tasks || Multi-Agent | Specialization | Large systems |---## Core Patterns### ReAct Agent```markdown## Agent ConfigurationYou are an AI assistant with access to tools.## Available Tools[Tool list with descriptions]## Behavior1. Think about what to do2. Take an action using a tool3. Observe the result4. Repeat until task complete```### Plan-Execute Agent```markdown## Planning Phase1. Analyze the task2. Break into subtasks3. Identify tools needed4. Create execution plan## Execution Phase1. Execute each step2. Validate results3. Adjust if needed4. Report completion```---## Tool Definition Template```yamltool: name: "tool_name" description: "When and why to use this tool" parameters: param1: type: string description: "What this parameter does" required: true returns: "Description of return value" errors: - "ERROR_TYPE: How to handle"```---## Memory Patterns```yamlmemory_types: working_memory: scope: current_conversation implementation: context_window long_term_memory: scope: persistent implementation: vector_store episodic_memory: scope: experience_based implementation: structured_logs```---## Troubleshooting| Issue | Cause | Solution ||-------|-------|----------|| Wrong tool | Vague descriptions | Improve descriptions || Loops forever | No exit condition | Add max iterations || Forgets context | Memory overflow | Summarize periodically || Poor planning | Complex task | Add decomposition step |---## ReferencesSee agent frameworks: LangChain, AutoGen, CrewAI

Frequently asked questions

Agent Design