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AI agent design and tool-use prompting patterns

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1Download skill
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SKILL.md

name agent-design
description AI agent design and tool-use prompting patterns
sasmp_version 1.3.0
bonded_agent react-pattern-agent
bond_type PRIMARY_BOND

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