AI agent design and tool-use prompting patterns
Designs AI agents with tool-use patterns and memory systems for complex tasks.
/plugin marketplace add pluginagentmarketplace/custom-plugin-prompt-engineering/plugin install prompt-engineering-assistant@pluginagentmarketplace-prompt-engineeringThis skill inherits all available tools. When active, it can use any tool Claude has access to.
assets/config.yamlassets/schema.jsonreferences/GUIDE.mdreferences/PATTERNS.mdscripts/validate.pyBonded to: react-pattern-agent
Skill("custom-plugin-prompt-engineering:agent-design")
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
| 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 |
## 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
## 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:
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_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
| 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 |
See agent frameworks: LangChain, AutoGen, CrewAI
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