Design multi-step AI agent architectures with tools, memory, and orchestration. TRIGGERS - Use when user wants to design AI agents, multi-agent systems, or autonomous AI workflows.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add Winbda/claude-skills-collection --skill agent-designer --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Agent Designer?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/winbda-agent-designer)More formats (shields.io, HTML) on the badges page.
---
name: agent-designer
description: |
Design multi-step AI agent architectures with tools, memory, and orchestration.
TRIGGERS - Use when user wants to design AI agents, multi-agent systems, or autonomous AI workflows.
---
# AI Agent Designer
## Overview
Designs AI agent architectures — single agents or multi-agent systems — with clear roles, tools, memory, and orchestration patterns.
## Workflow
### Step 1: Define the Agent
1. **Objective**: What should the agent accomplish?
2. **Scope**: What's in and out of bounds?
3. **Tools needed**: What APIs/services should it access?
4. **Autonomy level**: Fully autonomous, human-in-the-loop, or supervised?
5. **Platform**: LangChain, CrewAI, AutoGen, custom, or conceptual?
### Step 2: Choose the Architecture
| Pattern | When to Use |
|---------|-------------|
| **Single agent + tools** | One task, multiple steps |
| **Sequential chain** | Linear workflow, each step feeds the next |
| **Router agent** | Different tasks need different specialists |
| **Parallel agents** | Independent tasks that can run simultaneously |
| **Hierarchical** | Manager delegates to worker agents |
| **Collaborative** | Agents discuss and refine outputs |
### Step 3: Design the System
For each agent:
```markdown
## Agent: [Name]
### Role
[One sentence — what this agent does]
### System Prompt
```
[Full system prompt]
```
### Tools Available
| Tool | Purpose | Input | Output |
|------|---------|-------|--------|
| [tool] | [why] | [format] | [format] |
### Memory
- **Short-term**: [conversation context]
- **Long-term**: [persistent storage approach]
- **Shared**: [what other agents can access]
### Decision Logic
- IF [condition] → [action]
- IF [condition] → [escalate to human]
- IF [error] → [fallback]
### Output
[What this agent produces and where it goes]
```
## Output Format
```markdown
# AI Agent System: [Name]
## Architecture Overview
**Pattern**: [architecture type]
**Agents**: [count]
**Orchestration**: [how they coordinate]
## System Diagram
```
[Text-based architecture diagram]
```
## Agent Specifications
### Agent 1: [Name]
[Full specification per template above]
### Agent 2: [Name]
[Full specification]
## Orchestration Logic
[How agents communicate and coordinate]
## Error Handling
[What happens when things go wrong]
## Human Touchpoints
[Where and when humans intervene]
## Implementation Guide
- **Platform**: [recommendation]
- **Models**: [which LLMs for which agents]
- **Estimated cost**: [per-run cost estimate]
- **Setup steps**: [how to build it]
```
## Quality Checklist
- [ ] Each agent has a clear, single responsibility
- [ ] Tools defined with input/output formats
- [ ] Orchestration logic handles all paths
- [ ] Error handling and fallbacks defined
- [ ] Human oversight points identified
- [ ] Cost estimate included

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!