Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add mhylle/claude-skills-collection --skill "agent-creator"
Install specific skill from multi-skill repository
# Description
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# SKILL.md
name: agent-creator
description: |
Create composable AI agent systems in NestJS projects following the "tools all the way down" architecture. Use this skill when users want to: (1) Create new AI agents with orchestrator/planner/executor/evaluator components, (2) Build agentic systems that can call other agents as tools, (3) Implement DAG-based planning with parallel execution, (4) Add database-backed state persistence for agent runs, (5) Create custom evaluators for quality assurance. Triggers on "create agent", "build agent", "agent system", "agentic", "orchestrator", "planner/executor pattern", or NestJS AI agent requests.
Agent Creator
Create composable AI agent systems in NestJS with uniform tool interfaces, DAG-based planning, and database-backed state.
Core Concept
Every agent system exposes the same Tool interface as a simple tool. Callers don't know if they're calling a web search API or a complex research system. This enables arbitrary composition and nesting.
Workflow
1. Gather Requirements
Ask the user:
- Purpose: What should this agent accomplish?
- Inputs/Outputs: What data goes in and comes out?
- Tools: What capabilities does it need? (existing tools or other agents)
- Success Criteria: How do we know the output is good?
- Evaluator Types: What quality dimensions matter? (see evaluators.md)
2. Generate Agent Structure
Create this NestJS module structure:
src/agents/{agent-name}/
├── {agent-name}.module.ts # NestJS module
├── {agent-name}.tool.ts # Tool interface (public API)
├── services/
│ ├── orchestrator.service.ts # Workflow coordination
│ ├── planner.service.ts # Plan generation
│ ├── executor.service.ts # Tool execution
│ └── state.service.ts # State management
├── evaluators/
│ ├── evaluator.registry.ts # Registry service
│ └── {type}.evaluator.ts # Per evaluator type
├── tools/
│ └── tool.registry.ts # Available tools
├── entities/ # TypeORM entities
├── dto/ # Input/output DTOs
├── prompts/ # LLM prompts
├── config/
│ └── {agent-name}.config.ts
└── interfaces/
3. Implement Components
For each component, follow the patterns in:
- architecture.md - Core interfaces, component roles, loops
- nestjs-patterns.md - NestJS service templates
- prompts.md - System prompts for planner/executor/evaluators
- evaluators.md - Built-in evaluator types
4. Wire Up Module
@Module({
imports: [TypeOrmModule.forFeature([...entities])],
providers: [
OrchestratorService,
PlannerService,
ExecutorService,
StateService,
EvaluatorRegistry,
...evaluators,
ToolRegistry,
AgentTool,
],
exports: [AgentTool], // Only export the Tool interface
})
export class AgentNameModule {}
Key Architecture Rules
- Uniform Interface: Agent's public API is always
Tool.execute(input, context) - Planning Loop: plan → evaluate plan → revise → repeat (max iterations)
- Execution Loop: execute step → evaluate → retry with feedback → repeat
- DAG Plans: Steps declare dependencies; independent steps run in parallel
- State Persistence: All context, messages, plans, executions stored in PostgreSQL
- Composition: Agents can use other agents as tools transparently
Quick Reference
Tool Interface
interface Tool {
id: string;
name: string;
description: string;
inputSchema: JSONSchema;
outputSchema: JSONSchema;
execute(input: any, context?: ExecutionContext): Promise<ToolResult>;
}
Plan Structure
interface Plan {
id: string;
goal: string;
success_criteria: string[];
steps: PlanStep[];
}
interface PlanStep {
id: string;
description: string;
tool_id: string;
input: any;
success_criteria: string[];
evaluator_type: string;
depends_on: string[]; // DAG dependencies
}
Default Config
export const agentConfig = {
maxDepth: 3,
maxPlanIterations: 3,
maxStepRetries: 3,
timeoutMs: 300000,
llm: { model: 'claude-sonnet-4-20250514', maxTokens: 4096 },
};
Composition Example
After creating research-agent and document-generator:
// document-generator/tools/tool.registry.ts
@Injectable()
export class ToolRegistry {
constructor(private readonly researchTool: ResearchTool) {
this.register(this.researchTool);
}
}
The document generator's planner can now create steps using research-system-v1 as a tool_id.
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.