nw-agent-creation-workflow

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Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement

AI & Automation 526 stars 55 forks Updated 1 weeks ago MIT

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Quality Score: 92/100

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91
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90
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100
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50
License 10%
100
Description 5%
100

Skill Content

# Agent Creation Workflow ## Overview Create agents through 5 phases: ANALYZE -> DESIGN -> CREATE -> VALIDATE -> REFINE. Each phase has clear inputs, outputs, and quality gates. Follow "start minimal, add based on failure." ## Phase 1: ANALYZE **Goal**: Understand requirements and determine agent architecture. **Inputs**: User requirements, use case description, existing codebase context. **Steps**: 1. Identify single clear responsibility 2. Determine new agent or modification of existing 3. Check overlap with existing agents (avoid duplication) 4. Classify agent type: - **Specialist**: Single-domain expert (most common) - **Reviewer**: Validates outputs from another agent (Reflection pattern) - **Orchestrator**: Coordinates multiple agents 5. Identify required tools (start with Read, Glob, Grep -- add only what's needed) 6. Determine if Skills needed (domain knowledge > 50 lines) **Gate**: Single responsibility identified. Agent type classified. No overlap. **Output**: Requirements summary with agent type, tools list, skill needs. ## Phase 2: DESIGN **Goal**: Design agent architecture and structure. **Inputs**: Requirements summary from Phase 1. **Steps**: 1. Select design pattern (load `design-patterns` skill) 2. Define role and goal (1-2 sentences each) 3. Identify core principles that DIVERGE from Claude defaults: - What must this agent do differently than Claude naturally would? - Domain-specific methodology steps - Non-obvious constraints |...

Details

Author
nWave-ai
Repository
nWave-ai/nWave
Created
3 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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