Skip to main content
ClaudeWave
Skill542 repo starsupdated yesterday

nw-agent-creation-workflow

This Claude Code skill provides a structured five-phase workflow for building AI agents, from requirements analysis through design, creation, validation, and iterative refinement. Use it when developing new agents or modifying existing ones to ensure each agent has a single clear responsibility, appropriate architecture, properly scoped tools, and quality gates at each phase.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/nWave-ai/nWave /tmp/nw-agent-creation-workflow && cp -r /tmp/nw-agent-creation-workflow/nWave/skills/nw-agent-creation-workflow ~/.claude/skills/nw-agent-creation-workflow
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# 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 | Project-specific conventions
4. Design workflow (3-7 phases)
5. Plan Skills extraction: domain knowledge -> separate Skill | Testing/validation -> separate Skill | Keep workflow and principles in core agent
6. Design Skill Loading Strategy (required for 3+ skills):
   - Map each skill to the workflow phase where it's needed
   - Create a loading table: Phase → Skill → Trigger condition
   - Add explicit `Load: skill-name` directives in each workflow phase
   - Document path: `~/.claude/skills/nw-{skill-name}/SKILL.md` (installed) or `nWave/skills/nw-{skill-name}/SKILL.md` (repo)
   - Note: `skills:` in frontmatter is declarative only — Claude Code does NOT auto-load skill files. The agent must use Read tool to load them, triggered by `Load:` directives in workflow text.
7. Draft frontmatter:
   ```yaml
   ---
   name: {kebab-case-id}
   description: Use for {domain}. {When to delegate.}
   model: inherit
   tools: [{minimum tools needed}]
   maxTurns: 30
   skills:
     - nw-{skill-name}
   ---
   ```

**Gate**: Design fits ~200-300 lines (core) + Skills. Pattern selected. Frontmatter drafted.

**Output**: Agent architecture document (working notes, not deliverable).

## Phase 3: CREATE

**Goal**: Write agent definition file and Skills.

**Inputs**: Design from Phase 2.

**Steps**:
1. Create agent `.md` file:
   - YAML frontmatter (name, description, tools, model, maxTurns, skills)
   - Role + Goal paragraph
   - Core Principles (divergences only, 3-8 items)
   - Workflow phases
   - Critical Rules (3-5, where violation causes real harm)
   - Examples (3-5 canonical cases)
   - Subagent mode instructions
   - Constraints (what agent does NOT do)
2. Create Skill files if needed: each in `nWave/skills/{agent-name}/` | YAML frontmatter with `name` and `description` | Focused content, 100-250 lines each
3. Measure: `wc -l`. Target: under 300 lines.

4. Add Skill Loading Strategy section (required for agents with 3+ skills):
   ```markdown
   ## Skill Loading Strategy

   Load on-demand by phase, not all at once:

   | Phase | Load | Trigger |
   |-------|------|---------|
   | 1 Phase Name | `skill-name` | Always — core methodology |
   | 2 Phase Name | `other-skill` | When condition is met |

   Skills path: `~/.claude/skills/nw-{skill-name}/SKILL.md` (installed) or `nWave/skills/nw-{skill-name}/SKILL.md` (repo)
   ```
5. Add `Load:` directives at the start of each workflow phase referencing the applicable skills
6. Verify: every skill in frontmatter `skills:` has at least one `Load:` directive in the workflow text. Orphan skills (declared but never loaded) are a bug.

**Gate**: Agent file created. Under 300 lines. Skills created if needed. Skill Loading Strategy present for 3+ skills.

**Output**: Agent `.md` file + Skill files.

## Phase 4: VALIDATE

**Goal**: Verify agent meets quality standards.

**Steps**:
1. Run 14-point validation checklist:
   - [ ] Uses official YAML frontmatter format
   - [ ] Total definition under 400 lines (domain knowledge in Skills)
   - [ ] Only specifies behaviors diverging from Claude defaults
   - [ ] No aggressive signaling language
   - [ ] 3-5 canonical examples for critical behaviors
   - [ ] Tools restricted to minimum needed
   - [ ] maxTurns set in frontmatter
   - [ ] Safety via platform features, not prose
   - [ ] Instructions phrased affirmatively
   - [ ] Consistent terminology throughout
   - [ ] Description clearly states delegation criteria
2. Check anti-patterns: no monolithic sections (>50 lines without structure) | No duplicated Claude defaults | No embedded safety frameworks | No aggressive language
3. Test with representative inputs (Layer 1 testing)

**Gate**: All 14 items pass. No anti-patterns.

**Output**: Validation report (pass/fail per item).

## Phase 5: REFINE

**Goal**: Iteratively improve based on testing feedback.

**Steps**:
1. Address validation failures
2. Test with edge cases
3. Add instructions ONLY for observed failure modes: wrong decision -> add rule/example | Missed step -> clarify workflow | Over-generated -> add constraint
4. Re-measure: `wc -l`. If approaching 400 lines, extract to Skills.
5. Re-validate with 14-point checklist.

**Gate**: All validation passes. Line count within target. Edge cases handled.

**Output**: Final agent definition, ready for installation.

## Quality Gates Summary

| Phase | Gate | Blocks |
|-------|------|--------|
| ANALYZE | Single responsibility, no overlap | DESIGN |
| DESIGN | Architecture fits size targe
nw-ab-critique-dimensionsSkill

Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation

nw-abr-critique-dimensionsSkill

Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation

nw-ad-critique-dimensionsSkill

Review dimensions for acceptance test quality - happy path bias, GWT compliance, business language purity, coverage completeness, walking skeleton user-centricity, priority validation, observable behavior assertions, traceability coverage, and walking skeleton boundary proof

nw-agent-testingSkill

5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance

nw-architectural-styles-tradeoffsSkill

Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating architecture styles.

nw-architecture-patternsSkill

Comprehensive architecture patterns, methodologies, quality frameworks, and evaluation methods for solution architects. Load when designing system architecture or selecting patterns.

nw-at-completeness-checkSkill

Canonical AT completeness gate — research-anchored 7-category taxonomy (C1-C7) + 15-item mechanical checklist. Paradigm-neutral. Drives acceptance-designer reviewer verdict deterministically.

nw-authoritative-sourcesSkill

Domain-specific authoritative source databases, search strategies by topic category, and source freshness rules