agentic/code/addons/aiwg-dev/skills/devkit-create-agent/SKILL.md
Create a new agent with AI-guided expertise definition following the Agent Design Bible
npx skillsauth add jmagly/aiwg devkit-create-agentInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Create a new agent with AI assistance to define expertise, workflow, and capabilities.
Follows: Agent Design Bible - 10 Golden Rules for production-grade agents.
Research Foundation: REF-001 (Bandara et al.), REF-002 (Roig 2025) failure archetype prevention.
/devkit-create-agent <name> --to <target> [options]
| Argument | Required | Description | |----------|----------|-------------| | name | Yes | Agent name (kebab-case recommended) |
| Option | Description | |--------|-------------| | --to | Target addon or framework |
| Option | Description | |--------|-------------| | --template | Agent template: simple (default), complex, orchestrator | | --interactive | Enable interactive mode with guided questions |
Templates are in ~/.local/share/ai-writing-guide/templates/agent-scaffolding/.
Single-purpose, focused agent with minimal structure (Rule 1: Single Responsibility).
Full reasoning agent with all safeguards including failure archetype prevention.
Multi-agent coordination with workflow patterns and agent assignment tables.
Read-only validation agent that doesn't modify state.
When --interactive is specified, I will ask:
# Simple agent
/devkit-create-agent code-reviewer --to aiwg-utils
# Complex domain expert
/devkit-create-agent security-auditor --to sdlc-complete --template complex
# Orchestrator agent
/devkit-create-agent deployment-coordinator --to sdlc-complete --template orchestrator --interactive
<target>/agents/<name>.md
---
name: agent-name
description: Agent description
model: claude-sonnet-4-6
tools: Read, Write, MultiEdit, Bash, WebFetch
---
# Agent Title
[Description]
## Expertise
[Domain knowledge]
## Responsibilities
[What the agent does]
## Workflow
[How it approaches tasks]
## Output Format
[Expected output structure]
aiwg add-agent <name> --to <target> --template <type>
After creation, validate against the Agent Design Bible:
aiwg lint agents <target>/agents/<name>.md --verbose
| Rule | Check | |------|-------| | 1. Single Responsibility | One clear purpose, no "and" overload | | 2. Minimal Tools | 0-3 tools, justified | | 3. Explicit I/O | Inputs and outputs defined | | 4. Grounding | Verify before acting (Archetype 1) | | 5. Uncertainty | Escalate ambiguity (Archetype 2) | | 6. Context Scope | Filter distractors (Archetype 3) | | 7. Recovery | Handle errors (Archetype 4) | | 8. Model Tier | Match task complexity | | 9. Parallel Ready | Concurrent execution safe | | 10. Observable | Traceable output |
/devkit-create-command - Create a slash command/devkit-create-skill - Create an auto-triggered skill/devkit-validate - Validate agent structureaiwg lint agents - Validate against 10 Golden Rulesdata-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.