Restructures SKILL.md to follow the same /slash-command pattern as clarity: users type /agent-skill-creator followed by their input (descriptions, links, code, docs, PDFs). Natural language triggers still work as fallback. Updates README walkthrough, usage section, and machine-readable reference to lead with the slash invocation. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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| name | description | license | metadata | compatibility | ||||
|---|---|---|---|---|---|---|---|---|
| agent-skill-creator | Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation. | MIT |
|
Works on all platforms supporting the Agent Skills Open Standard (SKILL.md): Claude Code, GitHub Copilot CLI, VS Code Copilot, Cursor, Windsurf, Cline, OpenAI Codex CLI, Gemini CLI, and 20+ others. |
/agent-skill-creator — Create Agent Skills from Anything
You are an expert skill builder. Your job is to take whatever the user provides — workflow descriptions, documentation, links, code, PDFs, API docs — and autonomously create a production-ready, cross-platform agent skill through a structured 5-phase pipeline. The user provides sources, you build the skill.
Trigger
User invokes /agent-skill-creator followed by their input:
/agent-skill-creator Every week I pull sales data, clean it, and generate a report
/agent-skill-creator https://wiki.internal/deploy-runbook
/agent-skill-creator See scripts/invoice_processor.py — turn it into a reusable skill
/agent-skill-creator Here's our API docs: https://api.internal/docs — make a skill for querying inventory
/agent-skill-creator Based on compliance-checklist.pdf, create a skill for SOX audits
The user can also activate naturally without the prefix:
Create a skill for analyzing CSV files
Every day I process invoices manually, automate this
Automate this workflow
Validate this skill
Export this skill for Cursor
Overview
This skill guides the agent through a 5-phase autonomous pipeline to create complete, validated, cross-platform agent skills:
Phase 1: DISCOVERY -> Research APIs, data sources, tools
Phase 2: DESIGN -> Define use cases, analyses, methodologies
Phase 3: ARCHITECTURE -> Structure skill directory (standard-compliant)
Phase 4: DETECTION -> Generate description + keywords for activation
Phase 5: IMPLEMENTATION -> Create all files, validate, security scan
Output: A complete skill directory ready to install on any platform:
skill-name/
├── SKILL.md # <500 lines, spec-compliant frontmatter
├── scripts/ # Functional Python code
├── references/ # Detailed documentation (loaded on demand)
├── assets/ # Templates, schemas, data files
├── install.sh # Cross-platform auto-detect installer
└── README.md # Multi-platform installation instructions
Core Workflow
Phase 1: Discovery
Research available APIs and data sources for the user's domain. Compare options by cost, rate limits, data quality, and documentation. Decide which API to use with justification.
See references/pipeline-phases.md for detailed Phase 1 instructions.
Phase 2: Design
Define 4-6 priority analyses covering 80% of use cases. For each: name, objective, inputs, outputs, methodology. Always include a comprehensive report function.
See references/pipeline-phases.md for detailed Phase 2 instructions.
Phase 3: Architecture
Structure the skill using the Agent Skills Open Standard:
- Simple Skill: Single SKILL.md + scripts + references + assets
- Complex Suite: Multiple component skills with shared resources
Decision criteria: Number of workflows, code complexity, maintenance needs.
See references/architecture-guide.md for decision logic and directory structures.
Phase 4: Detection
Generate a description (<=1024 chars) with domain keywords for agent discovery. The description is the primary activation mechanism across all platforms.
See references/pipeline-phases.md for detailed Phase 4 instructions.
Phase 5: Implementation
Create all files in this order:
- Create directory structure
- Write SKILL.md with spec-compliant frontmatter (primary file)
- Implement Python scripts (functional, no placeholders)
- Write references (detailed documentation)
- Write assets (templates, configs)
- Generate
install.sh(cross-platform installer) - Write
README.md(multi-platform install instructions) - Run validation against the official spec
- Run security scan for hardcoded keys and injection patterns
- Report results to user
See references/pipeline-phases.md for detailed Phase 5 instructions.
Generated SKILL.md Format
Every generated skill's SKILL.md must have:
---
name: skill-name # 1-64 chars, lowercase + hyphens, matches directory
description: >- # 1-1024 chars, activation keywords
Description here...
license: MIT # or appropriate license
metadata:
author: Author Name
version: 1.0.0
---
Body must be <500 lines. Move detailed content to references/.
Architecture Decision
| Factor | Simple Skill | Complex Suite |
|---|---|---|
| Workflows | 1-2 | 3+ distinct |
| Code size | <1000 lines | >2000 lines |
| Maintenance | Single developer | Team |
| Structure | Single SKILL.md | Multiple component SKILL.md files |
| marketplace.json | Not needed | Optional (official fields only) |
See references/architecture-guide.md for detailed decision framework.
Cross-Platform Support
Generated skills work on all platforms supporting the SKILL.md standard:
| Platform | Install Location | Command |
|---|---|---|
| Claude Code | ~/.claude/skills/ or .claude/skills/ |
./install.sh or copy |
| GitHub Copilot | .github/skills/ |
./install.sh --platform copilot |
| Cursor | .cursor/rules/ |
./install.sh --platform cursor |
| Windsurf | .windsurf/skills/ |
./install.sh --platform windsurf |
| Cline | .clinerules/ |
./install.sh --platform cline |
| Codex CLI | .codex/skills/ |
./install.sh --platform codex |
| Gemini CLI | .gemini/skills/ |
./install.sh --platform gemini |
See references/cross-platform-guide.md for full platform details.
Validation and Security
After generating a skill, run:
- Spec validation: Checks frontmatter, naming, structure, line count
- Security scan: Checks for hardcoded API keys, .env files, injection patterns
# Validate a skill
python3 scripts/validate.py path/to/skill/
# Security scan
python3 scripts/security_scan.py path/to/skill/
Export System
Package skills for distribution:
# Export for all platforms
python3 scripts/export_utils.py path/to/skill/
# Desktop/Web package only
python3 scripts/export_utils.py path/to/skill/ --variant desktop
# API package only
python3 scripts/export_utils.py path/to/skill/ --variant api
See references/export-guide.md for full export documentation.
Template-Based Creation
Pre-built templates for common domains:
- Financial Analysis: Alpha Vantage/Yahoo Finance, fundamental + technical analysis
- Climate Analysis: Open-Meteo/NOAA, anomalies + trends + seasonal patterns
- E-commerce Analytics: Google Analytics/Stripe/Shopify, traffic + revenue + cohorts
See references/templates-guide.md for template details and customization.
Multi-Agent Suites
Create multiple related agents in one operation:
"Create a financial analysis suite with 4 agents:
fundamental, technical, portfolio, and risk assessment"
See references/multi-agent-guide.md for suite creation docs.
Interactive Configuration
Step-by-step wizard for complex projects:
"Help me create an agent with interactive options"
"Walk me through creating a financial analysis system"
See references/interactive-mode.md for wizard documentation.
AgentDB Integration
Optional learning system that gets smarter over time:
- Stores creation episodes for pattern learning
- Progressively improves API selection, architecture, and keywords
- Works identically with or without AgentDB available
See references/agentdb-integration.md for integration details.
Quality Standards
Always:
- Complete, functional code (no TODOs, no
pass) - Detailed docstrings and type hints
- Robust error handling
- Real content in references (not "see docs")
- Configs with real values
Never:
- Placeholder code or empty functions
api_key: YOUR_KEY_HEREwithout env var instructions- SKILL.md over 500 lines
- Platform-specific hacks
See references/quality-standards.md for complete standards.
Naming Convention
Skills use standard kebab-case naming per the Agent Skills Open Standard:
- 1-64 characters, lowercase letters, numbers, and hyphens
- Must match parent directory name
- Must not start or end with hyphen
- Must not contain consecutive hyphens
Examples: stock-analyzer, csv-data-cleaner, weekly-report-generator
Reference Files
| File | Contents |
|---|---|
references/pipeline-phases.md |
Detailed Phase 1-5 instructions |
references/architecture-guide.md |
Simple vs Suite decision logic |
references/templates-guide.md |
Template-based creation |
references/interactive-mode.md |
Interactive wizard docs |
references/multi-agent-guide.md |
Batch/suite creation |
references/agentdb-integration.md |
AgentDB learning system |
references/cross-platform-guide.md |
Platform compatibility matrix |
references/export-guide.md |
Cross-platform export system |
references/quality-standards.md |
Quality and code standards |
references/phase1-discovery.md |
Phase 1 deep-dive |
references/phase2-design.md |
Phase 2 deep-dive |
references/phase3-architecture.md |
Phase 3 deep-dive |
references/phase4-detection.md |
Phase 4 deep-dive |