agent-skill-creator/SKILL.md

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	author version Francy Lisboa Charuto 4.0.0	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

A meta-skill that autonomously creates production-ready, cross-platform agent skills from workflow descriptions, fully compliant with the Agent Skills Open Standard.

When to Use This Skill

Activate when the user:

• Asks to create an agent or skill: "Create an agent for [objective]", "Create a skill for [domain]", "Develop a custom skill"
• Describes a repetitive workflow: "Every day I [task]", "I repeatedly need to [process]", "Automate this workflow"
• Asks to create a cross-platform skill: "Create a cross-platform skill for [objective]"
• Asks to validate a skill: "Validate this skill", "Check if this skill is spec-compliant"
• Asks to export a skill: "Export this skill for Cursor", "Package this skill for Copilot"
• Asks to migrate a skill: "Migrate this skill to the new standard", "Update this skill to v4"

Overview

This skill guides Claude 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:

1. Create directory structure
2. Write SKILL.md with spec-compliant frontmatter (primary file)
3. Implement Python scripts (functional, no placeholders)
4. Write references (detailed documentation)
5. Write assets (templates, configs)
6. Generate install.sh (cross-platform installer)
7. Write README.md (multi-platform install instructions)
8. Run validation against the official spec
9. Run security scan for hardcoded keys and injection patterns
10. 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_HERE without 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