# Agent Skill Creator **Create cross-platform agent skills from natural language workflow descriptions.** [![Agent Skills Open Standard](https://img.shields.io/badge/Agent%20Skills-Open%20Standard-blue)](https://github.com/anthropics/agent-skills-spec) [![Version](https://img.shields.io/badge/version-4.0.0-brightgreen)]() [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)]() --- ## What Is This? Agent Skill Creator is a **meta-skill** -- a skill that creates other skills. Describe a repetitive workflow in plain English and it generates a complete, validated, cross-platform agent skill through an autonomous 5-phase pipeline. Then publish it to the built-in registry so your entire team can install and use it. **Input**: *"Every day I download stock data, analyze trends, and create reports"* **Output**: A ready-to-install skill directory with functional scripts, documentation, cross-platform installer, and spec-compliant SKILL.md — published to a shared catalog your team can browse and install from. ### Built-in Quality Gates Every skill goes through automated checks before it reaches your team. You don't need to trust the output blindly — the toolchain enforces quality: | Gate | What It Checks | When It Runs | |------|---------------|--------------| | **Spec Validation** | SKILL.md exists, frontmatter is well-formed, name follows kebab-case rules, description under 1024 chars, body under 500 lines | During creation (Phase 5) and on every publish | | **Security Scan** | No hardcoded API keys, no exposed credentials, no `eval()`/`exec()` injection risks, no sensitive files (.env, secrets.json) | During creation (Phase 5) and on every publish | | **Naming Convention** | Directory name matches SKILL.md `name` field, no consecutive hyphens, 1-64 characters | During validation | | **Structure Check** | Required files present, local references resolve, metadata fields populated | During validation | Skills that fail validation **cannot be published**. Skills with high-severity security issues **are blocked** unless explicitly overridden. This means every skill in the registry has passed both gates — your team can install with confidence. You can also run these checks independently at any time: ```bash python3 scripts/validate.py ./my-skill/ # Spec compliance python3 scripts/security_scan.py ./my-skill/ # Security audit ``` --- ## Why Agent Skills Matter AI agents (Claude Code, GitHub Copilot, Cursor, Windsurf, Codex, Gemini) are becoming the primary interface for knowledge work. But out of the box, every agent starts from zero — it doesn't know your company's processes, data sources, naming conventions, or compliance requirements. **Agent skills solve this.** A skill is structured domain knowledge that an agent loads automatically. Instead of re-explaining your workflow every conversation, the agent already knows how to do it. **The corporate opportunity:** - **Without skills**: Every person prompts the agent differently. Knowledge stays in individual chat histories. New hires start from scratch. The same workflow gets re-explained hundreds of times. - **With skills**: Someone describes a workflow once. The agent-skill-creator turns it into a reusable skill. It gets published to the team registry. Now every agent on the team — regardless of platform — knows how to do that workflow. Knowledge compounds instead of evaporating. **What changes in practice:** 1. **Operations teams** describe their runbooks. Skills get created. Now agents can execute standard procedures consistently. 2. **Data teams** describe their analysis pipelines. Skills get created. Now any team member can run the same analysis by asking their agent. 3. **Finance teams** describe their reporting workflows. Skills get created. Now quarterly reports follow the same methodology every time. 4. **Engineering teams** describe their deployment processes, code review standards, testing protocols. Skills get created. Now agents enforce consistency across the organization. The pattern is always the same: **capture tacit knowledge as skills, share them through the registry, and let agents scale that knowledge across the team.** **Why you can trust the output:** The agent-skill-creator doesn't just generate code and hope for the best. Every skill it produces goes through automated validation (spec compliance) and security scanning (credential detection, injection patterns) before it's ready. When you publish to the registry, both checks run again as a gate — skills that fail cannot be published. This means the skills your team installs are structurally sound, security-reviewed, and follow a consistent standard. You describe the workflow; the toolchain handles the quality assurance. This repo is the complete toolkit: create skills from natural language, validate them against the open standard, security-scan them, and share them through a git-based registry that gives you version history, access control, and review workflows for free. --- ## End-to-End Walkthrough This is the full lifecycle from idea to team-wide adoption. ### Step 1: Install the Skill Creator Clone this repo into your agent's skill directory: ```bash # Claude Code git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.claude/skills/agent-skill-creator # Cursor git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .cursor/rules/agent-skill-creator # Any other supported platform — see "Setup by Platform" below ``` ### Step 2: Describe a Workflow Open your agent and describe a repetitive task in plain English: ``` "Every week I pull sales data from our CRM, clean duplicate entries, calculate regional totals, and generate a PDF report for leadership." ``` The skill creator activates automatically and walks you through its 5-phase pipeline: ``` DISCOVERY → Researches CRM APIs, data cleaning techniques, PDF generation | DESIGN → Defines use cases: data pull, dedup, aggregation, report | ARCHITECTURE → Plans the skill directory structure | DETECTION → Crafts activation keywords so the skill triggers reliably | IMPLEMENTATION → Generates all code, docs, and installer ``` Output: a complete skill directory (e.g., `./sales-report-builder/`) ready to use. ### Step 3: Validate and Scan Before sharing, verify the skill meets the open standard and has no security issues: ```bash python3 scripts/validate.py ./sales-report-builder/ python3 scripts/security_scan.py ./sales-report-builder/ ``` Both checks run automatically during publishing (Step 4), but you can run them manually anytime. ### Step 4: Publish to the Team Registry The registry lives inside this repo at `registry/`. Publishing copies the skill into the shared catalog: ```bash python3 scripts/skill_registry.py publish ./sales-report-builder/ --tags sales,reports,crm ``` This validates the skill, runs the security scan, copies the files into `registry/skills/sales-report-builder/`, and updates `registry/registry.json`. Then commit and push so the team can access it: ```bash git add registry/ git commit -m "feat: Add sales-report-builder skill" git push ``` ### Step 5: Team Discovers and Installs Skills Colleagues pull the latest and browse the catalog: ```bash git pull # What skills are available? python3 scripts/skill_registry.py list # Output: # NAME VERSION AUTHOR TAGS # sales-report-builder 1.0.0 sales-team sales, reports, crm # data-quality-checker 1.0.0 data-team data, validation # deploy-checklist 2.0.0 engineering deploy, ci, checklist # Search for something specific python3 scripts/skill_registry.py search "sales" # Get full details python3 scripts/skill_registry.py info sales-report-builder # Install it (auto-detects your platform) python3 scripts/skill_registry.py install sales-report-builder ``` ### Step 6: Use the Skill After installing, the skill activates automatically. The colleague just opens their agent and says: ``` "Generate the weekly sales report for the West region" ``` The agent recognizes this matches the sales-report-builder skill and executes the workflow — pulling data, cleaning it, calculating totals, and generating the PDF. Same process, same quality, every time. ### Step 7: Iterate Skills improve over time. Someone adds error handling for API timeouts. Another person adds a new region. They publish updates to the registry, the team pulls, and everyone benefits. ```bash # Update and re-publish python3 scripts/skill_registry.py publish ./sales-report-builder/ --force git add registry/ && git commit -m "fix: Handle CRM API timeouts" && git push ``` ### The Result Over weeks and months, the registry grows organically. Each team contributes skills from their domain. The organization builds a **living library of operational knowledge** that every agent can access — regardless of which platform (Claude Code, Cursor, Copilot, etc.) each person uses. ```bash python3 scripts/skill_registry.py list # NAME VERSION AUTHOR TAGS # sales-report-builder 1.2.0 sales-team sales, reports, crm # data-quality-checker 1.0.0 data-team data, validation # deploy-checklist 2.1.0 engineering deploy, ci, checklist # quarterly-compliance 1.0.0 legal-team compliance, audit # customer-churn-model 3.0.0 data-science ml, churn, prediction # incident-runbook 1.1.0 sre-team incidents, on-call # onboarding-guide 1.0.0 hr-team onboarding, new-hire ``` This is the shift: from individual prompting to organizational capability. --- ## Quick Start ### Claude Code ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.claude/skills/agent-skill-creator ``` ### GitHub Copilot ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .github/skills/agent-skill-creator ``` ### Cursor ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .cursor/rules/agent-skill-creator ``` After installing, open your agent and type: ``` Create a skill for analyzing CSV files ``` The skill creator activates and walks you through the full pipeline. For Windsurf, Cline, Codex CLI, Gemini CLI, and other platforms see [Setup by Platform](#setup-by-platform-complete-guide) below. --- ## Usage ### Trigger Phrases Say any of these to your agent: ``` "Create a skill for analyzing stock market data" "Every day I process CSV files manually, automate this" "Create a cross-platform skill for weather alerts" "Automate this workflow" "I need to automate [repetitive task]" "Validate this skill" "Export this skill for Cursor and Copilot" "Migrate this skill to v4" ``` ### What Happens The creator runs a **5-phase autonomous pipeline**: ``` Phase 1: DISCOVERY Research APIs, data sources, and domain knowledge | Phase 2: DESIGN Define use cases, methodologies, and outputs | Phase 3: ARCHITECTURE Structure skill directory (simple vs. complex suite) | Phase 4: DETECTION Generate description + keywords for reliable activation | Phase 5: IMPLEMENTATION Create all files, run validation, run security scan ``` Output: a complete skill directory you can install on any supported platform. --- ## Setup by Platform (Complete Guide) Each platform installs with a single `git clone` directly into the right location. Replace `agent-skill-creator` with the skill name when installing generated skills. ### Claude Code ```bash # Personal skill (available in all projects) git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.claude/skills/agent-skill-creator # Per-project (scoped to one repo) git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .claude/skills/agent-skill-creator ``` ### GitHub Copilot (CLI + VS Code) ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .github/skills/agent-skill-creator ``` ### Cursor ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .cursor/rules/agent-skill-creator ``` Cursor reads SKILL.md natively alongside its `.mdc` rules. ### Windsurf ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .windsurf/skills/agent-skill-creator ``` ### Cline ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .clinerules/agent-skill-creator ``` ### OpenAI Codex CLI ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .codex/skills/agent-skill-creator ``` ### Gemini CLI ```bash git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .gemini/skills/agent-skill-creator ``` ### Claude Desktop / claude.ai (Export) These platforms use `.zip` upload instead of directory copying: 1. Export: `python3 scripts/export_utils.py ./agent-skill-creator/ --variant desktop` 2. Open Claude Desktop or claude.ai 3. Go to Settings > Skills > Upload skill 4. Select the generated `.zip` file ### Claude API (Programmatic) ```bash python3 scripts/export_utils.py ./agent-skill-creator/ --variant api ``` ```python import anthropic client = anthropic.Anthropic() with open("agent-skill-creator-api-v4.0.0.zip", "rb") as f: skill = client.skills.create(file=f, name="agent-skill-creator") response = client.messages.create( model="claude-sonnet-4", messages=[{"role": "user", "content": "Your query here"}], container={"type": "custom_skill", "skill_id": skill.id}, betas=["code-execution-2025-08-25", "skills-2025-10-02"], ) ``` Note: API sandbox has no network access, no pip install at runtime, and an 8 MB size limit. ### Updating To update an installed skill, just `git pull` from inside the skill directory: ```bash cd ~/.claude/skills/agent-skill-creator && git pull ``` --- ## How It Works | Phase | What Happens | Key Output | |-------|-------------|------------| | **Discovery** | Researches the domain, identifies APIs and data sources | Domain model, API list | | **Design** | Defines use cases, analysis methods, output formats | Use case specs, methodology docs | | **Architecture** | Decides simple skill vs. complex suite, plans directory structure | Architecture decision, file plan | | **Detection** | Crafts SKILL.md description and activation keywords | SKILL.md frontmatter, trigger phrases | | **Implementation** | Generates all code, docs, installer; validates and scans | Complete skill directory | For full pipeline documentation, see [references/pipeline-phases.md](references/pipeline-phases.md). --- ## Generated Skill Format Every generated skill follows the Agent Skills Open Standard: ``` skill-name/ SKILL.md # Main skill file (<500 lines, spec-compliant) scripts/ # Functional Python code references/ # Detailed documentation (progressive disclosure) assets/ # Templates, schemas, config files install.sh # Cross-platform installer README.md # Multi-platform install instructions ``` ### SKILL.md Frontmatter ```yaml --- name: skill-name description: >- Concise description of what the skill does (<=1024 chars). Includes activation trigger phrases. license: MIT metadata: author: Your Name version: 1.0.0 compatibility: >- Works on Claude Code, GitHub Copilot, Cursor, Windsurf, Cline, Codex CLI, Gemini CLI. --- ``` Followed by sections: When to Use, Overview, Workflow, Implementation Guidelines, and References. **Naming rules**: `kebab-case`, 1-64 characters, pattern `^[a-z][a-z0-9-]*[a-z0-9]$`, must match directory name. --- ## Tools ### Validate a Skill Check spec compliance against the Agent Skills Open Standard: ```bash python3 scripts/validate.py ./my-skill/ # JSON output (for CI/CD) python3 scripts/validate.py ./my-skill/ --json ``` **Checks**: SKILL.md existence, valid frontmatter, kebab-case name (1-64 chars), description under 1024 chars, body under 500 lines, required directory structure, install.sh exists and is executable. **Exit codes**: `0` = valid (may have warnings), `1` = invalid (errors found). ### Security Scan Scan for common security issues before sharing or deploying: ```bash python3 scripts/security_scan.py ./my-skill/ # JSON output python3 scripts/security_scan.py ./my-skill/ --json ``` **Detects**: hardcoded API keys (OpenAI, AWS, GitHub, GitLab), tokens and secrets, command injection patterns, unsafe file operations, credential exposure in config files. **Exit codes**: `0` = clean, `1` = issues found. ### Export for Other Platforms Package skills for distribution: ```bash # Desktop/Web (.zip for Claude Desktop, claude.ai) python3 scripts/export_utils.py ./my-skill/ --variant desktop # API (.zip for Claude API, <=8MB) python3 scripts/export_utils.py ./my-skill/ --variant api # All variants python3 scripts/export_utils.py ./my-skill/ ``` Output goes to `exports/`. See [references/export-guide.md](references/export-guide.md) for full documentation. ### Skill Registry Share and discover skills across your team. The registry lives inside this repo (`registry/`) so one `git pull` gives everyone access to all published skills. **First-time setup** (once per organization): ```bash python3 scripts/skill_registry.py init --name "Acme Corp Skills" ``` **Typical workflow:** ```bash # Someone describes a workflow, the agent creates a skill # "Every week I pull sales data, clean it, and make a report" # → agent creates ./sales-report-builder/ # Publish it so the team can use it python3 scripts/skill_registry.py publish ./sales-report-builder/ --tags sales,reports # Browse what the team has built python3 scripts/skill_registry.py list python3 scripts/skill_registry.py search "sales" # Get details about a skill python3 scripts/skill_registry.py info sales-report-builder # Install a skill to your platform (auto-detects Claude Code, Cursor, etc.) python3 scripts/skill_registry.py install sales-report-builder # Install for a specific platform or at project level python3 scripts/skill_registry.py install sales-report-builder --platform cursor --project # Remove a skill from the registry python3 scripts/skill_registry.py remove sales-report-builder --force ``` After publishing, commit and push so colleagues can `git pull` and install the new skill. All commands support `--json` for machine-readable output. Use `--force` to overwrite duplicates or bypass confirmation prompts. **Exit codes**: `0` = success, `1` = error. --- ## Architecture Decisions The creator automatically decides simple vs. complex based on scope: | Factor | Simple Skill | Complex Suite | |--------|-------------|---------------| | Workflows | 1-2 | 3+ distinct | | Code size | <1000 lines | >2000 lines | | Structure | Single SKILL.md | Multiple component SKILL.md files | For detailed decision logic, see [references/architecture-guide.md](references/architecture-guide.md). --- ## For AI Agents (Machine-Readable Reference) This section provides structured metadata for AI agents ingesting this README as context. ### Activation Triggers ``` create an agent for [objective] create a skill for [domain] develop a custom skill automate this workflow every day I [task] I repeatedly need to [process] I need to automate [task] create a cross-platform skill for [objective] validate this skill check if this skill is spec-compliant export this skill for [platform] package this skill for [platform] migrate this skill to v4 update this skill to the new standard create a multi-agent suite for [objective] create a skill from the [name] template ``` ### Install Commands ```bash # Claude Code (personal) git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.claude/skills/agent-skill-creator # GitHub Copilot git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .github/skills/agent-skill-creator # Cursor git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .cursor/rules/agent-skill-creator # Windsurf git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .windsurf/skills/agent-skill-creator # Cline git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .clinerules/agent-skill-creator # Codex CLI git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .codex/skills/agent-skill-creator # Gemini CLI git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .gemini/skills/agent-skill-creator # Update cd /agent-skill-creator && git pull ``` ### Tool Commands ```bash # Validate python3 scripts/validate.py PATH # Human output python3 scripts/validate.py PATH --json # Machine output # Security scan python3 scripts/security_scan.py PATH python3 scripts/security_scan.py PATH --json # Export python3 scripts/export_utils.py PATH --variant desktop python3 scripts/export_utils.py PATH --variant api # Registry (default --registry ./registry) python3 scripts/skill_registry.py init --name "Team Name" python3 scripts/skill_registry.py publish SKILL_PATH --tags T1,T2 python3 scripts/skill_registry.py list [--json] python3 scripts/skill_registry.py search QUERY [--json] python3 scripts/skill_registry.py install SKILL_NAME [--platform PLATFORM] [--project] python3 scripts/skill_registry.py info SKILL_NAME [--json] python3 scripts/skill_registry.py remove SKILL_NAME --force ``` ### Platform Paths | Platform | Path | Scope | |----------|------|-------| | Claude Code | `~/.claude/skills/` | User-level | | Claude Code | `.claude/skills/` | Project-level | | GitHub Copilot | `.github/skills/` | Project-level | | Cursor | `.cursor/rules/` | Workspace | | Windsurf | `.windsurf/skills/` | Workspace | | Cline | `.clinerules/` | Workspace | | Codex CLI | `.codex/skills/` | Workspace | | Gemini CLI | `.gemini/skills/` | Workspace | | Claude Desktop | `.zip` upload | App-level | | claude.ai | `.zip` upload | Web | | Claude API | `.zip` via API | Programmatic | ### SKILL.md Spec (Required Fields) ```yaml --- name: kebab-case-name # 1-64 chars, ^[a-z][a-z0-9-]*[a-z0-9]$ description: >- # 1-1024 chars, include activation keywords What this skill does... license: MIT metadata: author: Author Name version: X.Y.Z --- # Body: <500 lines. Move detailed content to references/. ``` ### Pipeline Phases ``` DISCOVERY -> DESIGN -> ARCHITECTURE -> DETECTION -> IMPLEMENTATION ``` Each phase is documented in `references/phase{1..5}-*.md`. --- ## Migration from v3.x Key changes in v4.0: - `-cskill` suffix removed from skill names (use standard kebab-case) - SKILL.md body limited to 500 lines (move detail to `references/`) - `install.sh` cross-platform installer added - Spec validation and security scanning tools added - `marketplace.json` simplified (optional for simple skills) Quick migration: ```bash mv my-skill-cskill/ my-skill/ # Update SKILL.md name field to remove -cskill suffix python3 scripts/validate.py ./my-skill/ ``` For the complete migration guide, see [MIGRATION.md](MIGRATION.md). --- ## Troubleshooting **Skill not activating**: Ensure SKILL.md `description` field contains the trigger phrases you expect. The description is the primary activation mechanism. **Validation fails on name**: Names must be kebab-case, 1-64 characters, no consecutive hyphens, no leading/trailing hyphens. Pattern: `^[a-z][a-z0-9-]*[a-z0-9]$`. **SKILL.md too long**: Body must be under 500 lines. Move detailed documentation to `references/` and link from the main SKILL.md. **Export fails with size error**: API exports have an 8 MB limit. Reduce asset sizes or exclude large files. **install.sh not executable**: Run `chmod +x install.sh` before executing. **Platform not auto-detected**: Use `./install.sh --platform ` to specify explicitly. --- ## Project Structure ``` agent-skill-creator/ SKILL.md # Meta-skill definition README.md # This file MIGRATION.md # v3.x to v4.0 migration guide scripts/ validate.py # Spec compliance validator security_scan.py # Security scanner export_utils.py # Cross-platform export tool skill_registry.py # Git-based shared skill registry install-template.sh # Template for generated install.sh references/ pipeline-phases.md # Full 5-phase pipeline docs architecture-guide.md # Simple skill vs. complex suite cross-platform-guide.md # Platform-specific details export-guide.md # Export system documentation phase1-discovery.md # Phase 1 deep dive phase2-design.md # Phase 2 deep dive phase3-architecture.md # Phase 3 deep dive phase4-detection.md # Phase 4 deep dive phase5-implementation.md # Phase 5 deep dive phase6-testing.md # Testing guide quality-standards.md # Quality standards reference templates-guide.md # Template system guide templates/ # Skill templates tools/ # Validation and scanning tools examples/ # Example configurations registry/ # Shared skill catalog (git-tracked) registry.json # Skill manifest skills/ # Published skill directories integrations/ agentdb_bridge.py # AgentDB integration bridge fallback_system.py # Graceful degradation system learning_feedback.py # Learning loop integration validation_system.py # Integration validation article-to-prototype/ # Example generated skill exports/ # Export output directory docs/ CHANGELOG.md # Version history NAMING_CONVENTIONS.md # Naming rules reference PIPELINE_ARCHITECTURE.md # Pipeline internals DECISION_LOGIC.md # Architecture decision logic ``` --- ## Contributing 1. Fork the repository 2. Create a feature branch (`git checkout -b feature/my-feature`) 3. Make your changes 4. Run validation: `python3 scripts/validate.py ./` 5. Run security scan: `python3 scripts/security_scan.py ./` 6. Submit a pull request --- ## License MIT License. --- ## Links - [Agent Skills Open Standard](https://github.com/anthropics/agent-skills-spec) - [Migration Guide (v3.x to v4.0)](MIGRATION.md) - [Changelog](docs/CHANGELOG.md) - [Architecture Guide](references/architecture-guide.md) - [Pipeline Phases Reference](references/pipeline-phases.md) - [Cross-Platform Guide](references/cross-platform-guide.md) - [Export Guide](references/export-guide.md) - [Activation Best Practices](references/ACTIVATION_BEST_PRACTICES.md)