Agent Skill Creator
Turn any workflow into reusable AI agent software that installs on 17 platforms — no spec writing, no prompt engineering, no coding required.
Genuine output from a real run — validate → security_scan → eval --rollout on a generated skill (paced for readability). See the flow diagram.
What you get: describe a workflow in plain English (or hand over a PDF, a link, a script) → a complete, validated and security-scanned agent skill, with functional code, its own eval spec, and a cross-platform installer → the same skill running on Claude Code, Cursor, Copilot, Gemini, Windsurf, and 12 more with one command.
Quick start
# macOS / Linux — paste into Terminal
curl -fsSL https://raw.githubusercontent.com/FrancyJGLisboa/agent-skill-creator/main/scripts/bootstrap.sh | sh
Then open your AI tool and describe what you do:
/agent-skill-creator Every Friday I clean the CRM export, calculate regional
totals, and email a PDF sales report.
…and watch it build the skill end to end:
▸ Phase 1 Discovery ▸ Phase 4 Detection
▸ Phase 2 Design+evals ▸ Phase 5 Build · validate · security-scan
▸ Phase 3 Architecture
✓ weekly-crm-report-skill (12 files, evals, installer)
installed on Claude Code, Cursor, Gemini CLI
Use it: /weekly-crm-report-skill data/crm-export.csv
→ report.pdf → dashboard.html
No clone, no pip, no API key to get started — just git and any one of 17 supported tools. Windows one-liners and single-tool installs are in Advanced Install.
Why this vs. the alternatives
| Agent Skill Creator | Hand-writing a SKILL.md | Anthropic's skill-creator |
|---|
| Time to a working skill | ~minutes, one prompt | hours of spec + iteration | minutes (interactive Q&A) |
| Coding required | none — it writes the code | yes | some |
| Cross-platform install | 17 platforms, auto-detected + format adapters | one tool, by hand | Claude-focused |
| Built-in validation + security scan | yes (hard gates) | manual | partial |
| Ships an eval spec (regression metric) | yes, per skill | no | no |
| Optimizable (autoresearch handoff) | yes | no | no |
| Input you can hand it | prose, PDF, URL, code, transcript | you write it from scratch | guided prompts |
Anthropic's skill-creator is excellent for authoring a Claude skill interactively. This is for turning whatever you already have into a validated skill that installs everywhere, with the testing and security gates wired in.
Examples
Three runnable example skills ship in references/examples/. Each one passes the same gates the creator applies to your skills — validate.py, check_pipeline.py, and its own bundled eval spec (run_evals.py --rollout):
| Skill | You'd say… | It produces |
|---|
| weekly-crm-report | "clean this CRM export and total sales by region" | a deduped regional-totals JSON summary |
| pr-blocker-summarizer | "summarize my open PRs, blockers first" | a standup digest: blocked vs. ready, one-line count |
| stock-analyzer | "analyze AAPL with RSI and MACD" | indicators + a buy/sell/hold signal with reasoning |
Try one without installing anything:
git clone https://github.com/FrancyJGLisboa/agent-skill-creator
cd agent-skill-creator/references/examples/weekly-crm-report
python3 scripts/run_pipeline.py --input evals/golden/case-1/input.csv --output /tmp/summary.json
python3 scripts/run_evals.py --rollout # runs the skill on its golden inputs and scores them
The Problem
Every AI coding tool — Claude Code, GitHub Copilot, Cursor, Windsurf, Codex, Gemini, Kiro, and more — starts from zero. It doesn't know your company's processes, data sources, or compliance requirements. So every person re-explains the same workflows in every conversation. Knowledge stays in individual chat histories. New hires start from scratch.
Agent skills fix this. A skill is structured knowledge your agent loads automatically — like installing an app. Once installed, anyone on your team can invoke it and get consistent results, every time, on any platform.
The catch: building a proper skill requires understanding the spec format, writing clear prompt instructions, designing how information loads progressively, writing functional code, and getting activation keywords right. Even simple skills take multiple rounds of iteration to get right.
Agent Skill Creator removes that barrier entirely. You pass in whatever you have — messy docs, links, code, PDFs, transcripts, vague descriptions — and it produces a validated, security-scanned skill ready to install on 17 platforms and share with your team. You describe what you do; it builds the software.
Install & first skill — in detail
1. Install
The macOS/Linux one-liner is in Quick start above. Windows:
Windows (PowerShell):
irm https://raw.githubusercontent.com/FrancyJGLisboa/agent-skill-creator/main/scripts/bootstrap.ps1 | iex
Windows (Command Prompt):
powershell -ExecutionPolicy Bypass -Command "irm https://raw.githubusercontent.com/FrancyJGLisboa/agent-skill-creator/main/scripts/bootstrap.ps1 | iex"
The installer clones to ~/.agents/skills/agent-skill-creator and links to every detected platform (Claude Code, Copilot, Gemini CLI, Kiro, Cline, Roo Code, Kilo Code, Factory Droid, Cursor, Goose, OpenCode). To update later, run cd ~/.agents/skills/agent-skill-creator && git pull.
Advanced: Want to install to a single tool, or already have a local clone? See Advanced Install below.
2. Use it
Open your agent and type /agent-skill-creator followed by whatever you have:
/agent-skill-creator Every week I pull sales data from our CRM, clean
duplicate entries, calculate regional totals, and generate a PDF report.
You can pass anything — plain English, documentation links, existing code, API docs, PDFs, database schemas, transcripts. Combine multiple sources in one message. The more context, the better the result.
/agent-skill-creator Based on our deployment runbook: https://wiki.internal/deploy-process
/agent-skill-creator See scripts/invoice_processor.py — turn it into a reusable skill
3. What comes out
A complete skill, automatically installed on your platform:
Skill installed successfully.
To use it, open a new session and type:
/sales-report-skill Generate the weekly report for the West region
Installed at: ~/.claude/skills/sales-report-skill
The agent detects your platform, installs the skill to the right location, and tells you exactly how to invoke it. No manual steps.
The generated skill includes a cross-platform installer (install.sh) that auto-detects all 17 supported platforms, generates format adapters for Cursor (.mdc), Windsurf (.md rules), and Junie (guidelines.md) automatically, and creates a universal ~/.agents/skills/ symlink so the skill is discoverable by multiple tools at once.
sales-report-skill/
├── SKILL.md # Skill definition (activates with /sales-report-skill)
├── AGENTS.md # Companion file (read by many tools for cross-tool reach)
├── scripts/ # Functional Python code
├── references/ # Detailed documentation
├── assets/ # Templates, configs
├── install.sh # Cross-platform installer (17 platforms, format adapters, --all flag)
└── README.md # Installation instructions
Your team installs it the same way — one git clone to their tool's path — and invokes it with /sales-report-skill.
What's new
v6 — Artifacts. Skills can emit interactive React artifacts in Claude Code (and Claude.ai). When output is visualizable — time series, comparisons, KPIs, tables — Phase 2 inlines one of four bundled React templates plus the artifact protocol into the generated SKILL.md; you write no React. In hosts that don't render artifacts (Cursor, Cline, Codex CLI, Gemini CLI) the source appears as fenced code and the markdown analysis is unchanged — honest degradation. Suppress with --no-artifact; force a template with --artifact <line-chart|bar-chart|kpi-cards|data-table>. (design notes)
Every skill ships its own metric. Each generated skill carries an eval spec (evals/<name>.eval.md) plus a scripts/run_evals.py runner. In Phase 2 the creator derives 3–6 binary checks and ≥3 golden cases (seeded from your own files); you give a one-word thumbs-up. It's an instant regression test — python3 scripts/run_evals.py exits non-zero on failure, so it drops into CI. With a declared run command, run_evals.py --rollout executes the skill on each golden input and scores the real output (--rollout --promote captures the first passing baseline). The spec is consumable by autoresearch-universal for optimization with no reformatting. Honest limits: --rollout is opt-in (it runs arbitrary skill code), and llm-judge checks print as a checklist rather than being auto-graded. On by default; skip with --no-eval.
How It Works
You don't need to understand any of this to use it. But if you're curious:
The agent doesn't just follow your description literally. Humans describe what they do, not what they need. "I pull sales data and make a report" hides a dozen implicit requirements — who reads the report, what format, what happens when data is missing. The agent reads all your material, uncovers these implicit requirements, and generates its own internal specification before writing any code. It builds from that deeper understanding, not from your surface description.
UNDERSTAND Read all material → uncover real intent → generate internal spec
BUILD Structure directory → write code and docs → craft activation keywords
VERIFY Spec validation → security scan → block delivery if either fails
Every skill is automatically validated (correct structure, naming, metadata) and security-scanned (no hardcoded keys, no credential exposure, no injection risks) before delivery. Skills that fail these checks are blocked.
Share Skills Across Your Team
After the agent builds and installs your skill, it asks:
Want to share this skill with your team so they can install it too?
Say yes. The agent detects whether your team uses GitHub or GitLab, creates a repo, pushes the skill, and gives you a one-liner to share:
Shared! Your colleagues can install it by pasting this in their terminal:
git clone https://github.com/your-org/sales-report-skill.git ~/.agents/skills/sales-report-skill
One git clone to ~/.agents/skills/ makes it available on Codex CLI, Gemini CLI, Kiro, and Antigravity simultaneously. For Claude Code users: ~/.claude/skills/sales-report-skill. For Cursor: .cursor/rules/sales-report-skill.
Send that line to your colleague on Slack or Teams. They paste it. Done. They can now type /sales-report-skill in their agent.
No registry commands, no publishing steps, no terminal knowledge beyond paste. The agent handles the repo creation, the push, and generates install commands for every platform.
The result over time
Each team member creates skills from their own domain and shares them. Over months the organization accumulates a library of reusable skills:
- Sales team shares
/sales-report-skill
- Engineering shares
/deploy-checklist-skill
- Legal shares
/quarterly-compliance-skill
- Data science shares
/customer-churn-skill
- SRE shares
/incident-runbook-skill
Any colleague installs any skill with one git clone. Any agent on any platform can invoke it. Knowledge compounds instead of evaporating.
For teams and consultants: the skill registry
When an organization has more than a few skills, the agent offers to set up a team skill registry — a shared git repo where all team members publish their skills and anyone can browse and install them.
The consultant (or team lead) sets it up once:
python3 scripts/skill_registry.py init --name "Acme Corp Skills"
Then every team member can:
# Publish a skill they created
python3 scripts/skill_registry.py publish ./sales-report-skill/ --tags sales,reports
# Browse what's available
python3 scripts/skill_registry.py list
# Search for a specific skill
python3 scripts/skill_registry.py search "sales"
# Install a colleague's skill (auto-detects platform)
python3 scripts/skill_registry.py install sales-report-skill
The registry is a git repo on GitHub or GitLab. Clone it once, and every team member can publish and install. No servers, no databases — just git.
For AI consultants: The engagement model is teach, not build. Install agent-skill-creator on each team member's machine, create the shared {team}-skills-registry repo, teach the team the 5-step workflow (install, clone registry, create skill, publish, install from registry), and hand over a self-sustaining system. After you leave, the team keeps creating and sharing skills on their own. They know their workflows better than you do — your job is to remove the friction.
Advanced Install
If you prefer to install to a single tool, or you already cloned the repo:
Clone to a specific tool:
# Claude Code
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 ~/.copilot/skills/agent-skill-creator
# Gemini CLI
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.gemini/skills/agent-skill-creator
# Cursor (per-project — no global path)
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .cursor/skills/agent-skill-creator
# Universal path (Codex CLI, OpenCode, Goose, and others)
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.agents/skills/agent-skill-creator
Already cloned? Link to all tools:
macOS / Linux:
cd agent-skill-creator
./install.sh # Link to all detected platforms
./install.sh --dry-run # Preview without changes
./install.sh --uninstall # Remove all links
Windows (PowerShell):
cd agent-skill-creator
.\install.ps1 # Link to all detected platforms
.\install.ps1 -DryRun # Preview without changes
.\install.ps1 -Uninstall # Remove all links
See the full platform table below for every supported tool and path.
17 platforms supported. Same skill, same invocation, same results everywhere.
How it works
Every generated skill outputs both SKILL.md (~15 tools read it natively) and AGENTS.md (~15 tools read it) to maximize reach. Tools in Tier 2 need format conversion — the installer handles it automatically.
| Tier | Platforms | What happens |
|---|
| Tier 1 — Native SKILL.md | Claude Code, Copilot, Codex CLI, Gemini CLI, Kiro, Cline, Roo Code, Kilo Code, Goose, OpenCode, Factory Droid, Antigravity | Reads SKILL.md directly |
| Tier 2 — Auto-adapted | Cursor, Windsurf, Trae, Junie | Installer converts SKILL.md to native format (.mdc, .md rules, guidelines) |
| Tier 3 — Manual | Zed, Augment, Aider, Continue.dev | Copy skill body into tool's config file |
# Claude Code
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 ~/.copilot/skills/agent-skill-creator
# Gemini CLI
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.gemini/skills/agent-skill-creator
# Kiro
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.kiro/skills/agent-skill-creator
# Cline
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.cline/skills/agent-skill-creator
# Roo Code
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.roo/skills/agent-skill-creator
# Kilo Code
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.kilocode/skills/agent-skill-creator
# Factory Droid
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.factory/skills/agent-skill-creator
# Goose
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.config/goose/skills/agent-skill-creator
# OpenCode
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.config/opencode/skills/agent-skill-creator
# Codex CLI / universal path (read by 7+ tools as fallback)
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/.agents/skills/agent-skill-creator
Use each tool's own native path. The universal ~/.agents/skills/ path works as a fallback for Codex CLI, Gemini CLI, OpenCode, Goose, Cline, Roo Code, and Kilo Code.
Per-project install
# GitHub Copilot
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .github/skills/agent-skill-creator
# Cursor (project only — no global path exists)
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .cursor/skills/agent-skill-creator
# Windsurf
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .windsurf/rules/agent-skill-creator
# Cline
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .clinerules/skills/agent-skill-creator
# Kiro
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .kiro/skills/agent-skill-creator
# Trae
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .trae/rules/agent-skill-creator
# Roo Code
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .roo/skills/agent-skill-creator
# Kilo Code
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .kilocode/skills/agent-skill-creator
# Junie (JetBrains)
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .junie/skills/agent-skill-creator
# Antigravity (note: .agent/ singular, NOT .agents/)
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git .agent/skills/agent-skill-creator
Cursor — global workaround
Cursor has no global skills directory. Clone once and symlink per project:
# 1. Clone once
git clone https://github.com/FrancyJGLisboa/agent-skill-creator.git ~/agent-skills/agent-skill-creator
# 2. In any project, symlink
mkdir -p .cursor/rules && ln -s ~/agent-skills/agent-skill-creator .cursor/rules/agent-skill-creator
Add a shell alias to automate this (~/.zshrc or ~/.bashrc):
alias install-skills='mkdir -p .cursor/rules && ln -s ~/agent-skills/agent-skill-creator .cursor/rules/agent-skill-creator'
Then in any project: install-skills. Updates propagate automatically via the symlink.
Using the installer (for generated skills)
Every skill generated by agent-skill-creator includes a cross-platform installer — both install.sh (macOS/Linux) and install.ps1 (Windows):
macOS / Linux:
./install.sh # Auto-detect platform
./install.sh --platform cursor # Force specific platform (auto-generates .mdc)
./install.sh --all # Install to every detected tool at once
./install.sh --dry-run # Preview without installing
Windows (PowerShell):
.\install.ps1 # Auto-detect platform
.\install.ps1 -Platform cursor # Force specific platform
.\install.ps1 -All # Install to every detected tool at once
.\install.ps1 -DryRun # Preview without installing
Both installers handle all 17 platforms and create a universal ~/.agents/skills/ link after every install for cross-tool discoverability.
Claude Desktop / claude.ai
python3 scripts/export_utils.py ./agent-skill-creator/ --variant desktop
# Then: Settings > Skills > Upload the generated .zip
Update
cd ~/.agents/skills/agent-skill-creator && git pull
If you used the one-liner (Option A) or ./install.sh (Option C), all symlinks update automatically — just git pull once from the canonical location. The skill also performs a silent git-based version check when loaded and will mention if a newer version is available.
Quality Gates
Every skill goes through automated checks before delivery and on every publish:
| Gate | What It Checks |
|---|
| Spec Validation | SKILL.md structure, frontmatter format, naming rules, file references |
| Security Scan | No hardcoded API keys, no credentials, no injection patterns |
| Staleness Check | Review dates, dependency health, API schema drift |
Run them independently anytime:
python3 scripts/validate.py ./my-skill/
python3 scripts/security_scan.py ./my-skill/
python3 scripts/staleness_check.py ./my-skill/
python3 scripts/staleness_check.py ./my-skill/ --check-deps --check-drift
Skills that fail validation cannot be published. Skills with high-severity security issues are blocked.
Staleness Detection
Skills go stale. APIs change, compliance rules update, data sources move. A skill that worked six months ago may silently produce wrong results today. Staleness detection surfaces this before users hit it.
Three layers, each opt-in:
Review tracking — Every skill can declare when it was last reviewed and how often it should be. The staleness checker compares these dates and flags overdue skills. Skills without explicit dates fall back to the last git commit date on SKILL.md.
python3 scripts/staleness_check.py ./my-skill/
# Exit code 0 = fresh, 1 = overdue for review
Dependency health — Skills can declare external URLs they depend on (APIs, data sources). The --check-deps flag HTTP-checks each one and reports failures.
python3 scripts/staleness_check.py ./my-skill/ --check-deps
# Exit code 2 = one or more dependencies unreachable
Schema drift — Skills can declare the expected top-level keys in API responses. The --check-drift flag fetches each endpoint and compares actual keys against expected. Missing keys = the API changed under you.
python3 scripts/staleness_check.py ./my-skill/ --check-drift
All three layers are controlled by optional frontmatter fields. Existing skills work unchanged — the tool just suggests adding the metadata:
metadata:
created: 2026-02-27
last_reviewed: 2026-02-27
review_interval_days: 90
dependencies:
- url: https://api.example.com/v1
name: Example API
type: api
schema_expectations:
- url: https://api.example.com/v1/data
method: GET
expected_keys:
- id
- price
- volume
For teams using the skill registry, stale scans every published skill at once:
python3 scripts/skill_registry.py stale
# NAME VERSION STATUS DAYS SINCE SOURCE INTERVAL
# sales-report 1.2.0 OVERDUE 127 last_reviewed 90
# deploy-check 2.0.1 FRESH 12 published 90
Registry Commands
python3 scripts/skill_registry.py init --name "Acme Corp Skills" # First-time setup
python3 scripts/skill_registry.py publish ./skill/ --tags t1,t2 # Publish a skill
python3 scripts/skill_registry.py list # Browse all skills
python3 scripts/skill_registry.py search "query" # Search skills
python3 scripts/skill_registry.py info skill-name # Skill details
python3 scripts/skill_registry.py install skill-name # Install a skill
python3 scripts/skill_registry.py remove skill-name --force # Remove a skill
python3 scripts/skill_registry.py stale # Report stale skills
python3 scripts/skill_registry.py stale --json # Machine-readable output
Validation, Security, and Staleness
python3 scripts/validate.py ./skill/ # Spec compliance
python3 scripts/validate.py ./skill/ --json # Machine-readable output
python3 scripts/security_scan.py ./skill/ # Security audit
python3 scripts/security_scan.py ./skill/ --json # Machine-readable output
python3 scripts/staleness_check.py ./skill/ # Review staleness
python3 scripts/staleness_check.py ./skill/ --check-deps # + dependency health
python3 scripts/staleness_check.py ./skill/ --check-drift # + schema drift
python3 scripts/staleness_check.py ./skill/ --json # Machine-readable output
Install Any Skill (Universal Installer)
macOS / Linux:
# From git URL
./scripts/install-skill.sh https://github.com/someone/sales-report-skill.git
# From local path
./scripts/install-skill.sh ./sales-report-skill
# To a specific platform only
./scripts/install-skill.sh ./sales-report-skill --platform cursor --project
# Preview / remove
./scripts/install-skill.sh ./sales-report-skill --dry-run
./scripts/install-skill.sh ./sales-report-skill --uninstall
Windows (PowerShell):
# From git URL
.\scripts\install-skill.ps1 https://github.com/someone/sales-report-skill.git
# From local path
.\scripts\install-skill.ps1 .\sales-report-skill
# To a specific platform only
.\scripts\install-skill.ps1 .\sales-report-skill -Platform cursor -Project
# Preview / remove
.\scripts\install-skill.ps1 .\sales-report-skill -DryRun
.\scripts\install-skill.ps1 .\sales-report-skill -Uninstall
Export
python3 scripts/export_utils.py ./skill/ --variant desktop # For Claude Desktop
python3 scripts/export_utils.py ./skill/ --variant api # For Claude API
All commands use exit code 0 for success, 1 for errors. All support --json for CI/CD integration.
Troubleshooting
Skill not activating: Check that the SKILL.md description field contains keywords matching your query. The description is how the agent decides when to activate the skill.
Validation fails on name: Names must be lowercase, use hyphens between words, 1-64 characters. Examples: sales-report-skill, deploy-checklist.
SKILL.md too long: Move detailed content to references/ files and link from the main SKILL.md.
Platform not auto-detected: Use --platform cursor (or copilot, windsurf, codex, gemini, kiro, trae, goose, opencode, roo-code, kilo-code, factory, junie, cline, antigravity, universal) to specify explicitly.
Install to all tools at once: Inside a generated skill, use ./install.sh --all (macOS/Linux) or .\install.ps1 -All (Windows) to install to every detected platform in one command.
Project Structure
agent-skill-creator/
SKILL.md # The skill definition (what the agent reads)
README.md # This file
install.sh # Self-installer, macOS/Linux (for cloned repos)
install.ps1 # Self-installer, Windows (for cloned repos)
scripts/
bootstrap.sh # One-liner bootstrap, macOS/Linux
bootstrap.ps1 # One-liner bootstrap, Windows (PowerShell)
bootstrap.bat # One-liner bootstrap, Windows (Command Prompt)
install-skill.sh # Universal skill installer, macOS/Linux
install-skill.ps1 # Universal skill installer, Windows
install-template.sh # Template for generated installers, macOS/Linux
install-template.ps1 # Template for generated installers, Windows
validate.py # Spec compliance checker
security_scan.py # Security scanner
staleness_check.py # Staleness detection (review, deps, drift)
export_utils.py # Cross-platform export
skill_registry.py # Team skill registry
references/ # Detailed docs (loaded by the agent on demand)
pipeline-phases.md # Full creation pipeline
architecture-guide.md # Skill structure decisions
quality-standards.md # Code and documentation standards
multi-agent-guide.md # Multi-skill suite creation
cross-platform-guide.md # Platform compatibility (tiers, adapters, paths)
export-guide.md # Export documentation
templates-guide.md # Template system
interactive-mode.md # Interactive wizard
agentdb-integration.md # Learning system
phase4-detection.md # Detection & keyword-design craft reference
templates/ # Skill templates
examples/stock-analyzer/ # Example skill
registry/ # Shared skill catalog
registry.json
skills/
exports/ # Export output
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Run
python3 scripts/validate.py ./ and python3 scripts/security_scan.py ./
- Submit a pull request
License
MIT
Links
