@marcfargas/skills

Reusable AI agent skills for pi, Claude Code, Cursor, and any Agent Skills compatible agent

Package details

skill

Install @marcfargas/skills from npm and Pi will load the resources declared by the package manifest.

$ pi install npm:@marcfargas/skills
Package
@marcfargas/skills
Version
0.5.1
Published
Feb 15, 2026
Downloads
49/mo · 26/wk
Author
marcfargas
License
MIT
Types
skill
Size
193.1 KB
Dependencies
0 dependencies · 0 peers
Pi manifest JSON
{
  "skills": [
    "azcli",
    "gcloud",
    "repo-hygiene",
    "pm2",
    "pre-release",
    "web-search",
    "sheet-model",
    "vhs"
  ]
}

Security note

Pi packages can execute code and influence agent behavior. Review the source before installing third-party packages.

README

Skills

Reusable skills for AI coding agents. Works with pi, Claude Code, Cursor, and any agent that supports the Agent Skills standard.

Available Skills

Category Skill Description
☁️ Azure azcli Azure CLI with agent safety model — hub + reference files
☁️ Google Cloud gcloud GCP CLI with agent safety model — hub + 7 reference files
🔧 Maintenance repo-hygiene Periodic repo health check — deps, git, CI, code quality, docs, security
⚙️ Process pm2 Process management — keep services alive, auto-restart, monitoring, ecosystem configs
🚀 Release pre-release Pre-release checklist + AI-written changesets via @changesets/cli
🔍 Search web-search Web search + content extraction via ddgs — no API keys
📊 Modeling sheet-model Headless spreadsheet engine for financial modeling, scenario analysis, .xlsx with live formulas
🎬 Terminal vhs Record terminal sessions as GIF/MP4 with VHS

Install

One command (39+ agents)

npx skills add marcfargas/skills

Installs to Claude Code, Cursor, Copilot, Amp, Cline, Windsurf, Gemini CLI, and 30+ more agents automatically.

pi

pi install npm:@marcfargas/skills

Or add to ~/.pi/agent/settings.json:

{
  "packages": ["npm:@marcfargas/skills"]
}

Manual (any agent)

Copy the skill directory into your agent's skill folder:

cp -r google-cloud/gcloud ~/.claude/skills/gcloud

How We Build Skills

Multi-Model Review

Every skill is reviewed by 3+ models (Claude, Gemini, GPT) before publishing — structure, agent usability, safety, and real-world scenario testing. If an agent can misinterpret an instruction, we find out before you do.

Safety Classification

Every operation is classified: READ / WRITE / DESTRUCTIVE / EXPENSIVE / FORBIDDEN. Destructive and expensive operations are gated — the agent must confirm before executing, and costs are flagged upfront.

Progressive Discovery

Skills use a hub + spoke architecture. The SKILL.md hub is ~140 lines — just enough to match the right skill and know what's available. Detailed per-topic reference files are loaded on demand, keeping your context window lean.

Also

Structure

skills/
├── azcli/               # Azure CLI — hub + 7 reference files
├── gcloud/              # GCP CLI — hub + 7 reference files
├── repo-hygiene/        # Periodic repo health check
├── pm2/                 # Process management
├── pre-release/         # Pre-release checklist + changesets
├── web-search/          # Web search + content extraction
├── sheet-model/         # Headless spreadsheet engine
├── vhs/                 # Terminal session recording
└── README.md

External Skills

Some skills live in their own repositories — install them directly or via their npm packages:

Skill Description Install
go-easy Gmail, Drive, Calendar for AI agents — npx go-gmail, npx go-drive, npx go-calendar npx skills add marcfargas/go-easy
holdpty Detached PTY sessions — launch, attach, view, record terminal processes npx skills add marcfargas/holdpty
odoo Odoo ERP integration — connect, introspect, automate npx skills add marcfargas/odoo-toolbox

Contributing

Skills follow the Agent Skills specification. Requirements:

  • SKILL.md with YAML frontmatter (name, description)
  • name matches parent directory (kebab-case, max 64 chars)
  • description present (max 1024 chars)
  • No hardcoded paths or credentials
  • Destructive operations clearly marked

Validation

Use skills-ref (Python — the official reference implementation from the spec authors) to validate skills locally:

pip install skills-ref

# Validate a skill directory
agentskills validate path/to/skill

# Read parsed properties as JSON
agentskills read-properties path/to/skill

# Generate <available_skills> XML prompt block
agentskills to-prompt path/to/skill-a path/to/skill-b

CI runs agentskills validate on every push — see .github/workflows/validate.yml.

Sponsor

Building high-quality, multi-model-reviewed agent skills takes serious token budget. If these skills save you time, consider sponsoring:

GitHub Sponsors

License

Code (scripts, tooling): MIT

Skill content (**/SKILL.md and reference docs): CC0 1.0 Universal — public domain, no attribution required.

Why CC0 for skills: Skill docs are consumed by AI agents and freely incorporated into any workflow. Attribution requirements create friction in agent contexts where provenance tracking is impractical.