62 boosters for "package" — open source, verified from GitHub, ready to install
Create a Codex-compatible animated pet from a concept, brand cue, company/prospect name, one or more reference images, or any combination of those inputs. This workflow keeps the deterministic hatch-pet pipeline for atlas geometry, validation, visual QA, and packaging, while using concise state-spec
Hugging Face Spaces host machine-learning applications. There are 1M+ today; each Space is a git repo. This skill covers creating, building, debugging, and maintaining them. Before anything else: 1. Check the CLI is installed: . If not, .
Rules and patterns for ML demos on Hugging Face Spaces with ZeroGPU hardware. Covers , duration and quota tuning, process isolation, the CUDA availability model, concurrency safety, and CUDA build constraints. This skill is for Gradio SDK Spaces using ZeroGPU hardware. Docker and Static Spaces canno
Train language models using TRL (Transformer Reinforcement Learning) on fully managed Hugging Face infrastructure. No local GPU setup required—models train on cloud GPUs and results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Use Unsloth () instead of standard
A skill for fine-tuning and training language models on Hugging Face's cloud GPU infrastructure using TRL, supporting SFT, DPO, GRPO methods and GGUF conversion for local deployment. Developers and ML engineers working with cloud-based model training benefit from this comprehensive guidance.
Generates per-category catalog JSON files from the npm package's public API. Each catalog lists all UseCase and EventHandler abstractions in a category with their resolved source file paths. LLMs read source files on demand for exact, up-to-date types — no enrichment phase needed. 1. Discovers all
  
  
"name": "spec-driven-develop", "name": "zhu1090093659" "description": "Automates pre-development workflow for large-scale complex tasks"
Use uv exclusively for Python package management in all projects.
Stencil component rules for packages/components
This Python library provides offline timezone lookups for WGS84 coordinates by combining preprocessed polygon data, H3-based spatial shortcuts, and optional acceleration via Numba or a clang-backed point-in-polygon routine. The package aims at maximum accuracy around timezone borders (no geometry s
All canonicalized to via : A workspace can belong to multiple groups. Glob patterns matched via . into a workspace dir → vlt auto-targets that workspace for install/run/etc. For linked folders ( protocol), the folder must already be in the dependency chain for / to work.
<example type="invalid"> npm install --save-dev eslint npm uninstall lodash
Build reusable skill packages, not long prompts. Mode rules: Operating Modes, QA Ladder, Resource Boundary Spec, Method. 1. Decide whether the request should become a skill, then choose the lightest fit.
FortiManager Operations enables audit and management of Fortinet firewall estates through automated ADOM inventory, policy review, and compliance workflows. DevOps engineers and security teams managing FortiManager instances benefit from streamlined operational oversight.
Helps SwiftUI developers integrate the Recap library for in-app release notes, configure display policies, and maintain Releases.md documentation. Essential for teams building apps with Recap-based feature announcements.
A Copilot prompt that helps Laravel developers discover and evaluate useful packages within their ecosystem. Ideal for developers building Laravel applications who want AI-assisted package discovery and recommendations.
Expansion Playbook is a skill that helps sales and customer success teams structure upsell, cross-sell, and advocacy strategies by mapping customer milestones to growth plays with ROI narratives and enablement assets. It's designed for AEs, CSMs, and account managers running QBRs and account reviews.
Nix Development booster provides intelligent assistance for Nix/NixOS development by researching up-to-date information across multiple documentation sources. Developers working with Nix packages, flakes, derivations, and NixOS configurations benefit from accurate, context-aware guidance.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
A progressive-disclosure skill for ROS 2 development — from first workspace to production fleet deployment. Each section below gives you the essential decision framework; detailed patterns, code templates, and anti-patterns live in the
Skill Forge automates the creation and packaging of reusable AI skills by intelligently detecting, fetching, and organizing resources from GitHub, documentation, or local directories. Developers and AI engineers benefit from streamlined skill development workflows and reduced manual configuration overhead.
