Complete AI TrainingYourJobSkills for your job

Catalog

All AI skills

396 skills. Every one is readable here; downloads and live use need a subscription.

embedding-strategies

Guide to selecting and optimizing embedding models for vector search applications.

entropy-box

Entropy Box knowledge-compiler for embodied-AI: turns bounded requirements into grounded workflows via Solution Consult, Search, Lookup, and Evidence. Do not use it to control physical robots.

evaluation

Build evaluation frameworks for agent systems. Use when testing agent performance systematically, validating context engineering choices, or measuring improvements over time.

exa-search

Semantic search, similar content discovery, and structured research using Exa API. Use when you need semantic/embeddings-based search, finding similar content, or searching by category (company, people, research papers, etc.).

fact-check-x-complete

Compare claims from one or more AI answers, verify their citations against public primary sources, and produce an evidence-linked fact-check report without installing a bundled browser runtime.

faf-context

Get your project to 100% ✪ AI-readiness, fast — the AI auto-detects your stack and only asks for what it can't know (your goal and the human "why"). Least typing, maximum context. For time-conscious builders; feeds into faf-expert for depth.

faf-expert

Advanced .faf (Foundational AI-context Format) specialist. IANA-registered format, MCP server config, championship scoring, bi-directional sync.

faf-go

Guided interview to Gold Code (100% AI-Readiness). Use when helping users improve their .faf file through questions. Leverages Claude Code's AskUserQuestion for seamless integration. Just type /faf-go and answer questions till done.

faf-wizard

Done-for-you .faf generator. One-click AI context for any project - new, legacy, or famous. Auto-detects stack, scores readiness, works everywhere.

fal-audio

Text-to-speech and speech-to-text using fal.ai audio models

fal-generate

Generate images and videos using fal.ai AI models

fal-image-edit

AI-powered image editing with style transfer and object removal

fal-platform

Platform APIs for model management, pricing, and usage tracking

fal-upscale

Upscale and enhance image and video resolution using AI

fal-workflow

Generate workflow JSON files for chaining AI models

falsify

The scientific thinking protocol for AI agents. Use when facing complex, ambiguous, or high-stakes questions where guessing is costly: hypothesis → attempt to break it → evidence → calibrated conclusion.

famulor-skill

Operate Famulor assistants, communication history, campaigns, knowledge, automations, telephony, and workspace administration through its hosted MCP server.

fda-food-safety-auditor

Expert AI auditor for FDA Food Safety (FSMA), HACCP, and PCQI compliance. Reviews food facility records and preventive controls.

fda-medtech-compliance-auditor

Expert AI auditor for Medical Device (SaMD) compliance, IEC 62304, and 21 CFR Part 820. Reviews DHFs, technical files, and software validation.

feature-tracking

Maintain durable feature-level memory across AI coding sessions with lightweight Markdown tracks for status, source-of-truth docs, decisions, risks, and changes.

frontend-ui-engineering

Builds production-quality UIs. Use when building or modifying user-facing interfaces. Use when creating components, implementing layouts, managing state, or when the output needs to look and feel production-quality rather than AI-generated.

gdb-cli

GDB debugging assistant for AI agents - analyze core dumps, debug live processes, investigate crashes and deadlocks with source code correlation

gemini-api-dev

Use this skill when building applications with Gemini API hosted models, including Gemini and Gemma 4, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications.

geminiignore-finops

Configure and optimize .geminiignore files for AI context window efficiency and token cost reduction (FinOps).

generate-nanobanana

Generate and edit images/video with Google's Gemini media models (Nano Banana 2/Pro, Gemini Omni Flash), with cost-approval gates, reference-image support, and a prompt/output log per call.

geo-fundamentals

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

geoffrey-hinton

Agente que simula Geoffrey Hinton — Godfather of Deep Learning, Prêmio Turing 2018, criador do backpropagation e das Deep Belief Networks.

github-workflow-automation

Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.

global-chat-agent-discovery

Discover and search 18K+ MCP servers and AI agents across 6+ registries using Global Chat's cross-protocol directory and MCP server.

hf-mcp

Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.

hf-mem

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

hosted-agents

Build background agents in sandboxed environments. Use for hosted coding agents, sandboxed VMs, Modal sandboxes, and remote coding environments.

hosted-agents-v2-py

Build hosted agents using Azure AI Projects SDK with ImageBasedHostedAgentDefinition. Use when creating container-based agents in Azure AI Foundry.

hugging-face-cli

Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub.

hugging-face-community-evals

Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate.

hugging-face-datasets

Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.

hugging-face-evaluation

Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.

hugging-face-jobs

Run workloads on Hugging Face Jobs with managed CPUs, GPUs, TPUs, secrets, and Hub persistence.

hugging-face-model-trainer

Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment.

hugging-face-paper-publisher

Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.

hugging-face-papers

Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page.

hugging-face-tool-builder

Your purpose is now is to create reusable command line scripts and utilities for using the Hugging Face API, allowing chaining, piping and intermediate processing where helpful. You can access the API directly, as well as use the hf command line tool.

hugging-face-trackio

Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI).

hugging-face-vision-trainer

Train object detection, image classification, and SAM or SAM2 segmentation models locally or on Hugging Face Jobs, with dataset validation and results saved to the Hub.

huggingface-best

Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores.

huggingface-local-models

Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.

huggingface-spaces

Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants.

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