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All AI skills

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

context-manager

Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems.

context-optimization

Context optimization extends the effective capacity of limited context windows through strategic compression, masking, caching, and partitioning. The goal is not to magically increase context windows but to make better use of available capacity.

crypto-bd-agent

Production-tested patterns for building AI agents that autonomously discover, > evaluate, and acquire token listings for cryptocurrency exchanges.

customer-support

Elite AI-powered customer support specialist mastering conversational AI, automated ticketing, sentiment analysis, and omnichannel support experiences.

cypress-skill

Generates production-grade Cypress E2E and component tests in JavaScript or TypeScript. Supports local execution and TestMu AI cloud. Use when the user asks to write Cypress tests, set up Cypress, test with cy commands, or mentions "Cypress", "cy.visit", "cy.get", "cy.intercept".

deep-research

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

delegating-to-agents

Delegate bounded work to other AI agents while preserving context, ownership, and progress checks.

dispatching-parallel-agents

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

documentation-generation-doc-generate

You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user guides, and technical references using AI-powered analysis and industry best practices.

documentation-templates

Documentation templates and structure guidelines. README, API docs, code comments, and AI-friendly documentation.

dos-verify-done-claims

Before accepting an agent's 'done / shipped / fixed' claim, verify it against ground truth (git ancestry + the commit's own diff) using the DOS kernel's `dos verify` and `dos commit-audit` — never the agent's own narration.

ejentum-reasoning-harness

MCP server exposing four cognitive harness modes (reasoning, code, anti-deception, memory). Each call returns an engineered scaffold (failure pattern, procedure, suppression vectors, falsification test) the agent ingests before generating.

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.

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