swift-mlx-lm
MLX Swift LM - Run LLMs and VLMs on Apple Silicon using MLX. Covers local inference, streaming, wired memory coordination, tool calling, LoRA fine-tuning, embeddings, and model porting.
developing-with-prism
Guide for developing with Prism PHP package - a Laravel package for integrating LLMs. Activate or use when working with Prism features including text generation, structured output, embeddings, image generation, audio processing, streaming, tools/function calling, or any LLM provider integration (OpenAI, Anthropic, Gemini, Mistral, Groq, XAI, DeepSeek, OpenRouter, Ollama, VoyageAI, ElevenLabs). Activate for any Prism-related development tasks.
Smart Connections
MCP server for Obsidian Smart Connections. Semantic search using your vault's embeddings.
Doctree Mcp
BM25 search + tree navigation over markdown docs for AI agents. No embeddings, no LLM calls.
configuring-agent-brain
Installation and configuration skill for Agent Brain document search system. Use when asked to "install agent brain", "setup agent brain", "configure agent brain", "setting up document search", "installing agent-brain packages", "configuring API keys", "initializing project for search", "troubleshooting agent brain", "pip install agent-brain", "agent brain not working", "agent brain setup error", "configure embeddings provider", "setup ollama for agent brain", or "agent brain environment variables". Covers package installation, provider configuration, project initialization, and server management.
003-skills-inventory
Use when you need to generate a checklist document with Java system prompts from skills.xml, following the embedded section template and producing INVENTORY-SKILLS-JAVA.md. This should trigger for requests such as Create Java system prompts checklist; Generate INVENTORY-SKILLS-JAVA.md; Use @003-skills-inventory. Part of cursor-rules-java project
biome-developer
General development best practices and common gotchas when working on Biome. Use for avoiding common mistakes, understanding Biome-specific patterns (AST, syntax nodes, string extraction, embedded languages), and learning technical tips.
Srclight
Deep code indexing for AI agents. SQLite FTS5 + tree-sitter + embeddings + MCP.
KubeBolt Copilot Skill
You are the KubeBolt AI Copilot â an expert Kubernetes assistant embedded inside KubeBolt's monitoring UI. You have two knowledge sources: deep Kubernetes expertise and real-time cluster data from KubeBolt's API.
CodeScope Q&A
CodeScope indexes source code into a two-layer knowledge graph â **structure** (functions, calls, imports, classes, modules) and **evolution** (commits, file changes, function modifications) â plus **semantic embeddings** for every function. Supports **Python, JavaScript/TypeScript, C, and Java*
Io.Github.Fjnunezp75/Gpu Bridge
30 GPU-powered AI services as MCP tools. LLM, image, video, audio, embeddings & more.
zettelforge
ZettelForge v2.0.0 â Production CTI agentic memory system. Hybrid TypeDB (STIX 2.1 ontology) + LanceDB (vector search). Zero external AI dependencies: fastembed for embeddings, llama-cpp-python for LLM. 75% accuracy on CTI queries, 18% on LOCOMO. Use when agents need persistent memory, threat intel retrieval, entity extraction, graph traversal, or RAG synthesis.
Embgrep
Local semantic search — embedding-powered grep for files, zero external services.
cocoindex-v1
This skill should be used when building data processing pipelines with CocoIndex v1, a Python library for incremental data transformation. Use when the task involves processing files/data into databases, creating vector embeddings, building knowledge graphs, ETL workflows, or any data pipeline requiring automatic change detection and incremental updates. CocoIndex v1 is Python-native (supports any Python types), has no DSL, and is currently under pre-release (version 1.0.0a1 or later).
cost-report
Query and report on API usage costs across LLM, embedding, and tool providers
wax
Comprehensive guidance for the Wax on-device memory/RAG framework. Use when integrating MemoryOrchestrator, VideoRAGOrchestrator, Wax/WaxSession, embedding providers, hybrid search, maintenance, or when evaluating Wax constraints like offline-only, single-file .wax persistence and deterministic retrieval.
deAPI MCP Server
33 AI tools: transcription, image/video generation, TTS, music, OCR, embeddings via deAPI
001-skills
Use when you need to generate a checklist document with Java system prompts, following the embedded template exactly and producing SYSTEM-PROMPTS-JAVA.md in the project root. Part of the skills-for-java project
Memwright
Embedded memory for AI agents with SQLite, pgvector, and Neo4j graph search.
adding-templates
Adds new workflow templates to the ComfyUI template repository. Guides through creating workflow JSON, thumbnails, index.json entry, bundle assignment, model embedding, and i18n sync. Use when asked to: add a template, create a new template, submit a workflow, new workflow template, add a workflow, contribute a template, import a workflow, set up a new template, register a template, onboard a template, include a new workflow, publish a template, ship a template, upload a workflow, or make a new template available. Triggers on: add template, new template, new workflow, import workflow, contribute workflow, submit template, create template.
clean-doc-examples
Use when syncing or simplifying example code in docs/articles or README.md so embedded docs samples stay aligned with examples tests while removing compatibility noise from the published snippets.
ai-cost-manager-reducer
Audit AI-powered features, API calls, agent workflows, prompt chains, tool calls, embeddings, vector search, retries, streaming flows, background jobs, cron tasks, caching layers, logs, and model selection logic to detect token waste, repeated AI calls, and inefficient prompt chains. Produces severity-ranked findings with safe optimization strategies that preserve reasoning quality and chain reliability. Use before approving or modifying any AI-powered feature, agent workflow, or model-calling code.
Io.Github.Base76 Research Lab/Token Compressor
Compress prompts 40-60% using local LLM + embedding validation. Preserves all conditionals.
Twelvelabs Mcp Server
TwelveLabs MCP: video indexing, search, analysis, and embeddings for AI applications.
Io.Github.N24q02m/Better Code Review Graph
Knowledge graph for token-efficient code reviews with fixed search and configurable embeddings
discord-adv
Advanced Discord server management via Discord API v10: send embeds, create channels, manage roles, moderation. Use when managing Discord server structure, sending rich embedded messages, or moderating users. Requires DISCORD_BOT_TOKEN.