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Data & AI

Machine learning, LLMs, and data processing.

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llm-ai

24.4K

telegram-bot-builder

This skill should be used when the user asks to "create a Telegram bot", "build a Telegram chatbot", "set up a Telegram webhook", "add inline keyboards to a bot", "handle Telegram callback queries", "implement Telegram payments", "send media via Telegram bot", "configure Telegram bot commands", "deploy a Telegram bot", or mentions the Telegram Bot API, telegram bot tokens, getUpdates, setWebhook, or bot frameworks like node-telegram-bot-api, grammy, python-telegram-bot, or aiogram. Provides comprehensive guidance for building production-ready Telegram bots with Node.js and Python.

davila7

data-ai

llm-ai

24.4K

speech

Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.

davila7

data-ai

llm-ai

24.4K

think-tank

Run a Virtual Think Tank — a structured multi-persona debate — before planning or making architectural/design/strategic decisions. Use this skill whenever the user is about to plan a system, make a technology choice, evaluate trade-offs, decide on an approach, or faces any decision where multiple perspectives would sharpen the outcome. Also trigger when the user says "think tank", "debate this", "perspectives on", "trade-offs", "should I use X or Y", "help me decide", "before we plan", or asks for pros/cons of competing approaches. This skill should run BEFORE any implementation planning begins — it produces a structured analysis that feeds into better plans.

davila7

data-ai

llm-ai

24.3K

gws-chat-send

Google Chat: Send a message to a space.

googleworkspace

data-ai

machine-learning

24.3K

gws-modelarmor-sanitize-response

Google Model Armor: Sanitize a model response through a Model Armor template.

googleworkspace

data-ai

machine-learning

23.8K

paddle-design-distributed

Use when working with Paddle's distributed training system: understanding parallelism strategies (DP, ZeRO, TP, PP, SP), semi-automatic parallel with ProcessMesh + shard_tensor, SPMD inference rules, pipeline scheduling, or auto_parallel Engine.

PaddlePaddle

data-ai

llm-ai

23.4K

update-provider-models

Add new or remove obsolete model IDs for existing AI SDK providers. Use when adding a model to a provider, removing an obsolete model, or processing a list of model changes from an issue. Triggers on "add model", "remove model", "new model ID", "obsolete model", "update model IDs".

vercel

data-ai

llm-ai

23.4K

analyzing-agentscope-library

This skill provides a way to retrieve information from the AgentScope library for analysis and decision-making.

agentscope-ai

data-ai

machine-learning

22.9K

design-patterns

Rust design patterns for RTK. Newtype, Builder, RAII, Trait Objects, State Machine. Applied to CLI filter modules. Use when designing new modules or refactoring existing ones.

rtk-ai

data-ai

machine-learning

22.6K

llmfit-advisor

Detect local hardware (RAM, CPU, GPU/VRAM) and recommend the best-fit local LLM models with optimal quantization, speed estimates, and fit scoring.

AlexsJones

data-ai

llm-ai

22.6K

synonyms

Generate synonyms for words or phrases. Use this skill when the user needs alternative words with similar meanings, wants to expand vocabulary, or seeks varied expressions for writing.

QwenLM

data-ai

llm-ai

22.1K

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

ComposioHQ

data-ai

llm-ai

22K

ov-search-context

Search context data(memories, skills and resource) from OpenViking Context Database (aka. ov). Trigger this tool when 1. need information that might be stored as memories, skills or resources on OpenViking; 2. is explicitly requested searching files or knowledge; 3. sees `search context`, `search openviking`, `search ov` request.

volcengine

data-ai

llm-ai

21.6K

supermemory

Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.

supermemoryai

data-ai

data-analysis

21.5K

officecli-data-dashboard

Use this skill when the user wants to create a data dashboard, analytics dashboard, KPI dashboard, or executive summary from CSV/tabular data in Excel format. Trigger on: 'dashboard', 'KPI report', 'analytics summary', 'data visualization', 'CSV to Excel dashboard', 'executive dashboard', 'metrics dashboard'. Output is always a single .xlsx file.

iOfficeAI

data-ai

llm-ai

21.5K

aionui-skills

Access the AionUI Skills registry — discover and download AI agent skills. Use when you need to find a reusable skill for a task or manage your agent credentials on the AionUI Skills platform.

iOfficeAI

data-ai

llm-ai

21.5K

moltbook

The social network for AI agents. Post, comment, upvote, and create communities.

iOfficeAI

data-ai

data-analysis

21K

validate-oas

Use when you need a quick VALID or NOT VALID result for a scoped Kibana OAS area, and first ensure the generated `oas_docs` inputs are up to date so validation runs against the current environment rather than stale snapshots.

elastic

data-ai

llm-ai

21K

elasticsearch-onboarding

Primary guided playbook for Elasticsearch search in Kibana Agent Builder: intent → data → mapping → Dev Tools API snippets (SENSE), with one question at a time. Load this skill whenever the user wants to learn Elasticsearch search, get started, begin building, take first steps, onboard, follow a walkthrough or tutorial, go from zero to a working query, or get structured help setting up indices and search — including casual openers like hi, help, getting started, new to Elasticsearch, how do I build search, or I want to try search. Use when they need end-to-end onboarding, not a single narrow API answer. If they only ask what they can build with Elastic (exploration without the full playbook), prefer invoking /use-case-library first; you can still load this skill afterward for the guided build. The guidelines in this skill should be the main format for the conversation for the rest of the user's chat session or until they are done with onboarding or ready to leave kibana and have the necessary information to c

elastic

data-ai

llm-ai

21K

rag-chatbot

Guide for building RAG (retrieval-augmented generation) chatbots and Q&A systems with Elasticsearch. Use when a developer wants to build a chatbot, Q&A system, or AI assistant that answers questions from their own data.

elastic

data-ai

data-analysis

21K

graphify

any input (code, docs, papers, images) → knowledge graph → clustered communities → HTML + JSON + audit report

safishamsi

data-ai

data-engineering

20.7K

pipeline

Configurable pipeline orchestrator for sequencing stages

Yeachan-Heo

data-ai

llm-ai

20.7K

deep-interview

Socratic deep interview with mathematical ambiguity gating before execution

Yeachan-Heo

data-ai

machine-learning

20.7K

ecomode

Token-efficient model routing modifier

Yeachan-Heo

data-ai

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