Query, model, and analyze data — SQL and beyond.
Query, model, migrate, and analyze data without leaving your editor. This spans SQL generation and optimization, schema design and migrations, connectors for Postgres and other engines, dataframe and analytics workflows, and pipeline tooling. Many are MCP servers, which means your agent can inspect a live schema rather than guessing at column names.
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Model Context Protocol (MCP) server for interacting with data.gouv.fr datasets and resources via LLM chatbots
Extract text from PDF files, translate it to a target language, and save the result as a Markdown file. Use this skill when the user wants to translate a PDF document or asks to "convert PDF to Chinese".
"Skill for searching and evolving the SQLite-backed Knowledge Graph.\
Model Context Protocol server for Flint — compile, validate, and render semantic chart specs to Vega-Lite, ECharts, or Chart.js artifacts (PNG/SVG) in-process.
Use when: the user asks to make or render charts with flint-chart, visualize tabular data, generate a ChartAssemblyInput, validate/render through MCP, or add Flint to a JS/TS project. Author the semantic spec, transform data before Flint when needed, install/import Flint only when executable code is needed, and reserve backend-specific style tweaks for after compiling from Flint.
Transcribe audio with StepFun's stepaudio-2.5-asr — an SSE endpoint (NOT /v1/audio/transcriptions) with 32K context, ~85-101x RTF on long audio, and a single-call ceiling around 30 minutes (no client-side chunking). Use when transcribing Chinese / English audio with StepFun, when long-form recordings (5-30 min) need to land in one request, when migrating from step-asr / step-asr-1.1, or when hitting the misleading model stepaudio-2.5-asr not supported error (which actually means wrong endpoint). Triggers on 阶跃 ASR, StepFun ASR, stepaudio-2.5-asr, 转录, 语音识别, 长音频转写, 语音转文字. For TTS with the sibling stepaudio-2.5-tts model, use the stepfun-tts skill instead.
Collect real financial data for any US publicly traded company from free public sources (yfinance). Output structured JSON consumable by downstream financial skills (DCF modeling, comps analysis, earnings review). Handles market data (price, shares, beta), historical financials (income statement, cash flow, balance sheet), WACC inputs, and analyst estimates. Use when users request collect data for ticker, get financials for company, pull market data, gather DCF inputs, or any task requiring structured financial data before analysis. Also triggers on financial data, company data, stock data.
Use for anything involving the Synalinks neuro-symbolic LM framework (Keras-inspired) — DataModel/Field/Input, JSON operators (+ & | ^ ~), synalinks.ops, LanguageModel/EmbeddingModel and provider prefixes (openai/anthropic/ollama/groq/openrouter/bedrock/...); the Program class and its four building APIs (Functional/Sequential/Subclassing/Mixed), save/load, summary; generation modules (Generator, ChainOfThought, SelfCritique, Identity, PythonSynthesis) and custom Module subclassing; control flow (Decision, Branch, And/Or/Xor, parallel branches, self-consistency, XOR guards); agents (FunctionCallingAgent, RecursiveLanguageModelAgent/RLM, DeepAgent, Tool, MCP, subagents); KnowledgeBase/RAG (DuckDB, EmbedKnowledge/UpdateKnowledge/RetrieveKnowledge, hybrid search); training (compile/fit/evaluate/predict, callbacks, ProgramCheckpoint); rewards & metrics (ExactMatch, CosineSimilarity, LMAsJudge, ProgramAsJudge, F1Score, custom rewards, masking); optimizers (RandomFewShot, OMEGA/DNS); datasets (gsm8k, hotpotqa, arcagi) and visualization. Synalinks is Keras-shaped, so without guidance LMs mix Keras/LangChain/DSPy syntax — this skill constrains usage to idiomatic Synalinks.
抓取 A 股消息面情报：从财联社、华尔街见闻、金十、新浪 7x24、东财快讯、 证监会/央行/上交所/财政部政策公告、东方财富股吧等公开来源抓取与股票相关的 新闻、政策、情绪，输出结构化 JSON 或 Markdown。 当用户提到“A 股消息面”、“抓新闻”、“个股消息”、“政策监管”、“股吧情绪”、 “财联社”、“东财快讯”、“市场情绪”或需要把某只股票相关的公开情报聚合出来时 触发。也适用于“帮我看看 000001 最近有什么消息”这类口语化请求。
Pull Bigdata.com (RavenPack) financial and news data via the official bigdata-client SDK and /v1/ REST endpoints — structured financials, prices, analyst estimates, daily entity-sentiment series, annotated chunk search, screener — when the Bigdata MCP returns only pre-synthesized tearsheets but you need the machine-readable substrate. Use when the user mentions Bigdata.com, RavenPack, a bdv2 key, the bigdata MCP, rpentityid, chunk/queryunit cost, or wants structured financials, fundamentals, prices, sentiment, or annotated news.
分析一段时间内健康数据的趋势和模式。关联药物、症状、生命体征、化验结果和其他健康指标的变化。识别令人担忧的趋势、改善情况，并提供数据驱动的洞察。当用户询问健康趋势、模式、随时间的变化或"我的健康状况有什么变化？"时使用。支持多维度分析（体重/BMI、症状、药物依从性、化验结果、情绪睡眠），相关性分析，变化检测，以及交互式HTML可视化报告（ECharts图表）。
Extract Feishu (Lark) Docs, Wiki pages/collections, spreadsheets, and Minutes (妙记) transcripts into faithful local Markdown via the lark-cli API (no LLM rewriting of the body; browser-DOM fallback when lark-cli can't reach the content). Use whenever the source is a Feishu/Lark URL and fidelity matters — 导出飞书文档/合集/妙记转写, 把飞书 wiki/知识库转 markdown, archiving a Feishu collection, exporting a 妙记 transcript, or saving a Feishu page — even if the user only says clipping, archiving, converting, or "save this". Also covers the owner-exported .docx → faithful Markdown path.
Fetch comprehensive, login-free data for any Bilibili (B站) video — title, UP name and follower count, publish date, partition, tags, per-part cids, live stats (view, like, coin, favorite, share, reply, danmaku), and full danmaku (bullet-comment) text. Use this skill whenever working with a Bilibili video and needing real, citable numbers or metadata — ingesting a Bilibili source into a knowledge base, analyzing why a video performed, verifying a creator's claimed metrics, building a case study, or any time a Bilibili view/like/favorite count is about to be written into a document — fetch it, never hand-type or estimate it. Accepts BVID, av numbers, b23.tv short links, or full URLs. Subtitles are also covered but require the user's Bilibili login.
分析减肥数据、计算代谢率、追踪能量缺口、管理减肥阶段
分析旅行健康数据、评估目的地健康风险、提供疫苗接种建议、生成多语言紧急医疗信息卡片。支持WHO/CDC数据集成的专业级旅行健康风险评估。
Alpaca Trading API integration for Model Context Protocol (MCP). V2 generates 60+ tools directly from Alpaca's OpenAPI specs using FastMCP.
分析运动数据、识别运动模式、评估健身进展，并提供个性化训练建议。支持与慢性病数据的关联分析。
分析中医体质数据、识别体质类型、评估体质特征,并提供个性化养生建议。支持与营养、运动、睡眠等健康数据的关联分析。
An intelligent agent communication platform based on LLM
分析职业健康数据、识别工作相关健康风险、评估职业健康状况、提供个性化职业健康建议。支持与睡眠、运动、心理健康等其他健康数据的关联分析。
分析康复训练数据、识别康复模式、评估康复进展，并提供个性化康复建议
Open-source data catalog. Search assets, explore lineage, and find ownership.
分析营养数据、识别营养模式、评估营养状况，并提供个性化营养建议。支持与运动、睡眠、慢性病数据的关联分析。
分析健康目标数据、识别目标模式、评估目标进度,并提供个性化目标管理建议。支持与营养、运动、睡眠等健康数据的关联分析。
DuckDB-powered skills for Claude Code: read any data file, attach and query DuckDB databases, search DuckDB/DuckLake docs, search past session logs, and install/update DuckDB extensions.
分析家族病史、评估遗传风险、识别家庭健康模式、提供个性化预防建议
分析睡眠数据、识别睡眠模式、评估睡眠质量，并提供个性化睡眠改善建议。支持与其他健康数据的关联分析。
Multi-database MCP server - provides AI assistants with structured database access to MySQL, PostgreSQL, SQLite, and TimescaleDB
MCP Server for stock and crypto
Open source autopilot for Claude
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
Send and receive WhatsApp messages via the unofficial linked-device client pywhats (pip install pywhats) — pair with QR, send text/images, group chat, read receipts, presence/typing, and a long-running JSON event stream. Use when the user wants to script WhatsApp as a linked companion device (like WhatsApp Web), pair a device, send a WhatsApp from Python, or listen for inbound messages. Triggers: 'whatsapp', 'send whatsapp', 'pair whatsapp', 'pywhats', 'linked device', 'whatsapp web client'. NOT the official WhatsApp Business/Cloud API.
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
Send Telegram messages, files, and alerts via bot API; read replies; ask questions with inline buttons and wait for the answer (approve-from-phone). Supports multiple bots and named chat targets. Use when the user wants to send a Telegram message or alert, get notified on Telegram when a task finishes or needs input, ask for approval via Telegram, or wire Telegram notifications into hooks, cron jobs, or CI. Triggers: 'telegram', 'send me a telegram', 'alert me on telegram', 'ask me on telegram', 'notify me when done'.
Execute read-only SQL queries against multiple MySQL databases. Use when: (1) querying MySQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.
Execute read-only SQL queries against multiple Microsoft SQL Server databases. Use when: (1) querying MSSQL/SQL Server databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.
Search, read, and manage Outline wiki documents. Use when: (1) searching wiki for documentation, (2) reading wiki pages or articles, (3) listing wiki collections or documents, (4) creating or updating wiki content, (5) exporting documents as markdown. Works with any Outline wiki instance (self-hosted or cloud).
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
Orchestrate coding work by delegating well-specified implementation tasks to xAI's Grok Build CLI (grok) running headlessly, while the coding assistant plans, writes the task specs, reviews every diff, and owns the result. Use when user says: 'use grok', 'grok build', 'delegate to grok', 'have grok implement', 'have grok execute', 'have grok build', 'send to grok', 'execute this plan with grok'. Executes a Markdown implementation plan task-by-task, or ad-hoc tasks with an inline spec.
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
Delegate coding tasks to Google Jules AI agent for asynchronous execution. Use when user says: 'have Jules fix', 'delegate to Jules', 'send to Jules', 'ask Jules to', 'check Jules sessions', 'pull Jules results', 'jules add tests', 'jules add docs', 'jules review pr'. Handles: bug fixes, documentation, features, tests, refactoring, code reviews. Works with GitHub repos, creates PRs.
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…
Delegate complex, long-running tasks to Manus AI agent for autonomous execution. Use when user says 'use manus', 'delegate to manus', 'send to manus', 'have manus do', 'ask manus', 'check manus sessions', or when tasks require deep web research, market analysis, product comparisons, stock analysis, competitive research, document generation, data analysis, or multi-step workflows that benefit from autonomous agent execution with parallel processing.
24 cross-platform agent skills for Claude Code, Cursor, Codex & Gemini CLI — databases, messaging, research, TTS, DevOps, and Google Worksp…