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Found 1,763 Skills
Create new skills for the lovstudio/skills repo. Fork of the official skill-creator with lovstudio conventions: lovstudio: name prefix, skills/lovstudio-<name>/ directory structure, mandatory README.md per skill, SKILL.md with AskUserQuestion interactive flow, standalone Python CLI scripts, CJK text handling, and auto-update of root README + CLAUDE.md. Use when the user wants to create a new skill, add a skill to this repo, scaffold a skill, or mentions "新建skill", "创建skill", "new skill", "add skill", "生成skill".
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.
Add an AI agent / RAG backend (@convex-dev/agent) to the Convex app.
Look up startups across SEC Form D, GitHub, Hacker News, Companies House, YC, and Wikidata in one command — including the SEC fundraising data hidden behind paid Crunchbase tiers. Trigger phrases: `look up this startup`, `research <company>`, `what does <company> do`, `form D for <company>`, `is <company> still active`, `compare <a> and <b>`, `use company-goat`, `run company-goat-pp-cli`.
Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, query remote databases or cloud storage as DataFrames, or join data across different sources — even if they don't explicitly mention chdb or DataStore. Do NOT use for raw SQL queries, ClickHouse server administration, or non-Python languages.
Pinecone integration. Manage Indexs. Use when the user wants to interact with Pinecone data.
CData Software integration. Manage data, records, and automate workflows. Use when the user wants to interact with CData Software data.
Use the belt CLI — run 250+ AI apps, manage knowledge, search skills, connect MCP servers
Manages connected MCP sources for enterprise search. Detects available sources, guides users to connect new ones, handles source priority ordering, and manages rate limiting awareness.
Manage the full lifecycle of Alibaba Cloud managed Milvus instances—creation, scaling, configuration management, network management, and status queries. Use this Skill when users want to create a Milvus instance, view instance status, get connection addresses, scale/change configuration, modify settings, enable/disable public network access, set whitelists, release instances, or troubleshoot creation failures. Also applicable when users say "create a Milvus instance", "view instance details", "what's the connection address", "help me check the instance", "scale CU", "change config", "enable public network", "delete instance", etc.
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.