Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Integrate App Builder Database Storage (@adobe/aio-lib-db) into an Adobe Commerce app and scaffold a runtime action that reads and writes documents. Use when the user wants persistent, queryable storage backing a Commerce app — either from a web action (HTTP-invokable) or from an event/webhook handler. Requires a base app initialized with commerce-app-init.
A tool for querying Douyin’s daily like-surge rankings. It collects Douyin posts across the platform daily and outputs a TOP50 list of posts with the largest single-day increase in likes. Supports category-based queries and looking back at dates up to 30 days. Use when users ask for Douyin surge rankings, like surges, ranking surges, or new Douyin likes. Trigger terms: Douyin surge ranking, like surge, surge ranking, surge list, Douyin surge, new Douyin likes.
Recommends and generates suitable data visualization charts using the GPT-Vis library. Supports two output modes: (1) syntax mode — generates Syntax or JSON configuration; (2) code mode — generates complete runnable code. Supports 26 chart types.
Add PostHog AI Observability to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK setup if not yet installed.
MariaDB-specific features and capabilities that go beyond standard MySQL. Use when evaluating MariaDB, optimizing an existing MariaDB application, reviewing code or schema for MariaDB improvements, asking what MariaDB can do that other databases cannot, or migrating from Oracle to MariaDB. Also use when the user asks what could be improved in how a codebase uses MariaDB, or asks about MariaDB advantages over MySQL or PostgreSQL
Build a full-site or multi-page Scrapy spider to get structured data from a website, in a new project or added to an existing one. Do not use for analyzing locally saved HTML, fixing or debugging an existing spider, schema-only or existing-spec work, Scrapy Cloud operations, or advisory questions.
Manage Alibaba Cloud AnalyticDB for MySQL (ADB) via OpenAPI/SDK. Use whenever the user needs AnalyticDB resource lifecycle and configuration operations, status checks, or troubleshooting ADB API and cluster workflow issues.
Orchestrate a full China stock research workflow by first identifying the company's analysis patterns, then selecting and sequencing the right core research skills, optional overlays, and final output structure. Use this skill when starting a new stock deep-dive or when a user wants one unified, source-backed research framework instead of isolated module outputs.
Database sharding for PostgreSQL/MySQL with hash/range/directory strategies. Use for horizontal scaling, multi-tenant isolation, billions of records, or encountering wrong shard keys, hotspots, cross-shard transactions, rebalancing issues.
Generate realistic synthetic data using Spark + Faker (strongly recommended). Supports serverless execution, multiple output formats (Parquet/JSON/CSV/Delta), and scales from thousands to millions of rows. For small datasets (<10K rows), can optionally generate locally and upload to volumes. Use when user mentions 'synthetic data', 'test data', 'generate data', 'demo dataset', 'Faker', or 'sample data'.
Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.
Fetch and export public X (Twitter) data with a self-contained Python CLI (twikit; no API keys, uses the user's own login cookies): profiles, a user's tweets/replies/likes, threads, search, followers, timelines, JSON/JSONL/CSV/SQLite output, resumable pagination. Use to scrape, archive, monitor, or analyze tweets or accounts.
Use when you need to design or implement Kafka messaging in Spring Boot — including topic design, producer/consumer implementation, JSON serialization with Boot factory customizers, Testcontainers `@ServiceConnection` integration tests, retries and dead-letter topics, idempotency, and error handling. This should trigger for requests such as Add Kafka in Spring Boot; Review Spring Kafka consumers; Improve retries and DLT in Spring Kafka; Configure Spring Kafka topics serializers or listener containers; Add Spring Kafka dead-letter topic handling. Part of Plinth Toolkit
Fetch Bilibili (哔哩哔哩) video comments for UP主 self-analysis. Use when the user asks to collect, download, export, or analyze comments on a Bilibili video (BV号 / URL / UID). Produces JSONL + summary.json suitable for further Claude Code analysis (sentiment, keywords, audience trends). Read-only; does not post/edit/delete.
A tracking and analysis tool for the most influential Douyin accounts; the daily ranking updates at 17:30 each day and looks back 7 days, the weekly ranking updates at 17:30 every Monday and looks back 3 weeks, and the monthly ranking updates at 9:00 on the 2nd of each month and looks back 3 months. Use when users want to check Douyin account rankings, daily/weekly/monthly rankings, top accounts by Douyin category, or download ranking reports
Analyze recently closed opportunities to find patterns in what wins and what loses - stage of loss, common objections from transcripts, deal characteristics. Leader-focused. Use when the user asks "win loss review", "why are we losing deals", "what's working", or "analyze closed opps".
BYMA market data via public API: leading stocks, CEDEARs, sovereign bonds, LECAPs/BONCAPs, corporate ONs, repos, options, and SENEBI. Historical OHLCV data for instruments and indices (MERVAL, BURCAP). Bond fact sheets with amortization schedules. No API key.
Read-only audit of your CRM opportunities for missing fields, stale dates, and stage mismatches - outputs a fix checklist to apply by hand or through update-opportunity. Use when the user asks "check my CRM hygiene", "check my Salesforce or HubSpot data", "clean up my CRM", "audit my opps", "what's missing in the CRM", or "clean up my pipeline".
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch architecture.
Scrape social media profiles, posts, comments, followers, and search across 20+ platforms via x402. USE FOR: - Getting TikTok, Instagram, YouTube, LinkedIn, X/Twitter, Facebook, or Reddit profiles - Fetching a user's posts, stories, highlights, videos, or transcripts - Getting comments, replies, and reactions on posts - Listing followers and following for any account - Searching posts, hashtags, and profiles across platforms - Scraping ad libraries (Facebook, TikTok, Google, LinkedIn), Facebook Marketplace, Events, and Groups - GitHub users, repos, and trending; Rumble, Threads, Bluesky, Pinterest, Twitch, Spotify, and more - UGC research via the Lightreel agent: hooks, trends, creator search, scripts, briefs - Cross-platform social media research and monitoring TRIGGERS: - "tiktok", "instagram", "facebook", "reddit", "youtube", "linkedin", "twitter" - "get followers", "who follows", "following list" - "scrape profile", "get posts from", "social media data" - "instagram stories", "tiktok videos", "facebook page", "youtube channel" - "ad library", "facebook ads", "tiktok ads", "marketplace" - "ugc", "hooks", "creator search", "content trends" - "cross-platform", "social media research" IMPORTANT: StableSocial uses an async two-step flow. Step 1: POST triggers data collection (paid, $0.06). Step 2: Poll GET /api/jobs/{jobId} (or legacy GET /api/jobs?token=...) until finished (free). All endpoints are $0.06 per call.
Works out what to reorder and when, from what is actually selling: pulls sales history and stock on hand from Shopify, Square, NetSuite, or an uploaded CSV, computes 7-day and 28-day sales velocity per item, projects a conservative stockout date for each, sizes a 60-day reorder quantity, and drafts the purchase orders and vendor emails to cover it. Flags the money sitting still too — overstock, dead stock, and zero-velocity items, reported as slow movers to clear rather than things to buy more of. Seasonality is applied where the history supports it and named where it does not. Nothing is ordered and no vendor is emailed without approval. Reach for this whenever stock comes up — "what do I need to reorder," "am I going to run out," "what should I order this month," "we keep running out of filters," "how much cash is sitting in the warehouse," "what is not moving," or "draft a PO for my supplier."
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linking related objects, enforcing constraints, planning multi-step actions as graph transformations, or when skills need to share state. Trigger on "remember", "what do I know about", "link X to Y", "show dependencies", entity CRUD, or cross-skill data access.
Create, manage, and chat with Pinecone Assistants for document Q&A with citations. Handles all assistant operations - create, upload, sync, chat, context retrieval, and list. Recognizes natural language like "create an assistant from my docs", "ask my assistant about X", or "upload my docs to Pinecone".
Expert SurrealDB developer specializing in multi-model database design, graph relations, document storage, SurrealQL queries, row-level security, and real-time subscriptions. Use when building SurrealDB applications, designing graph schemas, implementing secure data access patterns, or optimizing query performance.
Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage. Use when analyzing forward expectations, consensus estimates, valuation inputs, or comparing projections to historical performance.
Structured data research: search sources, extract structured data, archive raw sources, maintain canonical tracker pages, and deduplicate. Parameterized via YAML recipes for investor updates, donations, company updates, or any email-to-structured-data pipeline.
Expert data engineering with Metabase at the center of any company's stack: explore and profile raw warehouse tables, build clean tables as Metabase transforms pinned by transform tests, build the semantic layer (models, metrics, measures, segments, metadata), design dashboards, answer questions with checked numbers, reconcile against a reference, change delivered definitions safely. Use for data work, not one `mb` command (`metabase-cli`): “make sense of my data”, “model this raw schema”, “set up analytics for X”, “build a data model”, “define MRR / active customers officially”, “build a semantic layer”, “go from raw tables to a dashboard”, “does this number match finance”, “our numbers look wrong”, “two cards disagree”, “test this transform”, “why does this transform get case X wrong”, “make Metabot answer questions about X”, “explain this table”, “change this definition”, “build a data app”, “add a page / a form to my data app”, “donor retention”, “event attendance”, “quarterly board report”, “be my data engineer / analyst”
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.
Use when the user wants the agent to connect to an existing Twenty workspace through MCP, retrieve or inspect workspace records and metadata, or present Twenty CRM data as readable Markdown with formatted dates, values, record links, and compact tables instead of raw API output.
Keeps the CRM current without the owner ever opening it. Creates and updates contacts and deals from email, calendar, and call transcripts; logs activity automatically; drafts follow-ups on deals that have gone quiet; and maintains a next-step queue so nothing sits unowned. Runs on demand or on a schedule, includes a hygiene sweep for duplicates and stale records, and builds a lightweight CRM in a spreadsheet for owners who don't have one. Use this whenever CRM data or pipeline hygiene comes up — including phrasings like "update my CRM," "log this call," "clean up HubSpot," "clean up Salesforce," "add this to the deal," "turn my meeting into a deal note," "which deals have gone quiet," "I hate data entry," or "my pipeline is out of date." Reach for it when the owner describes a call or meeting worth recording, even without naming the CRM.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.