Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Builds a comprehensive social media audit for a brand across all major platforms using apidojo's multi-platform scrapers. Triggers when the user asks to: do a social media audit for a brand, build a full social media presence report, analyze a brand's performance across all social platforms, create a cross-platform social media benchmark, audit a competitor's entire social media strategy, build a social media scorecard for a brand, or create a comprehensive social media analysis covering Twitter Instagram TikTok and YouTube. Returns per-platform metrics, follower counts, engagement rates, content mix, posting frequency, and overall brand health score. Ideal for social media managers, brand strategists, and agency teams doing comprehensive brand audits
AE metadata capability-gateway CLI: list, inspect, create, update, delete and download metadata data tables; bind an existing dimension table to a property or create and bind a CSV dimension table. Local file upload and event/property discovery are separate prerequisite capabilities.
Guides evaluation of RAG pipeline retrieval and generation quality. Use when evaluating a retrieval-augmented generation system, measuring retrieval quality, assessing generation faithfulness or relevance, generating synthetic QA pairs for retrieval testing, or optimizing chunking strategies.
Research computing toolkit for optoelectronic information science and engineering, MATLAB/Octave, Python scientific analysis, signal processing, image processing, statistics, simulation, optimization, publication figures, sensor/time-series data, citation lookup, and common scientific libraries. Use when the user asks for MATLAB code, scientific Python, data analysis, plots, simulations, formulas, statistics, machine learning, optical/physical/materials computation, or reproducible research workflows.
Extracts TikTok posts using a specific audio track or sound using apidojo's TikTok Music Scraper on Apify. Triggers when the user asks to: get all TikTok videos using a specific sound, find TikTok posts using an audio clip, scrape TikTok videos using a trending music track, export TikTok posts made with a song, find creators using a specific sound, or collect TikTok content associated with a music URL. Returns video caption, views, likes, comments, channel info, song metadata, and hashtags per post. Ideal for music marketers, trend analysts, and viral sound trackers
Scrapes all tweets, replies, and media from any Twitter/X account using apidojo's Tweet scraper on Apify. Triggers when the user asks to: get all tweets from a Twitter account, export a user's tweet history, scrape a specific Twitter profile's posts, fetch the latest tweets from an account, download tweet data from a user timeline, or collect all posts from a Twitter username. Returns tweet text, likes, retweets, replies, media URLs, and timestamp per tweet. Ideal for journalists, researchers, competitive analysts, and data engineers.
GitHub Trending exploration and analysis. Use it to discover popular open source projects, technology trends and developer preferences, and to understand what the tech community is interested in. Use cases include "See what's hot on GitHub today", "Popular Rust projects recently", "Daily trend report for the AI field", "Are there open source projects worth watching in this area", "Do a GitHub trending analysis for me".
Amazon keyword position monitoring and SERP analysis. Real-time position tracking, competitor movement alerts, search result changes, and keyword performance optimization. Use when the user asks about keyword monitoring, SERP tracking, position alerts, or search performance analysis.
Develop applications using the Docyrus API with @docyrus/api-client and @docyrus/signin libraries. Use when building apps that authenticate with Docyrus OAuth2 (PKCE, iframe, client credentials, device code), make REST API calls to Docyrus data source endpoints, construct query payloads with filters, aggregations, formulas, pivots, and child queries, or integrate with external connectors (discover connectors, send requests through provider auth, run actions). Triggers on tasks involving Docyrus API integration, @docyrus/api-client usage, @docyrus/signin authentication, data source query building, Docyrus REST endpoint consumption, connector discovery, or external provider requests.
Monitors Instagram for brand mentions and tagged posts using apidojo's Instagram scraper on Apify. Triggers when the user asks to: track Instagram mentions of a brand or product, monitor hashtag activity around a brand on Instagram, find posts where users tag or mention a company on Instagram, discover organic brand sentiment on Instagram, find untagged brand mentions in captions, track user-generated content featuring a brand, or monitor competitor mentions on Instagram. Returns post URL, caption, author handle, likes, comments, timestamp, and mention type. Ideal for brand managers, social listening teams, PR agencies, and community managers.
Scrapes detailed TikTok user data and recent video history using apidojo's TikTok User scraper on Apify. Triggers when the user asks to: get all videos from a TikTok account, fetch a TikTok creator's recent posts and stats, export a TikTok user's video history, scrape all TikTok content from a specific creator, get TikTok post data by username, or collect video-level metrics from a TikTok profile. Returns per-video view count, likes, comments, shares, captions, and timestamps for a given account. Ideal for creator analysis, content auditing, and competitive benchmarking.
Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives, standup facilitation, backlog grooming, story points, burndown charts, blocker resolution, or agile team health. Runs Python scripts to analyse sprint JSON exports from Jira or similar tools: velocity_analyzer.py for Monte Carlo sprint forecasting, sprint_health_scorer.py for multi-dimension health scoring, and retrospective_analyzer.py for action-item and theme tracking. Produces confidence-interval forecasts, health grade reports, and improvement-velocity trends for high-performing Scrum teams.
Analyzes a competitor's Instagram content strategy and performance using apidojo's Instagram scraper on Apify. Triggers when the user asks to: analyze what a competitor posts on Instagram, benchmark a competitor's Instagram engagement, see what content types perform best for a competitor on Instagram, reverse-engineer a competitor's Instagram content calendar, identify content gaps vs. a competitor on Instagram, compare posting frequency or content themes, or understand why a competitor's Instagram is growing. Returns post frequency, content type mix, top-performing posts, hashtag strategy, and engagement benchmarks. Ideal for social media managers, brand strategists, and content marketing teams.
Extracts and analyzes YouTube comments for audience research using apidojo's YouTube scraper on Apify. Triggers when the user asks to: extract YouTube comments for research, analyze what viewers say in YouTube comments, scrape comments from a YouTube video for sentiment analysis, find common questions in YouTube comments, research audience feedback from YouTube video comments, extract top comments from a YouTube channel for audience insights, or analyze viewer reactions from YouTube comment sections. Returns comment text, likes on comment, reply count, commenter username, and timestamp. Ideal for content creators, brand researchers, product teams, and audience insight analysts.
Initialize warehouse schema discovery. Generates .astro/warehouse.md with all table metadata for instant lookups. Run once per project, refresh when schema changes. Use when user says "/astronomer-data:warehouse-init" or asks to set up data discovery.
Analyzes competitor YouTube channel strategy and content performance using apidojo's YouTube scraper. Triggers when the user asks to: analyze a competitor's YouTube channel strategy, understand what makes a competitor YouTube channel successful, benchmark a YouTube channel against a competitor, find patterns in a competitor's YouTube content that drive growth, analyze the content mix and publishing cadence of a competitor channel, understand a competitor's YouTube audience and engagement, or reverse-engineer what a competitor is doing well on YouTube. Returns content mix, format performance, publishing cadence, engagement benchmarks, and strategic insights. Ideal for YouTube content strategists, brand video teams, and competitive intelligence analysts
Scrapes Instagram posts for any hashtag using apidojo's Instagram scraper on Apify. Triggers when the user asks to: get Instagram posts for a hashtag, scrape Instagram content by tag, export Instagram post data for a keyword or topic, fetch posts under an Instagram challenge or trend, collect Instagram media for a specific tag, or download Instagram post metadata by hashtag. Returns post URL, caption, like count, comment count, author handle, and timestamp per post. Ideal for trend analysts, UGC collectors, and social media researchers.
Social media analytics and reporting — read native platform data honestly and turn it into next actions. Use when someone wants to “check my analytics”, “see how my posts are doing”, “build a social media report”, “which content is working”, “what metrics/KPIs should I track”, or to turn performance data into next steps. Measures goal-mapped SIGNAL metrics (saves, shares, watch time/retention, engagement-rate-by-reach, follower-growth-rate, CTR, conversions) — not vanity (followers/impressions/likes) — and closes the loop. Uses the METER framework. Reads brand-profile + social-strategy (goals) first. Reads WoopSocial post analytics for TikTok, LinkedIn, Facebook, Instagram, Pinterest, YouTube, and Bluesky; native dashboards otherwise. It NEVER fabricates a metric. Feeds content-recycling, experimentation, competitor-analysis, and every growth skill. Distinct from goals-and-kpis (sets targets) and experimentation (runs tests).
Finds trending products on TikTok Shop using apidojo's TikTok scraper on Apify. Triggers when the user asks to: find trending TikTok Shop products, discover what products are selling on TikTok Shop right now, identify viral TikTok Shop items in a category, find trending items with TikTok affiliate links, research TikTok Shop bestsellers, discover products going viral on TikTok for e-commerce, find hot items being promoted by TikTok creators, or build a trending product list from TikTok Shop data. Returns product name, creator promotion count, engagement signals, price range, and trend momentum. Ideal for TikTok Shop sellers, dropshippers, and e-commerce trend researchers.
Apply statistical methods to financial data including descriptive statistics, covariance estimation, regression, hypothesis testing, and resampling. Use when the user asks about return distributions, correlation between assets, building a covariance matrix, running a CAPM regression, testing whether alpha is significant, checking if returns are normal, or estimating confidence intervals. Also trigger when users mention 'volatility', 'how correlated are these', 'fat tails', 'skewness', 'R-squared', 'beta of a fund', 'bootstrap a Sharpe ratio', 'shrinkage estimator', 'Ledoit-Wolf', or ask why their optimizer produces unstable weights.
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Scrapes Instagram posts tagged at a specific location or place using apidojo's Instagram Location scraper on Apify. Triggers when the user asks to: get Instagram posts from a location, scrape photos tagged at a restaurant or hotel, fetch Instagram content from an event or venue, collect posts from a geographic area on Instagram, export location-tagged Instagram media, or find what people post from a specific place on Instagram. Returns post URL, author handle, caption, likes, comments, and timestamp per post. Ideal for hospitality brands, event teams, and UGC content collectors.
Tracks sports team fan sentiment on Twitter using apidojo's Tweet scraper. Triggers when the user asks to: track fan sentiment about a sports team on Twitter, monitor Twitter reactions to sports team news, analyze fan mood after a game result on Twitter, measure public sentiment around a sports team, monitor Twitter buzz around a sports event, analyze fan reactions to player trades or news, or build a sentiment tracker for a sports team's social media presence. Returns sentiment distribution, volume trends, top fan reactions, topic themes, and event-triggered spikes. Ideal for sports marketing teams, brand sponsors, sports analytics firms, and sports media companies.
Answers questions about ThinkingAI SDK integration and usage, including the LogBus2 data import tool. Trigger words: 怎么接入 / 如何集成 / SDK / 埋点 / 报错 / 使用方式 / API / LogBus / tracking / integration / how to integrate / data import / データ連携 / インテグレーション / 트래킹 / 연동
Interactive generation of an AE tracking plan and upload. Trigger words: 埋点方案、埋点模板、tracking plan、AE 方案生成、create tracking plan、トラッキングプラン、트래킹 플랜. Follows anchor → draft → refine → token → upload five-phase workflow. Deliverable is a real tracking plan created in the AE platform.
Extracts and analyzes tweet history from competitor or brand Twitter profiles using apidojo's Twitter Profile Scraper on Apify. Triggers when the user asks to: get all tweets from a competitor's Twitter account, analyze what a company posts on Twitter, audit a brand's tweet history, track what topics a competitor covers on X, compare Twitter content strategy between brands, extract posts from a company's Twitter timeline, or monitor a competitor's messaging and announcements on Twitter. Returns tweet text, engagement metrics (likes, retweets, replies, views), and author data. Ideal for competitive intelligence teams, PR analysts, and brand strategists.
Install, load, and unload SAS packages with the SAS Packages Framework (SPF) and the SASPAC archive — package fileref rules, %installPackage / %loadPackage / %helpPackage / %unloadPackage, and version pinning. Use when installing a package such as sasjscore or debugging an installation that reports rc=20006 or a missing package zip
Interactive generation of AE tracking code, LogBus2 configuration, and debug scripts from a tracking plan. Trigger words: 代码埋点、埋点代码、tracking code、埋点落地、logbus 配置、AE 上报代码、generate tracking code、insert tracking、トラッキングコード、트래킹 코드. Supports independent output mode selection per platform (insert/snippet). Server-side defaults to LoggerConsumer + LogBus2 architecture.
Use when a Metabase data app needs to trigger a write or mutation — submitting a form, updating a row, deleting an entry, running a saved action, or any "do something" interaction. Covers invoking an existing action via `useAction`, parameter typing, response handling, and the critical post-action refresh of any UI data the action may have changed.
Analyzes a competitor's YouTube channel content strategy and performance using apidojo's YouTube scraper on Apify. Triggers when the user asks to: analyze what a competitor posts on YouTube, see what video types perform best for a competitor, reverse-engineer a competitor's YouTube content calendar, benchmark your YouTube channel against a competitor, identify content gaps vs. a competitor on YouTube, understand what topics drive views for a competitor, or compare subscriber growth and video performance between two YouTube channels. Returns video cadence, format mix, top-performing topics, view benchmarks, and engagement analysis. Ideal for content marketing teams, YouTube strategists, and brand video teams.
Salesforce Industries CME EPC product-modeling skill for Product2-based catalog creation. Use when creating EPC products, configuring product attributes, building offer bundles with Product Child Items, or reviewing EPC DataPack JSON metadata for product catalog changes. TRIGGER when: the user creates or updates Product2 EPC records, AttributeAssignment payloads, AttributeMetadata/AttributeDefaultValues, Offer bundles, or ProductChildItem relationships. DO NOT TRIGGER when: designing OmniScripts/FlexCards/Integration Procedures (use sf-industry-commoncore-* skills), implementing Apex business logic (use sf-apex), or troubleshooting deployment pipelines (use sf-deploy).
Scrapes comments from any YouTube video using apidojo's YouTube scraper on Apify. Triggers when the user asks to: get all comments on a YouTube video, export YouTube comment data, scrape what viewers say about a YouTube video, fetch comment text and likes from a YouTube URL, collect comment threads from a YouTube video, or download audience feedback from a YouTube video. Returns commenter username, comment text, like count, reply count, and timestamp per comment. Ideal for sentiment researchers, product teams, and content analysts
Scrapes comments from any TikTok video using apidojo's TikTok Comments scraper on Apify. Triggers when the user asks to: get all comments on a TikTok video, export TikTok comment data, scrape what viewers are saying on a TikTok post, fetch comment text and likes from a TikTok URL, collect TikTok comment threads for analysis, or download comments from a viral TikTok video. Returns commenter username, comment text, like count, reply count, and timestamp per comment. Ideal for sentiment analysts, brand monitors, and content researchers.
Extracts TikTok posts tagged at a specific location using apidojo's TikTok Location Scraper on Apify. Triggers when the user asks to: get TikTok videos from a specific location, scrape TikTok posts tagged at a place, find TikTok content from a city or venue, collect TikTok videos geotagged at a location URL, export TikTok location-tagged content, or pull TikTok posts from a place page. Returns video title, views, likes, comments, shares, channel info, hashtags, and timestamp per post. Ideal for local marketing teams, event researchers, and geo-targeting analysts.
Use when working in a project that depends on @prisma/orm-postgres, @prisma/orm-sqlite, or @prisma/orm-mongo (Prisma 8, formerly Prisma Next): editing contract.prisma or a contract.ts builder, running `prisma contract emit`, planning or applying migrations, editing migration.ts, writing db.orm / db.sql / db.query queries, wiring db.ts or middleware, integrating a build tool, using the Supabase extension or RLS, or reading a dotted error code such as MIGRATION.HASH_MISMATCH. Use when the user asks "what is Prisma 8", "where do I start", or compares it to another ORM. Use when the user asks to upgrade or bump Prisma 8 in an app or an extension package. Use when you see @internal/* or @prisma/orm-* imports, prisma.config.ts with definePrismaConfig, or contract.json / contract.d.ts. Do not use for Prisma ORM 7 or earlier (schema.prisma + @prisma/client).
Analyzes a competitor's TikTok content strategy and top-performing videos using apidojo's scrapers on Apify. Triggers when the user asks to: see what content a competitor posts on TikTok, analyze which TikTok videos perform best for a brand, reverse-engineer a competitor's TikTok strategy, find out how often a competitor posts and what gets the most engagement, study a brand's TikTok presence, compare TikTok content strategies across competing brands, or find out what topics a competitor covers on TikTok. Returns video topics, post frequency, avg views, top hooks, hashtags used, and engagement patterns. Ideal for social media strategists, content teams, and competitive intelligence analysts.
Monitors and aggregates brand mentions on Twitter/X using apidojo's Tweet and Search scrapers on Apify. Triggers when the user asks to: track mentions of a brand on Twitter, find what people are saying about a company on X, monitor brand sentiment on Twitter, set up brand mention tracking, find customer complaints or praise about a product on Twitter, analyze brand reputation based on tweets, or measure share of voice on X compared to competitors. Returns tweet text, author, engagement metrics, sentiment signals, and timestamps per mention. Ideal for brand managers, PR teams, community managers, and reputation analysts.
Convert any data file to another format: CSV, Parquet, JSON, Excel, GeoJSON, and more. Use when the user says "convert to parquet", "save as xlsx", "export as JSON", "make this a CSV", "turn into parquet", or any variation of format-to-format conversion for data files. Also triggers when the user wants to write Parquet, Excel, or other binary formats that Claude cannot produce natively.
Scrapes Twitter/X profile data for any list of usernames using apidojo's Twitter User scraper on Apify. Triggers when the user asks to: get profile data for Twitter accounts, fetch follower counts for a list of usernames, scrape Twitter bio and stats for multiple users, export Twitter profile metadata, check account details for a set of handles, or bulk-fetch Twitter user information. Returns username, display name, bio, follower count, following count, tweet count, verified status, and profile URL. Ideal for data analysts, list enrichment pipelines, and market researchers.
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g. adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization. Use when analyzing marketing campaigns, ad performance, attribution models, conversion rates, or calculating marketing ROI, ROAS, CPA, and campaign metrics across channels.
Tracks brand sentiment across Twitter, Reddit and TikTok simultaneously using apidojo's scrapers on Apify. Triggers when the user asks to: monitor brand reputation across social platforms, track how people talk about a brand on multiple channels, compare brand sentiment on Twitter vs Reddit vs TikTok, get a cross-platform brand health score, monitor product launch reactions across social media, measure overall public sentiment for a brand, or build a multi-platform social listening dashboard for a brand. Returns per-platform sentiment distribution, cross-platform score, top positive/negative posts, and theme analysis. Ideal for brand managers, CMOs, PR teams, and reputation management agencies.
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.