Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Builds Nango Functions in a checked-out Zero YAML TypeScript Nango project using local files, index.ts registration, nango dryrun, generated tests, and optional nango deploy via CLI. Use when creating, updating, validating, testing, or deploying Nango actions or syncs locally in a repo. This content overlaps with building-nango-functions but adds CLI workflow details, so load this instead of building-nango-functions whenever a local project, local files, Nango root, CLI, dryrun, generated tests, or nango deploy workflow is indicated.
Firebase gives you a complete backend in minutes—auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they’re often wrong. Firestore queries are limited, and you learn this after you’ve designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. I
Discover Amazon products and identify potential bestsellers using Jiimore data. Trigger this skill when the user mentions product mining, potential bestsellers, high-conversion product selection, click growth analysis, market growth opportunities, keyword-based product selection, FBA profitability screening, niche product discovery, seller source filtering, product mining, potential bestsellers, high-conversion product selection, market growth opportunities, Jiimore data, FBA profitability screening, or keyword-based product selection. Even if the user does not explicitly mention “Jiimore,” trigger this skill when their request involves keyword-driven Amazon product selection based on conversion rates, click volume, and profit metrics.
Use Jungle Scout to find keywords by ASIN. Enter up to 10 ASINs to retrieve all keywords they appear for in Amazon search results, along with search volume, competition, PPC bids, and other data across 10 marketplaces. Trigger this skill when the user mentions reverse ASIN keyword lookup, ASIN keyword mining, competitor keywords, ASIN traffic keywords, reverse ASIN lookup, ASIN search terms, keyword expansion, ASIN keyword databases, competitor traffic analysis, keyword by ASIN, reverse keyword lookup, or related terms. Trigger it even if the user does not explicitly mention “Jungle Scout” or “reverse lookup,” as long as they want to find keywords associated with an ASIN or analyze competitor keywords.
Query historical keyword search volume with Jungle Scout, returning precise Amazon keyword search volume trends in 7-day intervals across 10 marketplaces, including the US, UK, Germany, and Japan. Trigger this skill when the user mentions keyword search volume trends, historical search volume, changes in search popularity, keyword seasonality, search volume fluctuations, Jungle Scout search volume, keyword search volume history, keyword trend, search volume over time, seasonal search volume, or keyword popularity trend. Trigger it even if the user does not explicitly mention “Jungle Scout,” as long as they want to see how an Amazon keyword’s search volume changes over time.
Route BigQuery-backed Looker Studio work into one stakeholder-reporting packet: dashboard-spec, slow-dashboard triage, refresh-shape choice, audience split, or exec-handoff. Use when the user needs KPI boards, PM/ops reviews, marketing / GTM reporting, product funnel summaries, or game/live-ops telemetry dashboards on top of curated BigQuery data. Route KPI explanation to `data-analysis`, repeated anomaly hunting to `pattern-detection`, telemetry/alerting coverage to `monitoring-observability`, and semantic-platform choice to `survey`.
Market research specialist focused on comprehensive market analysis, consumer behavior insights, and market opportunity identification. Excels at quantitative market sizing, qualitative consumer research, and strategic market positioning analysis.
Gene-set enrichment analysis — GO (Biological Process, Molecular Function, Cellular Component), KEGG, Reactome pathway enrichment via clusterProfiler, gseapy, ORA, GSEA, plus g:Profiler for enrichment/ID conversion/ortholog mapping/SNP-to-gene annotation. Use for interpreting DEG lists, screen hit lists, or any gene-list-to-pathways query. Includes simplify-cutoff handling and union-vs-total denominator conventions for percent-DE questions.
Integrate Firecrawl into application code whenever a product, agent, or workflow needs web data inside the app — web search, live search results, page scraping, structured extraction, or browser interaction. Use when building any feature that needs data from the web in code, even if the user does not mention Firecrawl explicitly and only describes wanting web data, website content, search, scraping, or interaction in an application. Trigger for Firecrawl requests, "fire girl" shorthand, and generic app-level web-data needs that should map to `/scrape`, `/search`, or `/interact`. Do not use this skill for one-off terminal-only web tasks during the current session; use `firecrawl/cli` for those.
Sets up and optimizes Managed PostgreSQL on Render—connection strings (internal vs external), creation constraints, storage autoscaling, connection limits, high availability, read replicas, backups, and MCP inspection. Use when the user mentions Postgres, PostgreSQL, Render database, connection string, DATABASE_URL, backups, snapshots, replicas, HA, disk storage, connection pooling, or troubleshooting DB connectivity.
Jungle Scout keyword Share of Voice analysis returns brand voice share across the top 3 pages of Amazon search results (organic/sponsored/combined), exact 30-day search volume, median PPC bids, and TOP3 ASIN click and conversion data across 10 marketplaces. Trigger this skill when users mention brand market share, brand voice share, brand distribution in search results, Share of Voice, SOV analysis, brand competitive landscape, ad placement share, organic ranking brand share, PPC bid analysis, brand dominance analysis, keyword share of voice, brand visibility, organic vs sponsored share, brand dominance, PPC bid analysis, search result brand distribution, competitive landscape, weighted SOV, or top ASIN clicks conversions. Trigger this skill even if the user does not explicitly mention "Share of Voice" or "SOV," as long as their request involves analyzing brand market share or the competitive landscape in the search results for an Amazon keyword.
PostgreSQL database design, migration, and performance optimization best practices. This skill should be used when writing, reviewing, or refactoring database schemas, migrations, or query patterns. Triggers on tasks involving PostgreSQL databases, schema design, migration optimization, or data modeling
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).
Institutional and TradFi crypto exposure analysis covering public company holdings (MicroStrategy, Tesla, etc.), Bitcoin and Ethereum ETF flows, and institutional accumulation patterns. Use when the user asks about institutional adoption, ETF flows, corporate treasuries, what institutions are buying, or MicroStrategy holdings.
Prisma ORM expert for schema design, migrations, query optimization, relations modeling, and database operations. Use PROACTIVELY for Prisma schema issues, migration problems, query performance, relation design, or database connection issues.
Query Walmart product details through WallySmarter, including price history and sales trends. Trigger this skill when the user mentions Walmart product details, Walmart product data, WallySmarter, Walmart price trends, Walmart sales trends, Walmart product detail, Walmart price history, Walmart sales trend, or WallySmarter product. Trigger it even if the user does not explicitly mention "WallySmarter," as long as they want to view details, historical price changes, or sales trends for an individual Walmart product.
Implements Syncfusion Blazor SfDataManager for data access, data binding, and adaptor configuration in Blazor Server, WebAssembly, and Web App. Used when binding components like SfGrid and SfDropDownList to local or remote data sources, choosing adaptors (UrlAdaptor, ODataAdaptor, WebApiAdaptor, GraphQLAdaptor), or performing CRUD. Includes custom binding using DataAdaptor, DataManagerRequest, DataOperations, and the Syncfusion.Blazor.Data package.
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis
Inspects PostHog Web analytics Live tab data — current users online, last-30-minutes pageviews, top pages, referrers, devices, browsers, countries, bot traffic, and the per-minute bot/users charts. Use when the user asks "who is on my site right now?", "what is happening live?", "what bots are crawling me?", asks about the "live tab" / "live dashboard", wants live numbers (last 30 min), or wants help filtering or drilling into the live view. Also covers building product-analytics insights that mirror what the tiles show.
Integrate Firecrawl `/interact` into product code for dynamic pages and browser actions after scraping. Use when a feature needs clicks, form fills, pagination, authentication-aware flows, or other multi-step interactions that plain `/scrape` cannot complete.
Guides experiment state transitions: launching, pausing, resuming, freezing/unfreezing exposure, ending, shipping variants, archiving, resetting, duplicating, copying to another project, and migrating a legacy experiment to the new experiments engine. Covers preconditions, implications for variant assignment and analysis, and the decision framework for when to use each action. TRIGGER when: user asks to launch, pause, resume, end, ship, archive, reset, duplicate, or copy an experiment to another project, to freeze/unfreeze exposure (stop enrolling new users while metrics keep flowing, or reopen enrollment), or to migrate, convert, move or upgrade a legacy experiment to the new engine or the new metric format. DO NOT TRIGGER when: user is creating an experiment (use creating-experiments), configuring rollout (use configuring-experiment-rollout), or setting up metrics (use configuring-experiment-analytics).
Use when automating SAP BW query inspection, InfoProvider metadata reads (characteristics, key figures), metadata-verified specification review, unsaved draft preparation, or human-confirmed query draft population through Eclipse or HANA Studio with BW Modeling Tools.
Stock and cryptocurrency data analysis. Analyze A-share, Hong Kong, and U.S. market quotes, technical indicators, financial data, fund flows, chip distribution, cryptocurrency candlesticks and long-short ratios, the overall market, sector rotation, and portfolio holdings
Guides agents through experiment creation: reading the project's setup with experiment-setup-context, defining the hypothesis, configuring rollout and bucketing, setting up analytics and running time, and reporting which choices are guesses. Delegates rollout decisions to configuring-experiment-rollout and metric setup to configuring-experiment-analytics.\nTRIGGER when: user asks to create a new experiment or A/B test, OR when you are about to call experiment-create.\nDO NOT TRIGGER when: user is updating an existing experiment, managing lifecycle, or only browsing experiments.
Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment (“split test demo,” “the File engagement boost experiment,” “onboarding retention test,” “landing page hero experiment,” “pricing experiment”), describes it loosely (“the signup experiment,” “my pricing test,” “the one with the new checkout”), uses a relative reference (“latest,” “most recent,” “the one I created yesterday”), filters by status (running, draft, paused, exposure frozen, stopped, archived), or otherwise refers to an experiment by anything other than its concrete ID.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Design storage-model and migration-safety packets for relational, document-heavy, and hybrid data systems. Use when the user needs entity ownership, constraints, indexes, staged schema changes, or queryable-vs-flexible field decisions across backend/fullstack products, internal ops tools, marketing/customer-data workflows, or game/live-ops systems. Route API contracts to api-design, auth-owned identity/session modeling to authentication-setup, verification to backend-testing, and reporting/telemetry follow-through to looker-studio-bigquery or monitoring-observability.
Implement Syncfusion Blazor Accumulation Chart (SfAccumulationChart) for proportional data visualization. Use this when creating pie charts, doughnut charts, funnel charts, or pyramid charts. This skill covers data labels, legends, tooltips, slice grouping, and part-to-whole visualizations in Blazor applications.
Creates comprehensive dashboard and analytics interfaces that combine data visualization, KPI cards, real-time updates, and interactive layouts. Use this skill when building business intelligence dashboards, monitoring systems, executive reports, or any interface that requires multiple coordinated data displays with filters, metrics, and visualizations working together.
A-share value investing analysis tool offering stock screening, in-depth individual stock analysis, industry comparisons, and valuation calculations. Based on value investing theory, it uses tushare to obtain public financial data and is suited to ordinary investors with a low trading frequency
Use when comparing physical Android benchmark configurations, investigating inconsistent rankings, or selecting an Android default from measured results. Do not use for code-level Compose performance diagnosis without a configuration comparison
Configures the analytics side of a PostHog experiment — exposure criteria (server-resolved default exposure event vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude from analysis" vs "Use first seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a secondary metric tracking 'downloaded_file' per user"), sets up a ratio metric (e.g. "revenue from purchase_completed / pageviews"), sets up a retention metric (e.g. "$pageview → uploaded_file, 7-day window"), configures custom exposure (e.g. "only count users who hit /checkout"), changes multivariate handling, or asks "who is in the analysis?", "how do I measure impact?", "is this winning?", "what's the confidence level?", or "should I ship?"
Access US stock market data including price bars, news with sentiment, and company details via eng0 data API. Use when user asks for stock prices, OHLCV data, price history, stock news, or company information. Triggers include "stock price", "price history", "OHLCV", "stock news", "company info", "market data", "ticker data". Do NOT use for SEC filings (use sec-edgar-skill instead).
Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video
/c-level-agents:cdo-review [plan] — Decision-driven Chief Data Officer interrogation of any plan that touches training data, data architecture, data productization, or data team hiring. Use when validating training-data rights before model work, choosing warehouse vs lakehouse vs mesh, or valuing data assets for productization or M&A.
This skill should be used when building data processing pipelines with CocoIndex, a Python library for incremental data transformation. Use when the task involves processing files/data into databases, creating vector embeddings, building knowledge graphs, ETL workflows, or any data pipeline requiring automatic change detection and incremental updates. CocoIndex is Python-native (supports any Python types), has no DSL, and uses version 1.0.0 or later.
Broad DeFi market overview combining category rankings, chain comparison, total TVL trends, top protocols, and market events. Use when the user asks for a market summary, "what's happening in DeFi", weekly recap, overall market state, DeFi dashboard, or wants a high-level snapshot of the ecosystem.
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.