Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Forward-looking spend extrapolation. Computes a USD-per-day rate from the recent measurement window, projects to 7d/30d/90d/365d horizons, and surfaces "days until budget exhausted" when a budget is configured. Predictive counterpart to `cost-budget-check` (reactive).
Per-message cost breakdown within a single session. The drill-down companion to cost-anomaly — when an outlier session is flagged, this surfaces the specific expensive messages so operators can see whether the cost came from output tokens, cache writes, or model escalations.
Youying Shopee product selection tool. Supports product searches and filtering across all Shopee sites, covering 11 markets including Malaysia, Taiwan, Indonesia, Thailand, the Philippines, Singapore, Vietnam, Brazil, Mexico, Chile, and Colombia. Trigger this skill when users mention Shopee product selection, Shopee product search, Shopee bestsellers, Shopee market analysis, Shopee category selection, Shopee keyword selection, Shopee sales filtering, Shopee price filtering, Southeast Asian e-commerce product selection, Shopee product search, Shopee product selection, Shopee bestsellers, or Shopee market analysis. Even if the user does not explicitly mention "Youying" or "Shopee", trigger this skill whenever their request involves searching for products on Shopee or filtering Shopee product data.
Onboard a user to Wren Engine end-to-end. Walks through environment checks, project scaffolding, connection configuration via .env, and first query. Use when: user wants to install Wren Engine, set up a new data source connection, or bootstrap a new project from scratch. Triggers: '/wren-onboarding', 'install wren', 'set up wren engine', 'wren onboarding', 'connect new database to wren'
Create, view, and manage Alibaba Cloud DTS data migration or synchronization tasks interactively. Automatically triggered when the user mentions keywords such as “DTS task”, “DTS migration”, “DTS sync”, “data migration task”, “data sync task”, “create migration”, “create DTS”, “new DTS”, “DTS status”, “migration status”, “sync status”, “stop migration”, “suspend DTS”, or “release DTS”.
MAD-based outlier detection on session spend. Robust to the very outliers it hunts (unlike mean+sigma). Surfaces specific anomalous sessions with modified-z scores; optional --alert-on-outliers exit code for CI gates. Distinct from cost-burn (aggregate trend) — this answers "which INDIVIDUAL session is the outlier?".
Burn-rate trend over time with optional drift-alert exit code. Bins session spend into buckets, surfaces window-over-window delta, and can exit 1 when latest bucket exceeds prior mean by a configurable %. Distinct from `cost-trend` (benchmark drift); this tracks PRODUCTION spend trajectory.
Defines database performance monitoring strategies with slow-query detection, resource-usage alerts, query-execution thresholds, and automated alerting. Use for “database monitoring,” “performance alerts,” “slow queries,” or “DB metrics.”
PostgreSQL and Drizzle ORM best practices. Triggers on: PostgreSQL, Postgres, Drizzle, database, schema, tables, columns, indexes, queries, migrations, ORM, relations, joins, transactions, SQL, drizzle-kit, connection pooling, N+1, JSONB, RLS. Use when writing database schemas, queries, migrations, or any database-related code. Proactively apply when creating APIs, backends, or data models.
An agent orchestrator for cross-border e-commerce product sourcing. Use this skill when the user needs a complete Temu product selection workflow, five recommended products, or end-to-end product analysis. It automatically calls skills such as amazon-movers-shakers, temu-competitor-search, ali1688-sourcing, and temu-pricing-calculator to produce a complete product selection report meeting the V4.1 standard.
This skill should be used when working with single-cell omics data analysis using scvi-tools, including scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics, and other single-cell modalities. Use this skill for probabilistic modeling, batch correction, dimensionality reduction, differential expression, cell type annotation, multimodal integration, and spatial analysis tasks.
Alibaba Cloud AnalyticDB for MySQL operations and diagnosis assistant. Supports cluster information queries, performance monitoring, slow query diagnosis, running SQL analysis, table-level optimization suggestions, and more. Triggers: “ADB MySQL,” “AnalyticDB,” “cluster list,” “slow query,” “BadSQL,” “data skew,” “idle index,” “SQL Pattern,” “space diagnosis,” “table diagnosis,” “performance monitoring.”
Generate a test suite of natural-language → SQL pairs that becomes the quality benchmark for a nao agent, then run it via `nao test`. Use when the user wants to start measuring agent reliability, extend an existing test suite, or add tests for new metrics. Tests are the only honest answer to "is the context working?". Do not use for writing rules (write-context-rules) or diagnosing failures (audit-context).
Use when the user is working with the Spree 6 product catalog — products, variants, option types/values, the default variant, product types (templates), categories vs collections, custom fields, media (images, video, media library), channel publications, search providers (database, spree_meilisearch, custom), digital assets, or catalog imports/exports. Common phrasings include "create a product", "add variants", "size and color options", "product type", "category tree", "collection", "brand", "custom field on products", "product images", "product video", "primary_media", "product not showing in store", "publish product on channel", "Meilisearch", "reindex", "custom search provider", "digital download", "master variant". Covers the catalog graph and how to read/write it from Ruby, the Admin SDK and `spree api`
Find and evaluate research datasets for any scientific question. Maps research questions to required study designs (longitudinal vs cross-sectional, observational vs experimental, single-cohort vs multi-cohort). Use when the user asks 'find data about X', 'where can I get data on Y', or needs a specific cohort/survey/repository. Covers GEO, ArrayExpress, dbGaP, NHANES, UK Biobank, ClinicalTrials.gov, GWAS Catalog, and 30+ scientific repositories.
Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guide the user through the full flow: install dlt, choose a SaaS source, set up credentials, run the data pipeline into DuckDB, then automatically generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
Analyze application logs from the .evlog/logs/ directory. Use when debugging errors, investigating slow requests, understanding request patterns, or answering questions about application behavior. Reads structured NDJSON wide events written by evlog's file system drain.
Expert knowledge for Azure Database for PostgreSQL development, including troubleshooting, best practices, decision-making, architecture and design patterns, limits and quotas, security, configuration, integrations and coding patterns, and deployment. Use when working with Flexible Server, pgvector/AI search, Private Link/TLS, PITR/restore, or replicas/sharding, and for other Azure Database for PostgreSQL-related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), or Azure Database for MySQL (use azure-database-mysql)
Manage DatoCMS records, uploads, and project automation through the Content Management API (CMA). Use for content reads/edits, publish/unpublish, bulk imports/exports, CSV scripts, localization, Structured Text and block edits, assets, roles/tokens, webhooks, scheduling, environment operations, and typed Node.js/TypeScript CMA scripts. Includes short follow-ups such as “publish them” or “fix those slugs”, token/OAuth setup before content operations, and model/field changes needing a migration-versus-direct decision or embedded in CMA automation. Works with the CLI or an available DatoCMS MCP; neither MCP installation nor local execution is assumed. Route schema-inspection-only requests, versioned migrations, and standalone CLI configuration to `datocms-cli`, GraphQL reads to `datocms-cda`, and frontend or plugin code to their dedicated skills.
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
Write and revise queries with the published HelixDB Go SDK v0.3.1. Use for normal functions returning `helix.Request`, `ReadQuery`/`WriteQuery`, inline params, traversal builders, projections, indexes, vector and BM25 search with traversal-scoped prefiltering, and server execution through `Client.Exec`. The module remains `github.com/helixdb/helix-db/sdks/go` without a `/v3` suffix; standard installs do not ship embedded or native-graph bindings. Stored routes and query bundles are not supported. When the target is Helix Cloud, always use helix-mcp first
Compare keyword search popularity and analyze trends with Google Trends, supporting global regions and custom time ranges. Trigger this skill when users mention Google Trends, keyword popularity over time, search interest comparisons, keyword trend analysis, seasonal trend detection, regional search popularity, keyword heatmaps, comparisons of multiple keywords on Google, Google Trends, keyword popularity comparison, search trends, seasonal analysis, regional popularity, or keyword comparison. Trigger it even if users do not explicitly say “Google Trends” as long as their request involves comparing keyword search popularity trends across different time periods or regions.
Bootstrap a nao agent for a project: gather warehouse, scope, and extra-context info in one round; look up the warehouse-specific config from nao docs; write nao_config.yaml; run nao init + nao sync; set up the LLM key; and generate the first RULES.md. Use when the user has just decided to use nao on a new project. Only for first-time setup; for editing rules, generating tests, or reviewing an existing context, use write-context-rules / create-context-tests / audit-context.
Use when the user wants to design or redesign the Dataverse schema and connector plan for an existing mobile app, or has an ER diagram (image, Mermaid, or text) to apply. Skip when the user is creating a brand-new app — /create-mobile-app handles the data model inline.
Diagnose the health of a nao context at any stage of its lifecycle. Use when the user wants a structured review of what's been synced, how RULES.md compares to the target structure, whether every table is documented, whether the data model is MECE, whether tests exist and what their failures reveal, and whether context files are bloated. Outputs a structured audit report with ranked recommendations. Do not use for first-time setup (setup-context) or routine rule writing (write-context-rules).
Builds document embedding pipelines with text chunking, embedding generation, indexing, and retrieval optimization. Use when users request “embedding pipeline,” “document indexing,” “text chunking,” “RAG preprocessing,” or “semantic indexing”
Analyze mental health data, identify psychological patterns, assess mental health status, and provide personalized mental health recommendations. Supports correlation analysis with other health data such as sleep, exercise, and nutrition.
Extracts structured resources from a webpage with the web CLI: icons (SVGs classified as icon or logo and optimized for AEM Edge Delivery Services /icons/), metadata and Open Graph tags, body text, forms, videos, and social links. Use when migrating pages to Edge Delivery Services, auditing a site, or extracting a page's icons, metadata, or other assets
A discipline for designing experiments (A/B tests, multivariate, holdouts) so the results actually answer the question you asked. Hypothesis writing, sample size, duration, segment analysis, running discipline, matching a result to a pre-committed decision rule, and the common failure modes that produce confidently wrong shipping decisions. Use this skill whenever the user is planning a test that has not run yet: framing a hypothesis, sizing the sample, setting duration, choosing guardrails, or deciding whether something is worth testing at all. Triggers on design an experiment, experiment plan, A/B test, split test, multivariate test, holdout, experiment hypothesis, sample size, minimum detectable effect, MDE, test duration, guardrail metric, no peeking, pre-committed decision rule, is this worth testing. Use `experimentation-analytics` instead when the test has already run and the question is how to read the result panel.
Guides exploration of $autocapture events captured by posthog-js to understand user interactions, find CSS selectors (especially data-attr attributes), evaluate selector uniqueness, query matching clicks ad-hoc, and create actions. Use when the user asks about autocapture data, wants to find what users are clicking, needs to build actions from click events, asks about elements_chain, wants to build a trend or funnel filtered by clicks or other autocapture interactions, asks which properties autocapture sends, or asks how to filter $autocapture events. Only applies to projects using posthog-js autocapture.
Use the HelixDB v3 `helix` CLI to manage local Docker/Podman instances and discover Helix Cloud with WorkOS session authentication, including resource management, queries, shell, status, and logs. Use for helix init/add/start/stop/query/shell/auth/workspace/project/cluster/database/service-credential/api and helix.toml. Cloud CLI authentication is WorkOS-only; never provide API keys or service credentials as CLI login. Defer query body authoring to helix-query-* skills.
How to actually instrument product analytics correctly. Event taxonomy, property design, naming conventions, schema versioning, identity stitching, funnel design, retention cohorts, North Star metric selection, dashboard hygiene, instrumentation debt, and the failure modes that produce data nobody trusts. Triggers on product analytics setup, event taxonomy, tracking plan, instrumentation, schema versioning, North Star metric, retention cohorts, funnel design, naming conventions, instrument new feature, audit existing analytics, dashboard reconciliation, instrumentation debt, Mixpanel setup, Amplitude setup, PostHog setup, warehouse-native analytics. Also triggers when the team has data but cannot trust it, or when designing instrumentation for a new feature, or when auditing an existing setup that has drifted.
Extract structured data (all available fields with values) from a page saved locally as an HTML file, optionally following a schema. Do not invoke when the user provides a URL. When invoking, pass the user's full request verbatim as args — do not pre-parse file paths and don't rephrase it.
Drug and chemical toxicity assessment via adverse outcome pathways (AOPs), real-world FAERS adverse event signals, FDA labels, toxicogenomic associations, and EPA CompTox quantitative hazard/high-throughput bioactivity data. Triangulates molecular initiating event to cellular outcome to organ-level toxicity to clinical adverse event. Use for hepatotoxicity/cardiotoxicity/nephrotoxicity prediction and toxicology reports.
Running experiments out of the data warehouse instead of via dedicated experiment platforms. SQL-based assignment, exposure logging discipline, metric definitions in dbt models, statistical analysis in SQL or Python, variance reduction with CUPED, sequential testing, and the operational tradeoffs vs platforms like Statsig and Optimizely. Triggers on warehouse-native experimentation, run experiments in BigQuery, run experiments in Snowflake, dbt experiments, SQL t-test, CUPED variance reduction, exposure log, sample ratio mismatch, sequential testing, mSPRT, doubly robust estimation, build vs buy experimentation. Also triggers when the team is choosing between platform and warehouse, building warehouse-native experiment infrastructure, auditing one, or running an experiment with a custom metric the platform cannot handle.
Use this skill for planning, testing, and safely executing PostgreSQL schema migrations — especially when working with production data or shared databases. Trigger when user asks to: Test a schema migration before applying it to production; add, remove, or rename columns safely on a live table; change a column's data type without downtime; add or drop indexes, constraints, or foreign keys on large tables; understand which ALTER TABLE operations lock the table; roll back a failed migration; plan a zero-downtime migration strategy; or fork a database to test a migration safely. Keywords: migration, schema change, ALTER TABLE, add column, drop column, rename column, change type, zero downtime, lock, AccessExclusiveLock, concurrent index, forking, rollback, backfill, deploy. Covers lock-level reference for every common DDL operation, safe migration patterns, fork-based testing, zero-downtime column changes, index creation, constraint addition, backfill strategies, pre/post-migration validation, and rollback planning.
Expert framework for assessing and achieving product-market fit. Combines PMF measurement methodologies, Sean Ellis survey, retention analysis, segment-specific PMF, and post-PMF scaling strategy. Use when determining if product has PMF, measuring user engagement, running PMF surveys, or deciding whether to scale or keep iterating.
Expert sales operations and analytics guidance for revenue teams. Use when designing CRM workflows, building sales dashboards, optimizing pipeline analytics, creating lead routing rules, designing territories, calculating commissions, managing data quality, building forecasting models, or integrating sales tech stack. Covers Salesforce, HubSpot, Outreach, Gong, and RevOps best practices.
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.