Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
CLI for querying Prometheus and PromQL-compatible engines (Thanos, Cortex, VictoriaMetrics, Grafana Mimir, Grafana Tempo...) — instant queries, range queries, metric discovery (metrics/labels/meta subcommands), output formats (table/csv/json/graph). Apply when executing PromQL queries, troubleshooting performance issues on a software having observability, investigating latency/error rates/saturation, or analyzing time series data.
Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results
Generate financial statements (income statement, balance sheet, cash flow) with period-over-period comparison and variance analysis. Use when preparing a monthly or quarterly P&L, closing the books and need to flag material variances, comparing actuals to budget, building a financial summary for leadership review, or looking up GAAP presentation requirements and period-end adjustments.
Sets up and manages ClickHouse using the clickhousectl CLI—installs and runs a local ClickHouse server for development, and creates managed ClickHouse Cloud services for production (authentication, service creation, schema migration, application connection). Use when the user wants to build an application with ClickHouse, set up a local ClickHouse dev environment, create tables and start querying, deploy ClickHouse to production or ClickHouse Cloud, or migrate from a local setup to the cloud.
Set up, audit, verify, or fix website conversion tracking. Use when the conversion is a form submission, booked meeting, chat, phone call, signup, or purchase; when conversions must reach Google Ads, Meta, GA4, LinkedIn, TikTok, or Microsoft Ads; when the work involves GTM tags and dataLayer events, pixels, the Conversions API (CAPI), Enhanced Conversions, server-side tagging, or gclid and fbclid capture; or when the user reports conversion problems like "conversions stopped", "double counting", "spend but no conversions", "GA4 and Google Ads don't match", or an Unverified or Inactive status. Covers lead gen and ecommerce. Always fire on confirmed success, never the submit click; verify a test conversion arrives; diagnose before changing anything; offer free and native paths alongside paid ones and disclose partner tools. For tracking plans and UTMs, see analytics. For attribution models, see attribution. For campaigns and bidding, see ads. For CRM lead-stage design, see revops.
Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations
Use when a user wants to build an application with ClickHouse, set up a local ClickHouse development environment, install ClickHouse, create a local server, create tables, or start developing with ClickHouse. Covers the full flow from zero to a working local ClickHouse setup.
Query central bank economic statistics time series and 100 key indicators—including base rates, exchange rates, the consumer price index, and money supply—through the Bank of Korea ECOS Open API. Use when the user asks about base rates, exchange rate trends, price indexes, M2, government bond yields, or macroeconomic statistics. Not for stock prices (korean-stock-search) or general KOSIS statistics (kosis-stats).
Provides guidance for migrating Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers migration to Airflow 2.11.1 (MSAA Gen 2 and 3) and Airflow 3 (MSAA Gen 3), including environment inspection, GCS download/upload and scanning patterns for breaking changes. Use when migrating the DAG code to newer Airflow version. Don't use when checking DAG run failures unrelated to code migration.
Retrieve authoritative guidance on Amazon Timestream for InfluxDB across its supported engine variants. Applicable to any InfluxDB-on-AWS request, including engine variant and licensing selection, provisioning and IAM, encryption at rest (AWS-owned and customer-managed KMS keys, key policies, and key lifecycle), schema design (tags vs fields, cardinality, HTTP/sensor/metric data modeling), migration from LiveAnalytics, Processing Engine plugins, connectivity (database endpoints and private or public access), and write/query errors.
Help developers new to Elasticsearch get from zero to a working search experience. Guide them in understanding their intent, mapping their data, and building a search experience with best practices built in. Use when users want to build search functionality, ask about Elasticsearch concepts for their use case, or need help getting started with Elasticsearch.
Set up Grafana Cloud Database Observability for MySQL and PostgreSQL — enables `pg_stat_statements` / Performance Schema, creates a least-privilege monitoring user, configures the `database_observability.postgres` / `database_observability.mysql` Alloy components, ships query samples + visual explain plans + RED metrics + schema details to Grafana Cloud, and correlates slow queries with application traces via `db.statement` / `db.system` OTel attributes. Use when monitoring database performance, diagnosing slow queries, setting up DB observability for RDS / Aurora / Cloud SQL / Azure Database / self-managed instances, correlating DB metrics with APM, or alerting on query latency — even when the user says "my database is slow", "find the slow queries", or "monitor RDS" without saying "observability".
Design robust, scalable database schemas for SQL and NoSQL databases. Provides normalization guidelines, indexing strategies, migration patterns, constraint design, and performance optimization. Ensures data integrity, query performance, and maintainable data models
Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced X For You algorithm. Use when building any system that picks "the top K items for a (user, context)" — content feeds, search ranking, RAG rerankers, task prioritizers, notification triage, ad selection.
Cut Grafana Cloud Metrics cost by shrinking active-series count with Adaptive Metrics aggregation rules — auto-recommendations from query history, custom exact/regex rules, label-drop config, unused-metric detection, and Alloy remote_write fallback. Use when investigating a high Mimir/Grafana Cloud bill, hunting high-cardinality labels (`pod_uid`, `service_instance_id`, `version`), pre-aggregating counters/gauges, dropping unused metrics, or measuring `grafanacloud_instance_active_series` before/after — even when the user says "reduce cardinality", "too many series", "metrics spend", "active series count is exploding", or "drop the version label" without naming Adaptive Metrics.
Use when fine-tuning LLMs, training custom models, or adapting foundation models for specific tasks. Invoke for configuring LoRA/QLoRA adapters, preparing JSONL training datasets, setting hyperparameters for fine-tuning runs, adapter training, transfer learning, finetuning with Hugging Face PEFT, OpenAI fine-tuning, instruction tuning, RLHF, DPO, or quantizing and deploying fine-tuned models. Trigger terms include: LoRA, QLoRA, PEFT, finetuning, fine-tuning, adapter tuning, LLM training, model training, custom model.
Provides guidance for authoring Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers environment context discovery, Airflow 2 vs 3 compatibility, authoring best practices, and local/remote validation processes. Use when creating or extending an Airflow DAG. Don't use when authoring Python code unrelated to Airflow DAGs
Find the Prometheus metrics that drive your Grafana Cloud bill. `dpm-finder` is a Grafana Professional Services CLI that ranks metrics by Data Points per Minute (DPM) with per-label-set breakdown, optional `--cost-per-1000-series` pricing, and a Prometheus-exporter mode. Use when investigating high Grafana Cloud spend, hunting noisy / high-cardinality metrics, comparing pre/post recording-rule cardinality, or feeding cost data into dashboards — even when the user says "why is my Mimir bill so high?", "find the biggest metrics", "cardinality offenders", or "optimize Prometheus cost" without naming dpm-finder
Provides comprehensive NestJS framework patterns with Drizzle ORM integration for building scalable server-side applications. Generates REST/GraphQL APIs, implements authentication guards, creates database schemas, and sets up microservices. Use when building NestJS applications, setting up APIs, implementing authentication, working with databases, or integrating Drizzle ORM.
Use this skill when authoring PolicyRuleDefinition and PolicyRuleDefinitionSet metadata XML for Salesforce Data Cloud governance policies, or when editing *.policyRuleDefinition / *.policyRuleDefinitionSet files. Covers the category decision tree, full schema for all policy variants (ACCESS, GOVERNANCE, RECORD, TRANSFORM), UI-compatibility rules for the Data Governance Policy Builder, output hygiene for user-facing agent responses, and validation guardrails. Do NOT use this skill for UserAccessPolicy, AccessPolicy, SharingRules, PermissionSet, or any other access-control metadata type — those have their own types and live outside the PolicyRuleDefinition schema.
Implement, review, or improve data persistence using SwiftData. Use when defining @Model classes with @Attribute, @Relationship, @Transient, #Unique, or #Index; when querying with @Query, #Predicate, FetchDescriptor, or SortDescriptor; when configuring ModelContainer and ModelContext for SwiftUI or background work with @ModelActor; when planning schema migrations with VersionedSchema and SchemaMigrationPlan; when setting up CloudKit sync with ModelConfiguration; or when coexisting with or migrating from Core Data.
Turn on AI + ML features in Grafana Cloud — Grafana Assistant (NL → PromQL/LogQL/TraceQL, dashboard build, incident investigation, MCP integration), Dynamic Alerting (Prophet forecasting + DBSCAN outlier detection), Sift (8-analysis automated root-cause), Knowledge Graph + RCA Workbench, and the LLM Plugin (OpenAI / Anthropic / Azure / Ollama / vLLM / LiteLLM). Use when you want anomaly alerts without static thresholds, natural-language querying, automated incident investigation, dashboards generated from a sentence, or a managed LLM proxy for plugins — even when the user says "alert when something looks weird", "explain this PromQL", "find the root cause", "make this a dashboard", or "wire Claude into Grafana" without naming any of these products.
Your AI agent's crypto brain. One skill, 100+ commands across 14 data domains — real-time prices, wallets, DeFi, on-chain SQL, prediction markets, and more. Natural language in, structured data out. Install once, access everything. Use whenever the user needs crypto data, asks about prices/wallets/tokens/DeFi, wants to investigate on-chain activity, or is building something that consumes crypto data — even if they don't say "surf" explicitly.
Turbo pipeline YAML reference and architecture guide. Covers: YAML field syntax (start_at, from, version, primary_key), source/transform/sink configuration, validation errors, resource sizing (xs–xxl), architecture decisions (dataset vs kafka, streaming vs job, fan-out vs fan-in, sink selection, pipeline splitting). Triggers on: 'what does field X do', 'what fields does a postgres sink need', 'what resource size', 'should I use kafka or dataset', 'how to structure my pipeline'. For writing transforms, use /turbo-transforms. For end-to-end building, use /turbo-builder.
Quantitative strategy frameworks: pairs trading/cointegration, volatility regime strategies, seasonality/calendar effects, multi-factor models (IC/IR), factor research and screening, correlation analysis, statistical methods (ADF/GARCH), strategy optimization, execution modeling, hedging, and ML-based prediction (sklearn). Also provides CLI access to run indicator scripts against K-line data. Triggers: "量化", "因子", "配对交易", "协整", "波动率策略", "季节性", "多因子", "IC", "机器学习", "对冲", "量化策略", "協整", "波動率策略", "季節性", "多因子", "對沖", "quant", "pairs trading", "cointegration", "volatility strategy", "seasonality", "multi-factor", "factor model", "IC IR", "machine learning", "hedging", "walk-forward", "配對交易", "機器學習", "因子選股"
Professional stock price tracking, fundamental analysis, and financial reporting tool. Supports global markets (US, KR, etc.), Crypto, and Forex with real-time data. (1) Real-time quotes, (2) Valuation metrics (PE, EPS, ROE), (3) Earnings calendar and consensus, (4) High-quality Candlestick & Line charts with technical indicators (MA5/20/60).
Build and deploy new Goldsky Turbo pipelines: requirements, dataset selection, YAML, validation, and deployment. Use for 'build a pipeline', 'index X on Y chain', or moving chain/contract data into Postgres, MySQL, ClickHouse, Kafka, Pub/Sub, S3, SQS, or webhooks. Also use for data goals such as Polymarket fills/positions/PnL, prediction markets, stablecoin or circulating supply, proof of reserves, sanctions/AML transfer monitoring, deposit detection, CCTP burns/mints, cross-chain settlement, payment reconciliation, wallet history streamed into the user's own database, token holder registries, tokenized equities/RWA, and wash-trading detection. A REST lookup of one wallet's balances or transfers is /feeds, not a pipeline, and so is a read of Polymarket activity, positions or balances. Debug existing pipelines with /turbo-doctor; look up syntax with /turbo-pipelines.
Synthesize user research into themes, insights, and recommendations. Use when you have interview transcripts, survey results, usability test notes, support tickets, or NPS responses that need to be distilled into patterns, user segments, and prioritized next steps.
Use this skill when the user needs to look up or verify Goldsky blockchain dataset names, chain prefixes, dataset types, or versions. Triggers on questions like 'what\'s the dataset name for X?', 'what prefix does Goldsky use for chain Y?', 'what version should I use for Z?', or 'what datasets are available for Solana/Stellar/Arbitrum/etc?'. Also use for chain-specific dataset questions (e.g., polygon vs matic prefix, stellarnet balance datasets, solana token transfer dataset names), and to answer 'is there a dataset for X?' where X is a domain rather than a chain — decoded logs, token transfers and balances, mint/burn events for circulating supply, DEX or prediction-market activity (Polymarket), or the raw blocks, transactions and traces behind wallet history and reconciliation. Do NOT trigger for questions about CLI commands, pipeline setup, or general Goldsky architecture unless the core question is about finding the right dataset name or chain prefix. Wallet Feeds API queries are /feeds.
Write SQL, TypeScript, and dynamic table transforms for Turbo pipelines. Covers: decoding EVM logs with _gs_log_decode, filtering/casting blockchain data, UNION ALL for combining events, TypeScript/WASM transforms (invoke function), dynamic lookup tables (dynamic_table_check), transform chaining, and Solana decoding. Triggers on: 'decode Transfer events', 'write a SQL transform', 'filter by contract', 'TypeScript transform', 'dynamic table', 'UNION ALL'. For pipeline YAML structure, use /turbo-pipelines. For end-to-end building, use /turbo-builder.
Diagnose and fix broken Goldsky Turbo pipelines interactively. Triggers on: pipeline in error state, stuck starting, connection refused, not getting data, duplicate rows, missing fields, slow backfill, or any named pipeline misbehaving. Runs logs/status commands, identifies root cause, and offers fixes. For CLI syntax or error pattern lookup without an active problem, use /turbo-operations instead.
Use this skill whenever a task involves a document file (PDF, DOCX, PPTX, XLSX, or image) and you need to read it or pull text, tables, or specific values out of it — to answer a question about its contents, look up a figure, or extract data. Provides fast, local, model-free extraction via the `lit` CLI with disciplined, low-cost search patterns.
Turbo pipeline operations reference — lifecycle commands (pause, resume, restart, delete), pipeline states, checkpoint behavior, streaming vs job-mode differences, CLI syntax for `inspect`/`logs`, TUI shortcuts, and error pattern lookup. Triggers on: 'how do I pause/restart/delete', 'will deleting lose my data', 'what does this error mean', 'inspect TUI shortcuts'. For interactive diagnosis of a broken pipeline, use /turbo-doctor.
Provides patterns to implement persistence layers with Spring Data JPA. Use when creating repositories, configuring entity relationships, writing queries (derived and `@Query`), setting up pagination, database auditing, transactions, UUID primary keys, multiple databases, and database indexing.
Use this skill when the user asks about Goldsky Mirror pipelines — creating, deploying, operating, or troubleshooting Mirror. Triggers on: 'Mirror pipeline', 'goldsky pipeline apply', 'sync subgraph to database', 'mirror vs turbo', 'direct indexing', 'mirror pipeline YAML', 'mirror pipeline pause/stop/restart'. Also use this skill when the user wants to sync a Goldsky subgraph into a database or message queue — Mirror is the only pipeline product that supports subgraph sources. For new pipelines that don't need a subgraph source, the turbo-builder skill is usually a better fit. Do NOT trigger on 'goldsky turbo' commands or generic 'build a pipeline' requests without subgraph context — those belong to the turbo skills.
Diagnose and fix broken Goldsky Mirror pipelines. Use this skill whenever a Mirror pipeline is failing, stuck, terminated, won't start, is in a restart loop, or is blocked by an in-flight request. Also use it when the user mentions a specific Mirror pipeline name alongside a problem—even if they don't say “mirror” explicitly, if they're using `goldsky pipeline` commands (not `goldsky turbo`), this is the right skill. Runs CLI commands directly to check status, read errors, identify the root cause, and apply fixes. For YAML syntax or config reference, use /mirror instead. For turbo pipeline problems, use /turbo-doctor instead
This skill should be used when the user asks to "find a dashboard", "search dashboards", "does a dashboard exist for X", "find widgets that query Y", "which dashboards use this field", "find a dashboard about errors", "look up dashboards by description", "search for existing monitoring dashboards", "find widgets that reference a field", or wants to discover existing Coralogix dashboards or widgets using natural-language or field-based search.
Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.
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.
Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.
Use to create, generate, or validate Salesforce Custom Report Type metadata. Trigger on custom report types, CRTs, cross-object reports, report builder data sources, exposing fields for reporting across related objects, inner vs outer joins in reports, report type categories, or deployment errors for .reportType-meta.xml files. Do NOT trigger for running, editing, or filtering existing reports; creating report folders, dashboards, or list views; or non-authoring reporting questions.
Build, author, and deploy Goldsky Subgraphs—hosted GraphQL APIs over onchain data. Use when the user wants to create, scaffold, write, or deploy a subgraph; design a schema/entities; write or fix AssemblyScript mapping handlers; configure subgraph.yaml (handlers, templates, instant/no-code from ABI); set up GraphQL endpoints, tags, or webhooks; optimize a slow subgraph (eth_calls, immutable entities); or pause/resume a subgraph. Triggers on: 'build/deploy/scaffold a subgraph', 'write a mapping', 'design a schema', 'subgraph.yaml', 'instant subgraph', 'combine/compose/merge multiple subgraphs', 'cross-chain subgraph', 'optimize indexing speed', 'too many eth_calls', 'pause/resume subgraph'. For a subgraph that is failing, stalled, erroring, or won't deploy, use /subgraph-doctor (optimizing a healthy subgraph belongs here, not the doctor). For migrating off The Graph, use /subgraph-migrate. For streaming raw chain data to a DB without GraphQL, use /turbo-builder.
Diagnose and fix broken Goldsky Subgraphs. Use this skill whenever a user has a subgraph that is failing, stalled, stuck syncing, not indexing, auto-paused, returning errors, or won't deploy. Triggers on: 'subgraph stopped syncing', 'subgraph stuck at block', 'subgraph stalled', 'subgraph failed to deploy', 'indexing error', 'SubgraphSyncingFailure', 'unexpected null in handler', 'no network found', 'deployment already exists', 'subgraph not returning data', 'subgraph endpoint 404', 'reached the subgraph limit', 'rate limited'. Also use when the user names a subgraph alongside a problem. Runs CLI commands directly to check status, read logs, identify root cause, and apply fixes. For building, authoring, deploying, endpoint/tag reference, or optimizing a healthy-but-slow subgraph (e.g. too many eth_calls), use /subgraph-builder instead. For migrating from The Graph, use /subgraph-migrate instead.
Use this skill to create, generate, or validate Salesforce Custom Field metadata. Trigger when users mention custom fields, field types, Roll-up Summary fields, Master-Detail relationships, Lookup relationships, formula fields, picklists, or field metadata. Also use for field deployment errors, especially involving Roll-up Summary formats, Master-Detail constraints, or formula issues. Always use this skill for custom field metadata work, field generation, or field troubleshooting.
Migrate a subgraph from The Graph to Goldsky as a drop-in replacement — no code changes required. Use this skill when the user wants to move, switch, port, or migrate a subgraph off The Graph (hosted service, Subgraph Studio, or the decentralized network) onto Goldsky, or when a subgraph endpoint they relied on (e.g. The Graph hosted service) was sunset. Triggers on: 'migrate from The Graph', 'move my subgraph to Goldsky', 'switch off The Graph', 'redeploy a TheGraph subgraph', 'my subgraph endpoint is gone', 'from-url', 'from-ipfs-hash', 'drop-in replacement for The Graph'. For diagnosing a subgraph that fails after migrating, use /subgraph-doctor. For building/authoring or general deploy/tag/endpoint reference, use /subgraph-builder.
Use this skill to create, generate, or validate Salesforce Custom Object metadata. Trigger when users mention custom objects, creating objects, object metadata, .object files, sharing models, name fields, or validation rules on objects. Also use when users say “create a custom object,” “generate object metadata,” “set up an object for...,” or troubleshoot object deployment errors, especially involving sharing models and Master-Detail relationships. Always use this skill for custom object metadata work.
Guide users through configuring key MongoDB MCP server options. Use this skill when a user has the MongoDB MCP server installed but hasn’t configured the required environment variables, or when they ask about connecting to MongoDB/Atlas and don’t have the credentials set up
Implement, review, or improve data visualizations using Swift Charts. Use when building bar, line, area, point, pie, donut, or iOS 26 3D charts; adding chart selection, scrolling, annotations, axes, scales, legends, or foregroundStyle grouping; plotting functions with BarPlot, LinePlot, AreaPlot, PointPlot, Chart3D, or SurfacePlot; or creating heat maps, Gantt charts, grouped bars, sparklines, threshold lines, or spatial visualizations
Extracts the full national store dataset from the Small and Medium Business Administration public commercial-district (상가) information files (unverified) based on industry-type and store-name keywords, matches store name plus coordinates against historical snapshots, and extracts a list of long-lived stores that 'existed years ago and are still operating'. Uses store names rather than business registration numbers, and provides a lower bound based on the earliest observation date rather than the opening date.
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.