Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Use when creating Autonomous Databases, troubleshooting connection failures, managing PDBs, or optimizing database costs. Covers connection string confusion, password validation errors, stop/start cost traps, clone type selection, and backup retention gotchas.
Monitor, inspect, and query saved Fabric Dataflows Gen2 with read-only CLI. List dataflows, decode mashup.pq/queryMetadata.json/.platform, inspect parameters, refresh status, job history, staging, and destinations, or run saved/ad-hoc read-only executeQuery requests and parse Arrow. Handle explicit requests to mutate through the Dataflows consumption or read-only path by refusing the write; offer `dataflows-authoring-cli` only after separate confirmation. For candidate M before persistence or connection configuration, use `dataflows-authoring-cli`. Triggers: "list dataflows", "inspect dataflow", "decode dataflow definition", "dataflow parameters", "refresh history", "last refresh status", "dataflow job history", "execute dataflow query", "executeQuery saved query", "executeQuery fetch rows", "ad-hoc dataflow query", "parse Arrow response", "Arrow IPC", "dataflow staging analysis", "use Dataflows consumption path to delete", "Dataflows read-only mutation refusal", "separate Dataflows authoring handoff".
Audit a PostHog A/B experiment for a customer — verify config, exposure, attribution, and metrics. Trigger phrases include \"audit [customer]'s experiment\", \"audit the [name] experiment\", \"check experiment setup for [customer]\", \"validate this A/B test\", or any request to review whether an experiment is correctly wired up. Assumes you already have MCP access to the customer's project (typically via the impersonation flow set up by the `impersonate-audit` wrapper that ships with this plugin).
Audit EVERY Google Search Console property at once — rank all sites by clicks and impressions with period-over-period deltas, then diff keywords per site to surface what is newly ranking, rising, dropping, lost, or ranking well without earning clicks. Built for agencies and multi-site owners. Use when asked to compare all sites, rank properties by traffic, find new keywords across a portfolio, or spot which site is down. Trigger phrases: "audit GSC", "all my sites", "rank my properties", "portfolio search performance", "which sites are down", "what new keywords are we ranking for", "client site performance", "GSC report across accounts". For ONE site's queries, pages, or index coverage, use the search-console skill instead.
Query Kubernetes, infrastructure and cloud-provider metrics from KubeSense with PromQL/MetricsQL — metric discovery, label inspection, the metric families KubeSense actually collects (kube-state-metrics, cAdvisor, node-exporter, OTel hostmetrics, DCGM GPU, JVM, and AWS/GCP/Azure/MongoDB Atlas/Confluent/Kong cloud resources), and the label conventions (clusterId, kubesense_cloud_resource_metric) needed to write a query that returns data.
Use Sorftime to research Walmart US categories: get the full category tree, match relevant NodeIds by natural-language category name, or query category market data and Best Seller products using an underscore-separated NodePath. Use when the user mentions Walmart category tree, category name search, category matching, category nodes, NodeId, NodePath, category market analysis, category research, category size, category best sellers, Best Seller, or needs to locate a category before researching the market.
Use Sorftime to research the Walmart US keyword market, reverse-lookup keywords from names, search-result products, keyword details, product related and expanded keywords, and manage saved keyword folders. Use when the user mentions Walmart keyword research, filtering by search volume or ranking, product keyword reverse lookup, related keywords, keyword details, keyword search-result products, saved keywords, keyword groups, keyword research, keyword discovery, related keywords or product keywords.
Use Sorftime to search Walmart US products by natural-language name, or query product details, product trends and daily sales. Use when the user mentions Walmart product name search, finding products by name, related products, ProductId, product details, price, rating, category ranking, product trends, historical changes, sales trends, variant sales, daily sales, yesterday's sales, competitor discovery or competitor tracking.
Operate Milvus vector database with pymilvus Python SDK. Use when the user wants to connect to Milvus, create collections, insert vectors, perform similarity search, hybrid search, full-text search, manage indexes, partitions, databases, or RBAC via Python code.
Reduce the memory footprint and cost of Materialize compute clusters: find where arrangement memory sits, pick and size the right optimization lever (index strategy, GROUP SIZE hint tuning, view slimming, subquery decorrelation), adjudicate proposed index or view changes, run measured experiments safely, and package verified changes. Use when a Materialize cluster or replica uses too much memory or is OOMing or crash-looping, when the user wants to downsize a replica or cut Materialize spend, when deciding which indexes to add or drop, or when tuning GROUP SIZE hints.
Pure Python DICOM for medical imaging (CT, MRI, X-ray, ultrasound). Read/write DICOM, pixels as NumPy, edit tags, windowing (VOI LUT), PHI anonymization, build DICOM, series→3D volumes. Use histolab for WSI pathology; nibabel for NIfTI.
Use when running a Roboflow Workflow over many images or videos with batch processing — Asset Library jobs (the platform stages workspace images for you) or staged jobs (you stage external local/cloud files with the inference-cli), plus monitoring jobs, downloading results, and routing imports to datasources (bucket mirror) instead.
Generate n8n workflows that use the official ScraperAPI community node (n8n-nodes-scraperapi-official). Use this skill whenever the user wants to build, design, automate, or scaffold an n8n workflow that scrapes the web through ScraperAPI — even when they don't say "skill" or "ScraperAPI node" by name. Triggers include: "build an n8n workflow that monitors Amazon prices", "create an n8n flow to scrape Google search daily", "generate an n8n JSON for a crawler that hits this site", "wire ScraperAPI into n8n to email me product reviews", "n8n automation for Walmart price tracking", "use ScraperAPI in n8n to enrich leads", "give my n8n AI Agent web access via ScraperAPI", "add ScraperAPI as a tool to my n8n agent", "build an AI parser in n8n to extract custom fields from a site". Produces either importable workflow JSON or a step-by-step build guide in the n8n editor, picking the format based on how the user phrased the request. Covers the api, sde, crawler, and AI Parser resources. Note: Transmits user-supplied queries, URLs, and content to ScraperAPI.
Best-practices reference for the ScraperAPI Ruby SDK (scraperapi gem). Consult whenever the user is writing, debugging, or reviewing Ruby code that calls ScraperAPI. Use when user asks: "scrape a website with Ruby and ScraperAPI", "ScraperAPI Ruby example", "how do I use the ScraperAPI gem", "Ruby ScraperAPI render", "ScraperAPI Ruby premium proxy", "ScraperAPI gem sessions", "ScraperAPI Ruby error handling". Covers gem setup, all request parameters, the escalation ladder, error handling by status code, and credit costs. Note: Transmits user-supplied queries, URLs, and content to ScraperAPI.
Use Scry's read-only SQL research surface (/v1/scry/schema, /v1/scry/query) for bounded SQL over the public internet and vector helpers. Also use when a research ask wants diverse, orthogonal sources, angles, hypotheses, or probe phrasings — includes the enumeration discipline and the /v1/creativity/outsized fan-out.
Generate Mermaid diagrams from Salesforce metadata and architecture. Reads org metadata, Apex classes, Flow XML, and object definitions to produce ERDs, class diagrams, sequence diagrams, flow visualizations, and deployment dependency graphs. Activate on "diagram", "visualize", "ERD", "sequence diagram", "class diagram", "flowchart", "data model", or "architecture diagram". DO NOT activate for PNG/SVG image rendering or non-Salesforce systems.
High-volume, asynchronous offline inference at up to 50% lower cost via Together AI's Batch API. Prepare JSONL inputs, upload files, create jobs, poll status, and download outputs. Reach for it whenever the user needs non-interactive bulk inference rather than real-time chat or evaluation jobs.
UX measurement: HEART framework, SUS, UEQ, SUPR-Q, task success and time-on-task metrics, A/B testing statistics, AI-specific metrics, and design system ROI. Use when defining UX KPIs, building a measurement plan, interpreting a usability score, or proving UX impact.
Use when you must prove an analysis ran on the intended data or lock a dataset version. Builds a deterministic content-hash manifest (file SHA-256, schema, per-column value hashes), verifies later copies against it for drift, and diffs two manifests.
Extract metadata and content from WeChat Official Account articles. Use when user needs to parse WeChat article URLs (mp.weixin.qq.com), extract article info (title, author, content, publish time, cover image), or convert WeChat articles to structured data. Supports various article types including posts, videos, images, voice messages, and reposts.
When the user wants to analyze why deals were won or lost, find patterns across closed deals, or extract competitive intelligence from deal outcomes. Trigger phrases: 'why did we lose that deal,' 'win-loss review,' 'analyze our closed deals,' 'what are we losing to,' 'deal post-mortem,' 'why do we keep losing to [competitor],' 'deal autopsy,' 'competitive losses,' 'why did we win that deal.' For individual call analysis, see call-debrief. For competitive positioning, see competitive-intel. For buyer understanding, see buyer-persona.
X (Twitter) data extraction and monitoring via Xquik: tweet search, user lookup, follower extraction, giveaway draws, trending topics, account monitoring with webhooks, reply/retweet/quote extraction, community and Space data, follow checks. 22 MCP tools + REST API.
Use when managing Alibaba Cloud Data Lake Formation (DlfNext) via OpenAPI/SDK, including the user needs DLF Next catalog/governance resource operations, including listing resources, create/update flows, status checks, and troubleshooting metadata workflow issues.
Resource saturation from system.metrics, system.events and system.asynchronous_metrics - memory, load average, connections, running queries, background pools, parts per partition, block device queues - plus short history. Use when the server feels slow or overloaded, queries queue or get rejected, or load and connection trends are needed.
Bilibili comment analysis tool. Enter a Bilibili video link or BV number to fetch top-level comment data, with paged browsing, comment sentiment analysis (positive/negative/needs/competitor), and generation of a polished HTML report. Use when the user needs to view Bilibili video comments, analyze comment sentiment, or understand user feedback. Trigger words: Bilibili comments, Bilibili video comments, comment query, comment analysis, comment sentiment, read comments, bilibili comments.
Convex backend guidance for queries, mutations, actions, schema, validators, auth, components, agents, search, testing, production config, and client/server integration. Use whenever interacting with a Convex backend, including Convex functions, schema changes, HTTP endpoints, scheduling, storage, AI features, or framework integration.
Use when the user asks to create a custom post type, build a portfolio, set up case studies, add team members, events, or podcast episodes, or says 'scaffold a CPT'. Creates the post type plus supporting taxonomies, an ACF field group, sample entries, and a builder-specific single template suggestion.
ETL/ELT pipelines, data warehousing (BigQuery, Snowflake, Redshift), stream processing (Kafka, Spark Streaming), orchestration (Airflow, Dagster, Prefect), dbt transformations, and data lake architecture. Use when building data pipelines, designing warehouse schemas, or implementing real-time data processing.
Orchestrate a new Splunk data source from requirements and supported collection-method selection through source, sourcetype, host, timestamp, event-boundary, indexed-event, ownership, and acceptance validation. Use for Splunk Cloud Platform or Splunk Enterprise source intake, applicability decisions, readiness, acceptance contracts, and exact implementation handoffs; do not use for endpoint setup, ingest troubleshooting, fleet rollout, pipeline architecture, field or CIM implementation, configuration, deployment, mutation, or remediation.
Connect to a hospital's FHIR R4 server (Epic, Oracle Health/Cerner, MEDITECH, athenahealth, or any SMART-on-FHIR endpoint), pull a patient's clinical data and notes, and extract structured findings. Use when users say "connect to the EHR", "connect to Epic/Cerner", "pull notes for patient X", "what do the last 6 months of notes say about Y", or any task that starts from a live EHR rather than pasted text.
Use this skill whenever the user's main ask is on-chain, protocol, or Web3 behavior (not a pure safety verdict). Covers address and token on-chain analysis, platform metrics, reserves, heatmaps, stablecoins, bridges; optional news/UGC. Legacy alias: gate-info-defianalysis. Delegate: gate-info-risk (safety), gate-info-research (broad research), gate-news-intel (events/sentiment). v0.7.6+ shortcuts (+address-tracker, +token-onchain, +community-scan); legacy fallback below 0.7.6.
Designs and builds knowledge graphs from unstructured or semi-structured data sources. Guides through data model selection (LPG, RDF, hypergraph, temporal), schema design, entity/relation extraction pipelines, and layered architecture construction. Use when designing knowledge graphs, choosing between LPG vs RDF, planning entity extraction, designing graph schemas, aligning ontologies, building a KG for RAG, or when user mentions knowledge graph construction.
Open, create, read, analyze, edit, or validate Excel/spreadsheet files (.xlsx, .xlsm, .csv, .tsv). Use when the user asks to create, build, modify, analyze, read, validate, or format any Excel spreadsheet, financial model, pivot table, or tabular data file. Covers: creating new xlsx from scratch, reading and analyzing existing files, editing existing xlsx with zero format loss, formula recalculation and validation, and applying professional financial formatting standards. Triggers on 'spreadsheet', 'Excel', '.xlsx', '.csv', 'pivot table', 'financial model', 'formula', or any request to produce tabular data in Excel format.
Guidance for implementing high-performance portfolio optimization using Python C extensions. This skill applies when tasks require optimizing financial computations (matrix operations, covariance calculations, portfolio risk metrics) by implementing C extensions for Python. Use when performance speedup requirements exist (e.g., 1.2x or greater) and the task involves numerical computations on large datasets (thousands of assets).
Guides use of the Qdrant Migration Tool CLI to move vectors, metadata, and sparse embeddings from another vector database into Qdrant. Use when someone asks 'how do I migrate from Pinecone/Weaviate/Milvus/Elasticsearch/OpenSearch/pgvector/s3/Azure/Chroma/Redis/MongoDB/FAISS/Solr to Qdrant', 'move my vector database to Qdrant', 'is there a migration tool for Qdrant', 'my migration got interrupted, how do I resume it', 'migration is too slow', or 'collection wasn't created after migration'. Also use when picking migration batch size, deciding on `--net=host`, or verifying data after a migration.
Write ClickHouse queries for SigNoz dashboards over OpenTelemetry logs and traces. Use this skill whenever the user asks for SigNoz ClickHouse queries for logs or traces, SigNoz dashboard queries, log analysis, span counts, latency, or trace breakdowns.
Manage Fabric Warehouse, Lakehouse SQL endpoints, and Mirrored Databases: DDL/DML, COPY INTO, read-only T-SQL, Query Insights diagnostics, and Capacity Metrics CU-spike correlation. Synapse migration target SQL belongs to synapse-migration; Fabric SQL database belongs to sqldb-cli. Triggers: query warehouse, create warehouse table, failed or canceled query, CU spike, Capacity Metrics app, custom SQL pool, Lakehouse table health.
Microsoft SQL Server specific features. Covers data types, indexes, partitioning, and SQL Server-specific syntax. Use for SQL Server database work. USE WHEN: user mentions "sql server", "mssql", "IDENTITY", "GETDATE()", "temporal tables", "columnstore", "SQL Server specifics", "Azure SQL" DO NOT USE FOR: T-SQL programming - use `tsql` instead, PostgreSQL - use `postgresql` instead, Oracle - use `oracle` instead
Guides and best practices for working with Neon Serverless Postgres. Covers getting started, local development with Neon, choosing a connection method, Neon features, authentication (@neondatabase/auth), PostgREST-style data API (@neondatabase/neon-js), Neon CLI, and Neon's Platform API/SDKs. Use for any Neon-related questions.
Help with modern ABAP SQL features and AMDP (ABAP Managed Database Procedures) including inline declarations, window functions, GROUP BY, HAVING, PRIVILEGED ACCESS, string functions, aggregate expressions, common table expressions (CTE), AMDP classes, AMDP procedures, AMDP table functions, CDS table functions, and AMDP scalar functions. Use when users ask about ABAP SQL, modern SQL, SELECT, window functions, CTE, common table expression, AMDP, SQLScript, AMDP table function, CDS table function, aggregate, GROUP BY, HAVING, UNION, INTERSECT, EXCEPT, PRIVILEGED ACCESS, ABAP SQL expressions, built-in SQL functions, or database procedures. Triggers include "ABAP SQL query", "window function", "CTE", "AMDP", "table function", "GROUP BY", "aggregate", "PRIVILEGED ACCESS", "inline SELECT", or "SQLScript".
Diagnoses ClickHouse external dictionaries - load status, memory usage, layout choice, reload staleness, source connectivity and lookup performance. Use for dictionary load failures, FAILED or LOADING_FAILED status, stale dictionary data, high dictionary RAM and slow dictGet lookups.
Diagnoses ClickHouse RAM usage, memory limits, OOM errors and the allocation breakdown across queries, caches, dictionaries and primary keys. Use when MEMORY_LIMIT_EXCEEDED appears, the server is killed by the OOM killer, memory grows steadily, or GROUP BY and JOIN queries run out of memory.
Diagnose ClickHouse replication health, Keeper connectivity, read-only replicas, replica lag, replication queue backlog and slow fetches. Use for replication lag, read-only replica problems, growing replication queues, failed fetches, or Keeper/ZooKeeper session and latency errors.
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.