Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Lucene searchQuery cheatsheet for DAM search_media_library. Use when the user describes assets in everyday language (brand, campaign, region, status, colour, rating, SKU) or when building or debugging a search, filter, or list of ImageKit files and folders.
Alibaba Cloud Bailian Knowledge Base Retrieval Tool. Use HTTPS API to query and retrieve knowledge base content. Use when: User needs to query knowledge base, retrieve document content, or answer questions based on knowledge base. Prerequisites: (1) Configure DashScope API Key (2) Activate Bailian Knowledge Base service.
Core bioinformatics concepts including SAM/BAM format, AGP genome assembly format, sequencing technologies (Hi-C, HiFi, Illumina), quality metrics, and common data processing patterns. Essential for debugging alignment, filtering, pairing issues, and AGP coordinate validation.
ARK-style single-stock disruptive-innovation diagnostic. Suitability gate on 4 dimensions (platform fit / innovation revenue / R&D intensity / management vision); if it passes, builds TAM (low/base/high), Wright's-Law cost curve with sourced learning rate, three-scenario 5-year target (Bull/Base/Bear, 15% discount), risks, conditional action frame. Data: Longbridge CLI first, MCP fallback, WebSearch only for TAM / learning rates / industry runway. Runs cross-statement reconciliation BEFORE analysis. Closes with a data-source appendix whose final row is the reconciliation summary. Independent implementation — not affiliated with ARK Invest. Triggers: "木头姐", "ARK", "ARKK", "颠覆式创新", "莱特定律", "TAM", "5年目标价", "情景分析", "AI 与大数据", "自动化与机器人", "能源存储", "基因革命", "区块链与金融科技", "木頭姐", "顛覆式創新", "萊特定律", "5年目標價", "Cathie Wood", "ARK Invest", "disruptive innovation", "Wright's Law", "learning rate", "bull base bear", "scenario analysis".
Search academic papers via the OpenAlex API for open citation data, institutional affiliations, and funding information. Use when the user says "openalex search", "search openalex", "open citation graph", or wants comprehensive academic metadata beyond arXiv/Semantic Scholar
Monitorar e manter a documentação completa da persistência em .specsfy/DATABASE.md, com inventário tabular de bancos, schemas, tabelas, campos, relações e migrations. Use quando o monitor de contexto apontar persistência pendente, sempre que banco, tabela, coleção, model persistente, coluna, índice, relação, schema ou migration for criado ou alterado, e ao auditar se o mapa de dados corresponde ao código. Preserva notas e decisões humanas fora do inventário detectado.
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.
This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.
QVeris provides professional data and tool access for AI. Use standardized capabilities/query for qveris_finance.* CAP workflows, or discover/call for specialized services such as real-time data, historical sequences, structured reports, web extraction, PDF workflows, media generation, OCR, TTS, translation, and more. Requires QVERIS_API_KEY.
Using SurrealDB with the Python SDK, covering both client/server mode (WebSocket) and embedded mode (in-memory or file-based). Use when connecting to SurrealDB from Python, using the surrealdb Python package, running SurrealDB embedded without a server, or performing CRUD operations from Python code. Triggers: surrealdb Python, Surreal(), AsyncSurreal(), Python SDK, embedded SurrealDB, mem://, file://.
Develop ZenStack V3 plugins. Use when building or declaring a plugin — custom ZModel attributes/functions, CLI code generators (CliPlugin with a generate callback for `zen generate`), or runtime plugins installed via $use/definePlugin (onQuery, onKyselyQuery, onEntityMutation hooks, extending the client, custom query args, computed result fields).
Alibaba Cloud RDS Copilot intelligent operations assistant skill. Used for RDS-related intelligent Q&A, SQL optimization, instance operations, and troubleshooting. Calls RdsAi OpenAPI through Alibaba Cloud CLI to get real-time RDS Copilot responses. Triggers: "RDS Copilot", "RDS Assistant", "SQL optimization", "RDS troubleshooting", "RDS operations", "database diagnosis"
Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.
Design, build, and maintain comprehensive knowledge bases. Bridges document-based (RAG) and entity-based (graph) knowledge systems. Use when building knowledge-intensive applications, managing organizational knowledge, or creating intelligent information systems.
Database schema design for PostgreSQL/MySQL with normalization, relationships, constraints. Use for new databases, schema reviews, migrations, or encountering missing PKs/FKs, wrong data types, premature denormalization, EAV anti-pattern.
This skill filters stocks based on criteria such as market and financial indicators; queries stocks and listed companies in specified industries or sectors, as well as the constituents of sector indexes; and supports related tasks such as recommending stocks, listed companies, sectors, and indexes, helping prevent LLMs from using outdated information when selecting stocks.
Universal scraper for any OpenWeb Ninja API. Scrape jobs, business listings, products, reviews, news, social profiles, finance data, and more. Use for lead generation, market research, competitor analysis, content monitoring, price tracking, or any structured data extraction task.
Set up, configure, and manage a ZenStack V3 project. Use when installing ZenStack, scaffolding a new project, or running the `zen` CLI (generate). (For database schema migrations use zenstack-db-migration; to migrate a Prisma project use zenstack-migrate-from-prisma; to upgrade from ZenStack V2 use zenstack-migrate-from-v2.)
Expert in product selection, listing, and business opportunity trends on 1688. Use to: (1) search for products and suppliers on 1688; (2) check linked downstream stores; (3) list products on platforms such as Douyin, Pinduoduo, Xiaohongshu, and Taobao; (4) configure 1688 AK keys; (5) view real-time business opportunity rankings; (6) view category/industry trends and price distributions; (7) generate daily store operations reports and product selection recommendations for main products. Triggers: find products for me, search 1688, product selection, listing products, list a product, check stores, configure AK, business opportunities, hot list, ranking, trends, price distribution, daily operations report, daily store report, sales analysis, operations analysis, product selection recommendations, find products on 1688.
Analyze session replay patterns across experiment variants to understand user behavior differences. Use when the user wants to see how users interact with different experiment variants, identify usability issues, compare behavior patterns between control and test groups, or get qualitative insights to complement quantitative experiment results. Also covers pairing the observed behavior with a linked survey when the user wants qualitative feedback beyond what recordings show
Runs the Metabase semantic checker against a tree of Representation Format YAML files to verify that all references resolve — cross-entity references (collection_id, dashboard_id, parent_id, parameter source cards, snippet references, transform tags, etc.) and references to columns inside MBQL and native queries. Slow (≥1 min per run). Only use when the user explicitly asks to verify entity references or column references in MBQL/SQL queries; in most cases this runs as a CI step, not locally. Requires database metadata on disk (by default `.metadata/table_metadata.json`)
Audit PostHog experiments and feature flags for configuration issues, staleness, and best-practice violations. Read when the user asks to audit, health-check, or review experiments or feature flags, check flag hygiene, or verify experiment setup.
Search and filter Amazon products using SellerSprite data with multidimensional criteria including price, monthly sales, BSR rank, gross margin, rating, shipping method, tags, and seller source, across multiple Amazon marketplaces. Trigger this skill when users mention Amazon product research or selection, product filtering, sales filtering, product discovery, BSR analysis, niche product discovery, competitor analysis, market opportunity assessment, product-level market sizing, gross margin filtering, SellerSprite product selection, Amazon product selection, sales filtering, BSR analysis, profit screening, market analysis, or product selection tool. Trigger it even if the user does not explicitly mention “卖家精灵,” whenever their need involves filtering and analyzing Amazon product-level data for product selection.
Use this skill when the user needs NetSuite-based finance analysis, Director of Financial Analysis support, period-close guidance, variance review, reconciliation review, cash reporting, or executive-ready financial narrative generation. Apply it to requests involving income statements, balance sheets, cash flow, budget versus actuals, AR or AP aging, month-end close, SOX-oriented finance checks, journal entry review, and board or CFO reporting. Prefer it when the request clearly involves NetSuite financial data interpretation or finance operations, but do not use it for general NetSuite development or non-finance administration tasks.
Redis Query Engine (RQE) guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR), DIALECT 2 query syntax, efficient FT.SEARCH and FT.AGGREGATE queries, zero-downtime index updates via aliases, and the SKIPINITIALSCAN option. Use when defining a search index on Hash or JSON documents, picking between TEXT and TAG for filtering, writing FT.SEARCH queries with filters and SORTBY, managing or swapping indexes in production, or troubleshooting slow searches with FT.PROFILE.
Analyze messy and unstructured Excel files to identify data quality issues, detect format inconsistencies, find missing values, and generate comprehensive analysis reports. Use when Claude needs to work with Excel files (.xlsx, .xls) for data quality assessment, structure analysis, or when users request data auditing, cleaning recommendations, or statistical summaries of spreadsheet data.
Optimize SurrealDB performance through record ID and key design, indexing strategy, and computed/derived fields. Use when queries are slow, when designing record IDs for locality and range scans, choosing between standard/unique/full-text/vector indexes, verifying index usage with EXPLAIN, or deciding whether to precompute values with computed fields, views, or events. Triggers: slow query, performance, record id design, range scan, DEFINE INDEX, EXPLAIN, computed field, FUTURE, DEFINE TABLE AS SELECT.
Retrieve protein structures from RCSB PDB, PDBe, AlphaFold, SWISS-MODEL, 3D-Beacons (cross-provider structure aggregator), and PDB-REDO (re-refined X-ray structures), with disambiguation, quality assessment (resolution, R-factor, pLDDT, coverage), and metadata. Distinguishes high-quality experimental (X-ray under 2 Angstrom) from predicted, homology-model, and medium-quality structures. Use to fetch protein structures, compare structure quality, batch-check model availability across a gene list, check all structure providers at once, and select structures for drug design or modeling.
Systems biology and pathway analysis integrating Reactome, KEGG, WikiPathways, BioCarta, NCI-Nature Pathway Interaction Database. Multi-database pathway enrichment, protein-pathway relationships, network reasoning. Use for pathway analysis on a gene list, multi-source pathway concordance, and systems-level interpretation across databases.
Migrate an existing Prisma project to ZenStack V3. Use when replacing Prisma/@prisma/client with ZenStack, converting schema.prisma to ZModel, swapping PrismaClient for ZenStackClient, updating generate/migrate scripts, mapping Prisma custom generators and client extensions, or keeping Prisma migrate tooling working.
Use this skill whenever users want to build, inspect, debug, automate, or publish workflows in Agentforce Grid (AI Workbench) using Salesforce plus the Grid MCP or direct Grid REST calls. Trigger it for Grid workbook creation, worksheet setup, Object/Reference/AI/Agent/AgentTest/Evaluation/PromptTemplate/InvocableAction column design, prompt drafting inside Grid, worksheet execution troubleshooting, Grid YAML `apply_grid` specs, and Windows-specific Grid setup issues. Also use it when users mention AI Workbench, Grid Studio, workbook IDs, worksheet IDs, Grid Connect, or ask for recipes like "top opportunities with AI email drafts", "agent test suite in Grid", or "build this worksheet from YAML". Do not use it for generic Salesforce work unrelated to Agentforce Grid.
Use when the user wants to analyze deal outcomes, conduct win/loss reviews, audit pipeline health, or improve deal inspection processes. Also use when the user mentions "win/loss analysis," "deal review," "pipeline audit," "why we lost," "deal inspection," "sales review," "forecast review," or "deal post-mortem." For ongoing deal documentation, see deal-documentation. For sales analytics, see sales-analytics.
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.