Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Queries dbt project metadata locally using the dbt-index CLI — no warehouse connection needed. Use when user asks about model or column lineage, blast radius of a change, test coverage, finding or describing dbt models or sources, build performance, semantic layer metrics, business context glossary, or comparing local vs production state.
Write Streamlit app source code that runs well in a PostHog sandbox — the posthog_apps.query() bridge for reading PostHog data, the packages baked into the sandbox image, caching and session state across Streamlit reruns, layout and chart patterns, and the app.py entry point with any helper modules and data files bundled beside it. Use when authoring or debugging the Python source of a PostHog Streamlit app, when a query inside an app fails, or when asked to "write a streamlit app that shows PostHog data".
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Audit the health of a PostHog project's data warehouse — find every broken or degraded pipeline item across sources, sync schemas, materialized views, batch exports, and transformations. Use when the user asks "what's broken in my warehouse?", "give me a health check", "audit my data pipeline", "why are some dashboards stale?", or wants a one-shot triage summary before deciding where to spend time. Produces a prioritized report of issues grouped by severity and type, with recommended next steps.
Connects an app to the Azure SQL Database container securely, with a least-privilege database user instead of the sa login, the right auth method per environment, and safe handling of the connection secret. Use when a user asks "don't use sa in my app", "create a least-privilege database user", "app login for SQL", "which authentication should my app use", "secure the connection string", "Encrypt / TrustServerCertificate", "store the connection string in Key Vault", "dotnet user-secrets", "managed identity for Azure SQL", or "grant only the roles my app needs". SQL auth locally, Microsoft Entra or managed identity in the cloud, changing only the connection string. Reach for this before wiring an app to connect as sa, or before committing a connection string to source.
Bilibili short-video operations growth assistant, suitable for content creators, operators, brands, and e-commerce when the user provides a Bilibili video link; helps generate comment sentiment and discussion structure, audience profiles and interest signals, and content and engagement suggestions based on the input material.
Builds Getis-Ord Gi* hotspot analysis workflows in CARTO. Triggers when the user mentions hotspots, coldspots, spatial clusters, Getis-Ord, Gi*, cluster detection, concentration areas, "where do X cluster", spacetime hotspot, temporal clusters, time-varying patterns, hotspot trends, emerging hotspots, Mann-Kendall, or wants to find statistically significant spatial or spatiotemporal patterns in point or grid data.
Builds territory planning workflows in CARTO combining territory balancing and location allocation. Triggers when the user mentions territory balancing, territory planning, sales territories, service zones, workload distribution, balanced territories, location allocation, facility placement, optimal locations, maximize coverage, minimize cost, minimize travel distance, depot placement, hub placement, warehouse siting, response time optimization, demand coverage, or wants to divide an area into balanced regions or find optimal facility locations.
Builds trade area and catchment analysis workflows in CARTO. Triggers when the user mentions trade area, catchment area, isochrone, site selection, where to open, best location, billboard, OOH, audience targeting, drive time, walk time, coverage area, commercial hotspot, site scoring, location ranking, or wants to generate isochrones, score candidate locations, or identify the best sites for retail, advertising, or services.
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
Owns repositories, data sources and mapping for Compose and Compose Multiplatform apps: DTO to domain to UiModel boundaries, Ktor clients and bearer auth, WebSocket and SSE, Room, DataStore, Paging 3, offline-first and data-layer tests. Use when writing or reviewing a repository, data source, DTO, mapper, HttpClient, bearer token, WebSocket, SSE, Room DAO, migration, DataStore, PagingSource, RemoteMediator, offline cache or MockEngine test. Do NOT use for ViewModel or UI wiring (compose-feature), composables (compose-ui), the MVI contract or error tiers (compose-architecture), Gradle modules (compose-project), or commonMain vs platform splits (compose-platform).
Aggregated trending-list API service across the web — based on the open-source DailyHotApi project, auto-deployed locally, with zero-configuration access to real-time trending data from 40+ platforms. Covers major platforms such as Douyin, Weibo, Zhihu, Bilibili, Baidu, Toutiao and Kuaishou. Trigger words: 热点、热搜、趋势、热榜、trending、hot topics.
Metadata management, data analysis, development changes, operations diagnostics, and inspections for Volcengine databases (MySQL, veDB-MySQL, PostgreSQL, SQL Server, MongoDB, Redis) and self-managed public-network databases (MySQL and PostgreSQL families). Covers instance lists, databases within instances, table lists and schemas, data queries, data analysis and visualization reports (including joint analysis across data sources/files), data governance (asset inventories/data profiling/data quality/sensitive data identification), slow query diagnostics, deadlock and lock-wait analysis, transaction and active session troubleshooting, error log queries, tablespace analysis, health inspections, monitoring metric queries, and change request applications. Does not support ByteCloud databases such as ByteRDS / ByteDoc / ByteRedis
Expert knowledge for Drizzle ORM - the lightweight, type-safe SQL ORM for edge and serverlessUse when "drizzle, drizzle orm, drizzle-kit, drizzle schema, drizzle migration, drizzle relations, sql orm typescript, edge database, d1 database, orm, database, typescript, sql, edge, serverless, d1, postgres, mysql, sqlite" mentioned.
Raw reference for ESPN's undocumented public JSON endpoints, for a sport, league, or operation that no dedicated sports-skills skill covers, or when a developer explicitly asks to work with raw ESPN endpoints. Prompt-only: endpoint catalog, documented league slugs, observed response shapes, pitfalls, and stdlib fetch helpers. Output is provider-native ESPN JSON, not normalized or canonical data. Use when: the requested league or operation is genuinely not covered by a dedicated skill (e.g. MMA, lacrosse, rugby, Australian football, NCAA volleyball, field hockey, water polo, IndyCar/NASCAR), or the user explicitly asks to write, debug, or inspect code against ESPN endpoints. Don't use when: a dedicated skill covers the league and job — nba-data, wnba-data, nfl-data, nhl-data, mlb-data, cfb-data (NCAA football), cbb-data (NCAA men's basketball), football-data (its listed soccer leagues), tennis-data (ATP/WTA), golf-data (PGA/LPGA/DP World), cricket-data, fastf1 (Formula 1); sports-news or sports-reporter for news and articles; betting, markets, kalshi, or polymarket for odds and prediction markets. volleyball-data covers Dutch Nevobo volleyball only, not NCAA. A dedicated skill's error, timeout, or empty result is not permission to switch to raw ESPN automatically — report it and ask first
Run scientific (software) experiments. Use when the user asks to "run an experiment", "run an investigation", or "research with Asta." Also use this skill to analyze experimental data generate a research report from it. The user may refer to this system by its internal project name, "Panda."
Design and generate accessible, cohesive data visualizations, SVG charts, metric cards, and dashboard tiles with theme-adaptive styling and verified viewports. Use when creating SVG charts, rendering metrics plots, designing dashboard visuals, or visualizing performance trends — even if the user does not explicitly say "fable-dataviz" (e.g. "make a chart of this data", "plot these benchmarks", "create an SVG graph", "visualize these metrics"). Do NOT use for non-visual text-only data summaries or generic code edits.
Plan, audit, or revise the figures, tables, captions, and visual evidence for a research paper. Use this skill whenever the user asks what figures or tables they need, whether a result should be a plot or table, how to present experiments, how to design ablation tables, how to make captions self-contained, what belongs in the appendix, or whether the current visual evidence supports the paper's claims. This skill is especially useful after experiment design and before writing the Results section.
Generates comprehensive synthetic fine-tuning datasets in ChatML format (JSONL) for use with Unsloth, Axolotl, and similar training frameworks. Gathers requirements, creates datasets with diverse examples, validates quality, and provides framework integration guidance.
Google Analytics 4, Search Console, and Indexing API toolkit. Analyze website traffic, page performance, user demographics, real-time visitors, search queries, and SEO metrics. Use when the user asks to: check site traffic, analyze page views, see traffic sources, view user demographics, get real-time visitor data, check search console queries, analyze SEO performance, request URL re-indexing, inspect index status, compare date ranges, check bounce rates, view conversion data, or get e-commerce revenue. Requires a Google Cloud service account with GA4 and Search Console access.
Investment-banking pitch book for strategic alternatives — trading comps, precedent transactions, valuation football field, DCF sensitivity, strategic-options matrix, process recommendation. Built by adapting `assets/template.html` so IB-specific chrome, disclosure bands, and source labels are preserved. Use for Board / sell-side discussion materials. Not a VC fundraising deck (see html-ppt-pitch-deck). Workflow adapted from Anthropic financial-services Pitch Agent (Apache-2.0).
ACTIVATE when building executive dashboards, tracking business metrics, creating executive scorecards, monitoring organizational KPIs, setting up health metrics, building dashboards for real-time monitoring, or establishing systems to track and measure business performance. Critical for any executive who needs to monitor company health, make data-driven decisions, or track progress toward strategic goals.
INVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (final_response, single_step, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.
Light research mainline step 2 · data engineering: **findable and affordable data** (source/license/version/size/split) + **judge data feasibility before proposing an idea** (is the data enough to support the research/statistical power) + **prevent data leakage** (a frequent rejection landmine at top conferences.) When to use: the user wants to find/choose/download public datasets, or has data and asks "can I do research with this/is it enough/is the quality OK" / needs cleaning, handling missing values and outliers, feature engineering, dataset splitting, data augmentation / building a dataset (collection, annotation guidelines, privacy compliance, release) / suspects train-test contamination (leakage) / wants to assess the data basis before proposing an idea. Trigger words: is the data enough / data feasibility / data quality / data leakage / preventing leakage / train-test overlap / how to split / cross-validation / annotation guidelines / inter-annotator agreement IAA / building a dataset / is the sample size enough / statistical power / find a dataset / data license / dataset search / data leakage / feasibility / data split / annotation. Core discipline: **data leakage = critical, an outright veto** (standardization before splitting / temporal leakage / entity overlap / target-encoding leakage); **data insufficient to support the idea = block before the idea (back edge 2⊣3, get more data/change the idea)**; power is an empirical threshold, not a power analysis; leakage detection is heuristic and bounded — do not claim "everything was checked".
Writes data from MATLAB to relational databases and performs database operations. Use when writing data with sqlwrite, updating rows with sqlupdate, executing SQL with execute, running stored procedures, managing transactions with commit/rollback, creating tables, or using SQL prepared statements.
Always invoke for spatial suitability, site selection, AHP, criteria weights, or weighted-overlay work, including audits of inconsistent pairwise judgments and requests for only a final map. Covers consistency, standardization, constraints, ranked surfaces, shortlists, and sensitivity. Route travel-time placement and location-allocation to network-accessibility-analysis.
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.