Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
This skill should be used when picking or diagnosing a training move (SFT, LoRA, DPO/KTO/ORPO, RFT, GRPO/PPO/RLOO, RLHF), or when the user mentions fine-tuning, post-training, training recipe, reward design, or weight updates. Decision tree by reward shape, smoke-run gate, three failure diagnostics, five false-progress patterns. Provider recipes and I/O contract in references/.
Fetch web content, take screenshots, extract structured data, search the web, and crawl documentation sites. Use when the user needs current web information, asks to scrape a URL, wants a screenshot, needs to extract specific data from a page, or wants to learn about a framework or library.
Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O'Neil's methodology. Dual-index tracking (S&P 500 + NASDAQ) with state machine for rally attempt, FTD qualification, and post-FTD health monitoring. Use when user asks about market bottom signals, follow-through days, rally attempts, re-entry timing after corrections, or whether it's safe to increase equity exposure. Complementary to market-top-detector (defensive) - this skill is offensive (bottom confirmation).
Invoke when the user needs to set up analytics, define telemetry events, establish KPIs, build dashboards, configure A/B testing, or implement data-driven design capabilities. Triggers on: "analytics", "telemetry", "KPIs", "metrics", "player data", "retention", "DAU", "dashboard", "A/B testing", "funnel analysis". Do NOT invoke for balance tuning (use game-balance-check) or economy design (use game-economy-designer). Part of the AlterLab GameForge collection.
Fills gaps in existing healthcare practitioner lists — adds missing phone numbers, credentials, specialties, contact info, education, reviews, and regulatory data. Triggers: "enrich my provider list", "fill in missing data", "add phone numbers to these doctors", "complete this practitioner database", "enrich CRM export", "fill gaps in my provider data", "supplement this healthcare list". Accepts CSV, Google Sheet URL, or pasted data. Searches for each provider's practice website, extracts missing fields, and enriches with reviews, clinical trials, and accreditation via WSAs. Do NOT use for extracting providers from practice URLs — use healthcare-providers-extract instead. Do NOT use for validating credentials — use healthcare-providers-verify instead. Do NOT use for discovering practices — use market-finder or local-places instead. Do NOT use for general extraction — use nimble-web-expert instead.
Extracts structured practitioner data from healthcare practice websites. Returns names, credentials, specialties, contact info, and education for every provider on a practice's site. Use when user asks to extract, pull, or list doctors, providers, or staff from practice websites. Triggers: "extract doctors from", "pull providers from", "who are the providers at", "build a provider database", "list all doctors at", "scrape the team page", "get practitioner data from". Accepts practice URLs (pasted, CSV, Google Sheet) or discovers practices via Google Maps when given specialty + location. Single sites or 100+ URLs. Do NOT use for filling data gaps — use healthcare-providers-enrich instead. Do NOT use for credential validation — use healthcare-providers-verify instead. Do NOT use for discovering practices — use market-finder or local-places instead. Do NOT use for general extraction — use nimble-web-expert instead.
The CLI for Hike Capital's Lightyear investment project management system. Load this skill when the user needs to query the project database, pull project lists, filter projects by stage/industry/valuation/quadrant, view post-investment stages and the investment pipeline, get system statistics, or mentions terms such as Lightyear, 光年, project intake, project meeting, investment decision meeting, closing, or quadrant. It provides lightyear_cli for project data queries and multi-dimensional filtering. Use hike-seek for talent, hike-portfolio-report for portfolio operating reports, and hike-knowledge for investment MEMO/decision MEMO standards.
Operating-data report generator for Hike Capital portfolio companies, currently supporting only Halara (other portfolio companies are out of scope for now). Load this skill when the user needs to generate a Halara weekly/monthly/quarterly report, view Best Sellers or the bestseller list, analyze operating data, monitor sales, view product rankings, review growth, or track ranking changes, or mentions terms such as Halara report, Halara data, or product analysis; it produces an HTML report.
Detect IBD-style Distribution Days for QQQ/SPY (close down at least 0.2% on higher volume), track 25-session expiration and 5% invalidation, count d5/d15/d25 clusters, classify market risk (NORMAL/CAUTION/HIGH/SEVERE), and emit TQQQ/QQQ exposure recommendations. Use after market close, before TQQQ exposure changes, or as input to FTD/market-state frameworks. Does not execute trades.
Cluster a list of keywords into topical groups with search intent labels, validated search volume, KD, and CPC data. Use this skill whenever a user provides a list of keywords (pasted, uploaded as CSV/Excel, or via Google Sheet URL) and asks to cluster, group, map, organize, or categorize them. Also trigger when a user says "keyword cluster", "cluster my keywords", "group these keywords", "keyword map", "keyword strategy from this list", "organize keywords by topic", or pastes or uploads a list of keywords and wants structure from it. Always use this skill — do not attempt keyword clustering manually without following this workflow.
When the user wants to create local SEO reports, track local ranking performance, set up reporting dashboards, or communicate results to clients. Also use when the user mentions "local SEO report," "client reporting," "local metrics," "KPIs for local," "GBP insights," "how to measure local SEO," or "prove ROI on local." For geogrid-specific analysis, see geogrid-analysis. For competitor benchmarking, see local-competitor-analysis.
Detect structural macro regime transitions (1-2 year horizon) using cross-asset ratio analysis. Analyze RSP/SPY concentration, yield curve, credit conditions, size factor, equity-bond relationship, and sector rotation to identify regime shifts between Concentration, Broadening, Contraction, Inflationary, and Transitional states. Run when user asks about macro regime, market regime change, structural rotation, or long-term market positioning.
Detects market top probability using O'Neil Distribution Days, Minervini Leading Stock Deterioration, and Monty Defensive Sector Rotation. Generates a 0-100 composite score with risk zone classification. Use when user asks about market top risk, distribution days, defensive rotation, leadership breakdown, or whether to reduce equity exposure. Focuses on 2-8 week tactical timing signals for 10-20% corrections.
Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and JSON files directly with SQL, reducing or profiling large data before MATLAB analysis, creating portable development databases, or installing DuckDB extensions. Triggers on: DuckDB, duckdb(), large CSV/Parquet/JSON, file too large for readtable, filter/aggregate at source, deduplicate, reduce before analysis, profile large file, persistent file import, analytical engine, SQL on CSV, SQL on Parquet, SQL on JSON, query CSV with SQL, query Parquet with SQL, run SQL on files, SQL queries on files, query files directly, SQL without database, in-process SQL.
Provides comprehensive guidance for MySQL database including SQL syntax, data types, indexes, transactions, stored procedures, and optimization. Use when the user asks about MySQL, needs to write SQL queries, design database schemas, optimize MySQL performance, or work with MySQL features.
Setting up and running Qdrant Hybrid Cloud on your own Kubernetes cluster (managed, on-prem, or edge): prerequisites, storage/CSI and backups, installing the Qdrant Cloud agent and operator, creating/exposing/securing clusters, registry mirroring, and secret rotation. Use when someone wants to set up, install, deploy, or configure Hybrid Cloud on their own infrastructure; is running Qdrant on their own EKS, GKE, AKS, OpenShift, or other Kubernetes; asks about the agent or operator, a storage class or volume snapshots for Hybrid Cloud, exposing a cluster, mirroring Qdrant images, or rotating secrets; or when a Hybrid Cloud install is failing on storage or connectivity.
Builds and validate revenue forecasts with pipeline coverage and gap analysis. Use when you're not confident in your commit number, pipeline coverage looks thin, a forecast call is coming and you need to tighten the number, weighted pipeline doesn't match gut feel, or there's a gap between target and what's realistic. Do NOT use for individual deal analysis (use /sales-deal-inspect) or building outbound cadences (use /sales-cadence).
A collection of algorithms for image processing in Python. Built on NumPy, SciPy, and Cython. It focuses on scientific image analysis including segmentation, geometric transformations, color space manipulation, analysis, and filtering.
Use when the user needs ML pipelines, statistical analysis, data preprocessing, feature engineering, model selection, experiment tracking, or data visualization. Triggers: dataset exploration, model training, feature engineering, hyperparameter tuning, experiment tracking setup, statistical hypothesis testing, visualization creation.
Discovers, selects, inspects, queries, and manages Tilebox datasets and external auxiliary grids. Use when choosing Earth observation or supporting DEM, weather, climate, QA, or land-mask data from a requested target product—even if no dataset is named—or when evaluating coverage, resolution, collections, schemas, datapoints, storage access, credentials, dataset creation, or schema updates.
Initializes, configures, builds, publishes, deploys, undeploys, and locally tests Tilebox workflow projects and releases with tilebox.workflow.toml and dynamic runners. Use when scaffolding workflow projects, iterating on workflow code, release artifacts, deployment targets, cluster runners, or completing an implicit Earth observation project routed to Tilebox.
Remote Python execution in managed sandboxes on Together AI with stateful sessions, file uploads, data analysis, chart generation, and notebook-like runs via the Sandboxes API. Reach for it whenever the user wants managed remote Python execution instead of local execution, raw clusters, or full model hosting.
Evaluates market bubble risk through quantitative, data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when the user asks about bubble risk, valuation concerns, or profit-taking timing.
Relational database implementation across Python, Rust, Go, and TypeScript. Use when building CRUD applications, transactional systems, or structured data storage. Covers PostgreSQL (primary), MySQL, SQLite, ORMs (SQLAlchemy, Prisma, SeaORM, GORM), query builders (Drizzle, sqlc, SQLx), migrations, connection pooling, and serverless databases (Neon, PlanetScale, Turso).
Bypasses anti-bot protections using Oxylabs Web Unblocker, an AI-powered proxy that handles fingerprinting, JavaScript rendering, and retries automatically. Use when the user needs to scrape protected websites, bypass CAPTCHAs, access blocked content, or when regular proxies fail due to anti-bot measures.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use when the user needs YouTube transcripts, video search, channel browsing, playlist extraction, or content monitoring. Trigger phrases: 'get the transcript for', 'search YouTube for', 'what are the latest videos on', 'list this playlist', 'monitor this channel', or any request involving a YouTube URL, video ID, or @handle. Do NOT use for downloading video or audio files, YouTube engagement data (likes, comments), or private/age-restricted videos.
Dung khi can theo doi lien tuc nguoi ta noi gi ve thuong hieu, doi thu va nganh tren mang xa hoi — bo tu khoa giam sat, phan loai sac thai, bao cao tuan va thang, canh bao som, chi so brand health. Kich hoat khi user nhac 'social listening', 'theo doi thuong hieu', 'giam sat mang xa hoi', 'brand monitoring', 'khach dang noi gi ve minh', 'do sentiment', 'co ai nhac ten shop khong', 'canh bao som khung hoang'. Khong dung cho — khung hoang DA XAY RA va can xu ly ngay thi dung skill 66-crisis-playbook; mo xe chien luoc mot doi thu cu the thi dung skill 08-nghien-cuu-doi-thu; doc so lieu ads va web thi dung skill 13-phan-tich-du-lieu.
Use when understanding images with Alibaba Cloud Model Studio Qwen VL models (qwen3-vl-plus/qwen3-vl-flash and latest aliases). Use when building image Q&A, visual analysis, OCR-like extraction, chart/table reading, or screenshot understanding workflows.
Create custom job steps for B2C Commerce batch processing. Use this skill whenever the user needs to write a batch job, data export script, scheduled cleanup task, or any server-side processing that runs on a schedule. Also use when they ask about steptypes.json, chunk-oriented vs task-oriented job steps, read/process/write patterns, how to get a custom job to appear in Business Manager, or how to author and import a jobs.xml job definition (job/flow/step structure, step type, the required triggers element) so a step type becomes a runnable, schedulable job — even if they just say "I need a script that runs nightly" or "batch process orders".
This skill MUST be used when the user names the BCG growth-share matrix (BCG 矩陣、成長佔有率矩陣、搖錢母牛), and SHOULD be used when assessing investment priorities across businesses, products, or brands using market growth and relative market share, including 資源配置、事業組合、產品組合、 投資、維持、收割、重定位或退出.
Systematic stock screening and investment idea sourcing for A-share markets. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Adapted from the original idea-generation skill for Chinese market conventions and data sources. Triggers on "A股选股", "股票筛选", "寻找机会", "stock screen China", "A-share ideas", "find ideas for Chinese stocks", or "screen for A-share opportunities".
Daily morning research note for A-share markets. Summarizes overnight developments, pre-market sentiment, trade ideas, and key events for the trading day. Adapted from the original morning-note skill for Chinese market conventions. Triggers on "早报", "晨会纪要", "今日策略", "morning note", "morning meeting", or "daily A-share preview".
Generate code for EDC export validation, clinical data range checks, cross-form consistency checks, SDTM structure validation, controlled terminology verification, and define.xml generation. Use when the user asks to validate clinical trial data exports, check vital sign or lab value ranges, verify AE date consistency, validate SDTM datasets against CDISC rules, generate define.xml, or build an automated data review pipeline. Triggers include "EDC validation", "range check clinical data", "cross-form consistency", "SDTM validation", "controlled terminology check", "define.xml generation", "Medidata Rave export", "Oracle InForm", "Veeva Vault CDMS", "clinical data cleaning", "edit check", "data query", "SDTM structure check", "lab range check", "vital signs validation", "AE date check", "protocol deviation detection", "OpenCDISC", "Pinnacles 21", "P21 validation".
Provides comprehensive guidance for Elasticsearch including indexing, mappings, query DSL, aggregations, analyzers, cluster management, and ELK Stack integration. Use when the user asks about Elasticsearch, needs to implement search functionality, work with Elasticsearch queries, or manage Elasticsearch clusters.
Train custom AI models (LoRA) on fal.ai — personalize image generation for specific people, styles, objects, or video generation. Use when the user requests "Train model", "Train LoRA", "Fine-tune", "Custom model", "Train on my images", "Portrait training".
Universal content grabber — fetch any URL and return structured Markdown. Supports X/Twitter, WeChat, Xiaohongshu, YouTube, GitHub, LinuxDo/IDCFlare/Discourse, Feishu/Lark, KDocs, FlowUs, Youdao Note, Zhihu, Bilibili (with subtitle transcription), Xiaoyuzhou podcasts, Ximalaya podcasts, Telegram, HackerNews, Medium, Reddit, Weibo, Douyin, Zsxq (Knowledge Planet), RSS, 300+ paywall news sites, and any web page. Use when user provides a URL and wants its content extracted.
Monitor dividend portfolios with Kanchi-style forced-review triggers (T1-T5) and convert anomalies into OK/WARN/REVIEW states without auto-selling. Use when users ask for 減配検知, 8-Kガバナンス監視, 配当安全性モニタリング, REVIEWキュー自動化, or periodic dividend risk checks.
Use when a trained medical-imaging model needs its documentation. Fills a Model Card and a Datasheet for its dataset from facts you supply, adds a METRIC-informed data-quality pass and gates that no required section is empty. Never invents numbers, provenance or licence.
Real-time blockchain event monitoring with webhooks. Use when user asks about setting up webhooks, real-time event streaming, monitoring wallet addresses, tracking token transfers in real-time, listening to all addresses on a chain, creating/updating/deleting streams, adding/removing addresses from streams, or receiving blockchain events as they happen. Supports all EVM chains. NOT for querying historical or current blockchain state - use moralis-data-api instead.
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.