Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
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.
Build GitHub Copilot workflows with Xquik X API SDKs, REST endpoints, hosted Apify Actor runs, MCP tools, TweetClaw OpenClaw plugin installs, signed webhooks, tweet search, user lookup, follower exports, media actions, and agent automation.
Build agentic RAG systems with autonomous planning, reflection, and tool use. Use this skill when implementing agent-driven retrieval, query decomposition, iterative refinement, or multi-source RAG orchestration. Activate when: agentic RAG, A-RAG, autonomous retrieval, query planning, iterative RAG, multi-step retrieval, agent retrieval, RAG agent.
Use this skill whenever a user wants to execute operations against Algolia indices or accounts — deleting records, copying/migrating indices, backing up data, importing/exporting records, managing API keys, editing synonyms, configuring rules, changing settings like facets, clearing indices, or automating Algolia in CI/CD pipelines. The key signal is that the user wants to act on their Algolia data or configuration (server-side / backend / admin operations), regardless of whether they mention "CLI" or "command line." If someone names a specific Algolia index and wants to change, move, query, or manage it, use this skill. Do NOT use for frontend search UI work (InstantSearch, React components, autocomplete widgets), Algolia dashboard GUI questions, or evaluating Algolia vs. other providers.
Query Catalog, database, and table metadata resources in Alibaba Cloud Data Lake Formation (DLF). Provides read-only queries via the DLF OpenAPI Python SDK, supporting listing and viewing Catalogs, databases, tables with their detailed information and Schema definitions. Use cases: "list available Catalogs", "list databases", "view table schema", "search tables", "search tables by name", "fuzzy search", "view DLF metadata", "what databases are in the data lake", "what columns does a table have", "find tables whose name contains xxx". This Skill only contains read-only operations — no create, modify, or delete operations.
Mixed methods research design and integration strategies for combining qualitative and quantitative approaches. Use when planning convergent, explanatory sequential, exploratory sequential, embedded, transformative, or multiphase designs; when integrating diverse data sources through merging, connecting, or embedding; when constructing joint displays or meta-inferences; or when evaluating quality criteria specific to mixed methods research. Covers Creswell & Plano Clark frameworks, notation systems, and software tools for integration. For single-strand qualitative coding (thematic analysis, grounded theory, saturation, inter-coder reliability) use alterlab-qualitative-methods; for questionnaire/Likert/instrument-validation mechanics use alterlab-survey-design. Part of the AlterLab Academic Skills suite.
BigQuery Expert Engineer Skill - Comprehensive guide for GoogleSQL queries, data management, performance optimization, and cost management Use when: - Running bq commands (query, load, extract) - Writing GoogleSQL queries (functions, JOINs, CTEs) - Designing partitioned/clustered tables - Using BigQuery ML or external data sources
Biopython sequence analysis: parse FASTA/FASTQ/GenBank/GFF (SeqIO), NCBI Entrez (esearch/efetch/elink), remote/local BLAST, pairwise/MSA alignment (PairwiseAligner, MUSCLE/ClustalW), phylogenetic trees (Phylo). Use for gene family studies, phylogenomics, comparative genomics, NCBI pipelines. For PCR/restriction/cloning use biopython-molecular-biology; for SAM/BAM use pysam.
Three-statement financial model for A-share stocks. Adapts the standard 3-statement-model methodology for Chinese accounting standards (CAS), Chinese GAAP differences, and AkShare-sourced financials. Use instead of the original 3-statement-model skill when building integrated IS/BS/CF models for Chinese listed companies.
Analyze text content using both traditional NLP and LLM-enhanced methods. Extract sentiment, topics, keywords, and insights from various content types including social media posts, articles, reviews, and video content. Use when working with text analysis, sentiment detection, topic modeling, or content optimization.
Guide for Convex performance optimization including denormalization, index design, avoiding N+1 queries, OCC (Optimistic Concurrency Control), and handling hot spots. Use when optimizing query performance, designing data models, handling high-contention writes, or troubleshooting OCC errors. Activates for performance issues, index optimization, denormalization patterns, or concurrency control tasks.
Use this skill when designing a data dashboard—choosing KPIs, structuring layout, applying visual hierarchy, or deciding which BI tool to use. Trigger phrases: ''design a dashboard'', ''build a KPI dashboard'', ''what should my dashboard show'', ''help me layout a dashboard'', ''dashboard for monitoring''. Not for building chart code from scratch (use chart-builder), writing SQL queries (use sql-analyst), or designing marketing landing pages.
Design effective data dashboards with proper KPI hierarchy, chart type selection, and interactive features. Use this skill when the user needs to create a dashboard, choose the right visualizations, organize metrics for different audiences, or evaluate dashboard tools — even if they say 'build a dashboard', 'our reports are confusing', 'which chart should I use', or 'executives can't find the metrics they need'.
Data export to CSV, Excel (XLSX), and JSON. ExcelJS, SheetJS (xlsx), Papa Parse, Apache POI (Java), openpyxl (Python). Streaming exports for large datasets. USE WHEN: user mentions "export CSV", "export Excel", "XLSX generation", "download spreadsheet", "ExcelJS", "SheetJS", "Papa Parse", "data export" DO NOT USE FOR: PDF generation - use `pdf-generation`; file upload/download - use `file-upload`/`cloud-storage`
Generate correct code for whole-slide image (WSI) analysis using TIAToolbox and foundation models (H-optimus-0, UNI, Prov-GigaPath). Triggers on requests involving whole-slide images, WSI, digital pathology, histopathology, SVS/NDPI/pyramidal TIFF, tissue segmentation, patch extraction, stain normalization, H-optimus-0, TIAToolbox, CAMELYON16/17, SlideGraph, MIL aggregation, HoVer-Net, PanNuke, or SageMaker deployment of pathology models. Produces deterministic commands and Python snippets for slide-info inspection, tissue masking, tile extraction at specified mpp, foundation-model feature embedding, slide-level aggregation, and regulated cloud inference.
Designs complete GraphRAG systems integrating graph databases, vector stores, orchestration frameworks, and LLM reasoning. Guides through pattern selection, technology stack decisions, integration pipeline design, and domain-specific customizations. Use when designing GraphRAG systems, choosing technology stacks for graph-augmented retrieval, combining Neo4j with LLM, using LangChain/LlamaIndex knowledge graphs, applying community detection for RAG, building hybrid symbol-vector pipelines, or deploying production or domain-specific GraphRAG.
Kuaishou short-video operations growth assistant, suitable for content creators, operators, brands, and e-commerce when the user provides a Kuaishou content link; helps generate sentiment, personas and discussion focal points, public-opinion and conversion leads, and optimization suggestions based on the input material.
Computes multi-constellation Global Positioning System (GPS) or Global Navigation Satellite System (GNSS) positions from RINEX v3 data using rinexread, gnssmeasurements, receiverposition, and gnssoptions. Filters by constellation, elevation mask, C/N0, and observation code. Reports DOP, scatter RMS, and satellite count. Use when processing GNSS data, computing positions from RINEX files, analyzing accuracy, comparing constellations, or evaluating satellite geometry. Do NOT use for carrier-phase RTK/PPP, IMU fusion, orbit propagation, NMEA streaming, or RINEX v4.
Reasoning skill for multi-omics data integration strategy selection. Use when the user asks to integrate transcriptomics with proteomics, combine multi-omic layers, choose between early intermediate or late integration, apply batch correction across omics, handle partial sample overlap, run MOFA+ or iCluster, interpret multi-omic factors, select enrichment methods for multi-omic signatures, or decide how to merge genomics epigenomics transcriptomics proteomics and metabolomics data. Triggers include "multi-omics integration", "combine omics layers", "early vs late fusion", "MOFA+", "iCluster", "batch correction across omics", "partial overlap", "multi-omic enrichment", "kernel integration", "concatenation vs stacking", "SNF", "similarity network fusion", "intermediate integration", "multi-omic factor analysis".
Trains, validates, tests, and runs prediction for Physical AI Studio policies via the library Lightning stack. Use when running physicalai fit/validate/test/predict, calling physicalai.train.Trainer and Policy APIs from Python, writing or editing YAML configs under library/configs, wiring a model + datamodule + trainer, resuming from a checkpoint, or debugging a training run. Covers ACT, Pi0, Pi0.5, GR00T, and SmolVLA.
Build browser automation and web scraping with Playwright on your local machine. Prevents 10 documented errors including CI timeout hangs, extension testing failures, and Ubuntu compatibility issues. Includes stealth mode for anti-bot bypass, authenticated sessions, infinite scroll handling, screenshot/PDF generation, and v1.57 Speedboard performance analysis. Use when: automating browsers, scraping protected sites, testing with real IPs, bypassing bot detection, generating screenshots/PDFs, or troubleshooting "target closed", "page.pause() hangs CI", "permission prompts block tests", or "Ubuntu 25.10 installation" errors.
Use when: you need to validate product optimization results, make data-driven A/B experiment decisions, or assess the causal impact of feature changes. Do NOT use when: changes cannot be measured quantitatively, the sample size is insufficient, or strict statistical validation is not needed
Every Google Trends workflow pytrends offered, plus the local history and rate-limit resilience that archived, frozen wrapper never had. Trigger phrases: `check google trends for`, `interest over time for`, `what's trending right now`, `compare search interest`, `related queries for`, `search interest by region`, `use google-trends`, `run google-trends-pp-cli`.
Real-world data cohort analysis pipeline for claims and EHR data — cohort identification with ICD-10, NDC, and CPT codes, medication adherence metrics (PDC/MPR), propensity score estimation and balance diagnostics, Kaplan-Meier survival curves, and Cox proportional hazards models. Use when the user mentions claims data, cohort identification, ICD-10 codes, NDC codes, CPT codes, medication adherence, PDC, MPR, propensity score, SMD balance, Kaplan-Meier, Cox model, Schoenfeld residuals, survival analysis on claims, or real-world evidence pipeline.
Use when building batch jobs, ETL pipelines, scheduled imports/exports, or any chunk-oriented bulk processing with Spring Batch. Covers the Spring Batch 5 / Boot 3 builder API, restartability and idempotent job parameters, reader/writer thread-safety, fault tolerance, and chunk transaction boundaries.
Maps identified symmetries to mathematical groups (cyclic, dihedral, symmetric, SO(3), SE(3), E(3)) for equivariant neural network architecture design, using taxonomy and foundations from Visual Group Theory. Use when candidate symmetries have been identified and need formalization into group theory language, or when user mentions cyclic groups, dihedral groups, Lie groups, SO(3), SE(3), or permutation groups.
Best practices for the Terra API Streaming (Real-Time) API – live, roughly per-second biometric data from wearables over websockets. Use when building realtime streaming with Terra API, TerraRT SDKs, or wss://ws.tryterra.co; streaming live heart rate, steps, distance, acceleration, ECG, HRV, RR intervals, calories, MET, power, cadence, speed, location, or gyroscope; pairing a wearable over BLE or ANT+; producing sensor data from a mobile app; consuming a live stream on a backend; or streaming from an Apple Watch or Wear OS watch. Covers the producer/broker/consumer architecture, the websocket handshake and opcodes, token minting, close codes, replay/backfill, and per-platform SDK setup (iOS, Android, React Native, Flutter, Wear OS).
Augment a Wren project with business context that DB schema cannot carry — enum value meanings, units (USD vs cents, ms vs sec), NULL semantics, magic sentinels (-1 = unknown), soft-delete default filters, business synonyms, time-grain / TZ conventions, cross-system identifiers, currency rules, canonical-table preferences, AND named aggregation metrics (ARR, churn, DAU, WAU, NRR) proposed as cubes. Runs in one of two modes selected at session start: `grill` (one question at a time, user-driven) or `auto-pilot` (agent infers and applies, escalates only on conflicts and high-blast-radius additions like new cubes / views / relationships). Reads everything under <project>/raw/ (PDFs, glossaries, handbooks, code, data dictionaries) and optionally samples low-cardinality columns from the live DB (grill mode), compares against the current MDL / cubes / instructions.md / queries.yml / memory pairs, then fills gaps via the ten-category gap catalog and the cube proposal flow. Confirmed findings are written back to the right sink. Use when: user says 'enrich context', 'augment my project', 'grill me on this project', 'auto-fill my context', 'agent doesn't understand our docs / enum values / units / null meanings', 'business context is missing', 'what does status=A mean', 'is this amount in USD or cents', 'we keep getting wrong aggregations', 'add cubes for ARR / DAU / churn', 'we have a handbook / glossary / data dictionary the agent should know'; or after generating an MDL and noticing the agent lacks business semantics.
Use when marketing numbers look bad and the user needs to know WHY — layered root-cause diagnosis across tracking, delivery, creative, landing page, offer, and audience quality, 5-Whys, regional benchmarks for US, EU, SEA, and LATAM, and a 48-hour action plan. Covers dropshipping ROAS and BE-ROAS. Trigger on 'why is CPA so high', 'my ads are not converting', 'ROAS dropped', 'we are burning budget', 'performance is bad this month', 'diagnose the funnel'. Also use when the user pastes a screenshot of numbers with no question attached. Not for — auditing account configuration and scoring health, see `21-ads-audit-global`; writing a report someone else reads, see `07-marketing-report-global`; turning a raw export into insight, see `13-data-analysis-global`.
Use this skill to grade running ads as Red (stop), Yellow (hold), or Green (scale), detect creative fatigue, analyze LTV:CAC, and recommend scaling actions. Trigger it when reviewing campaign exports or deciding what to kill, keep, or scale.
Use this Skill for Alibaba Cloud Lindorm work: instance lifecycle and configuration, networking and access control, monitoring, performance, storage, connection diagnosis, backup, migration, permissions (including Lindorm SQL user management with `CREATE USER` and `GRANT`), slow queries, SQL development, and Search, vector, graph, AI, multimodal, or knowledge-base workflows. Trigger on Lindorm product or CLI terms such as LindormTable, LindormTSDB, LindormSearch, Lindorm AI, HBase/AliHBase, lindormcli, Lindorm CLI, `aliyun lindorm`, or Chinese requests mentioning 宽表引擎、时序引擎、搜索引擎、向量检索、图引擎、白名单、实例创建/扩缩容/释放. Use this Skill's references or official Alibaba Cloud documentation; do not invent Lindorm-specific facts from general training knowledge.
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.