Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Finds the price buyers will actually pay. Reads the consumer panel's four price answers per buyer into a Van Westendorp price-sensitivity range (too cheap, a bargain, getting expensive, too expensive), sets it against what competitors really charge and against the CFO's margin, and recommends a price, a price ladder (good / better / best) and an opening offer to test. Use when the user says "how much should I charge", "price this", "is $X too expensive", "pricing strategy", "what price", or after the consumer panel.
Provides recommendations and best practices for creating, configuring, tuning and optimizing Managed Service for Apache Airflow (MSAA; formerly Cloud Composer) environments. Use when the user asks for guidance, recommendations, or best practices on configuring Managed Airflow environments, scaling Airflow environments, preventing workload restarts, or analyzing system health. Don't use for troubleshooting individual DAG or task run failures, authoring DAGs, or migrating DAGs to newer Airflow versions
Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on. Use when the user wants to "connect Stripe", "import data from Postgres", "add a new data source", "sync my warehouse tables", or wants to pick sync methods for each table. Walks through source-type discovery, credential validation, table discovery, per-table sync_type selection, and the final create call. Also covers picking a good prefix and what to do right after creation.
Your CFO. Builds the unit economics of a business before money is spent: what one unit earns after its direct costs, the real profit margin at the planned volume, the break-even point in units a day, year 1 month by month, the cash needed before it pays for itself, how long the startup spend takes to earn back, and what happens if the price drops, sales come in low or costs rise. Every number traces to an input the user can check. Use when the user says "find the profit margins", "do the numbers", "is this profitable", "break-even", "unit economics", "how much do I need to start", or "run the CFO".
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). **Trigger when user asks to:** - Combine keyword and semantic search - Implement hybrid search or multi-modal retrieval - Use BM25/pg_textsearch with pgvector together - Implement RRF (Reciprocal Rank Fusion) for search - Build search that handles both exact terms and meaning **Keywords:** hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.
DataWorks Operations Center assistant for task and workflow operations, alert rule creation and management. Covers troubleshooting, failure recovery, baseline assurance, monitoring and alerting. Supports periodic, manual, and triggered tasks/workflows (excludes real-time/streaming tasks). Uses aliyun CLI to call dataworks-public OpenAPI (2024-05-18). Trigger keywords: query task, task instance, instance log, workflow, workflow instance, alert rule, operations center, task failure, instance status, upstream/downstream dependency, rerun, monitoring alert, custom monitoring, alert rule, task instance, workflow instance, operation log, baseline assurance, failure recovery, DataWorks operations. Do NOT trigger: data source management, compute resources, resource groups, data development, MaxCompute table management, ECS/RDS/OSS operations, workspace member management, data quality, data lineage, data preview.
Configures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either. Use when the user mentions a rollout percentage, variant split, or traffic distribution; gives a ratio like 60/40, 70/30, or 80/20; asks "who sees the test variant?"; wants to increase, decrease, or change the rollout or split on a draft or running experiment; weighs equal vs uneven splits; or proposes a mid-experiment split change (often an anti-pattern that needs reset or end-and-restart).
Diagnose why a data warehouse sync is failing and recommend the right recovery action. Use when the user asks "why isn't my Stripe/Postgres/Hubspot sync working?", "this table has been stuck for hours", "the data in the warehouse looks wrong", or wants to troubleshoot a specific source or schema. Covers source-level vs schema-level failures, stuck Running states, credential and schema-drift errors, incremental-field misconfig, CDC prerequisite failures, and the cancel / reload / resync / delete-data recovery actions.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
Use when answering Scenario admin analytics questions about Creative Unit consumption, most-used models, usage by user or project, AI adoption observability, cached usage data, CSV exports, enterprise PDF reports with charts, or a local analytics dashboard. Keywords: usage API, CU, analytics, adoption, reporting, consumption, cache.
Use when the user asks about revenue, payments, subscriptions, billing, CRM deals, support tickets, ad spend, production database tables, or other data PostHog does not collect natively — or wants to join or correlate PostHog product events with that external business data. Also use when a query fails because a table does not exist or returns no results for expected external data. The data warehouse can import from SaaS tools (Stripe, Hubspot, Zendesk, etc.), ad platforms, production databases (Postgres, MySQL, BigQuery, Snowflake), and other arbitrary data sources. Covers checking existing sources, identifying the right source type, and guiding the setup.
Core reference for DefiLlama MCP tools. Maps DeFi questions to the correct tool call with proper parameters. Covers entity conventions, metric interpretation, stock vs flow distinctions, percentage formatting, and error recovery. Use whenever querying DeFi data — protocol TVL, token prices, chain metrics, fees, revenue, yields, stablecoins, bridges, ETFs, hacks, raises, treasuries, or institutional holdings.
Expert-level Power BI, DAX, M language, data modeling, Power Query, report design, and paginated reports. Use when the user mentions DAX, Power Query, BI, Microsoft platforms, analytics, or data modeling, or when the task involves DAX Fundamentals, Advanced DAX, Row-Level Security, or Report Design.
Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.
Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.
Explore PostHog's Inbox and act on what it surfaces — the place where signal reports cluster into actionable issues and trends. Use when the user asks "what's in my inbox?", "what should I look at?", "which reports are actionable?", "what's PostHog flagged recently?", asks about a specific report by ID or title, wants to act on / fix / implement a report (turn it into a PR), wants to resolve, dismiss, or snooze a report, or wants to see which signal sources are configured. Covers listing, filtering, drilling into, and acting on reports, plus pointers to the deeper `signals` skill when raw signals or semantic search are needed.
Comprehensive evaluation of potential stock investments combining valuation analysis, fundamental research, technical assessment, and clear buy/hold/sell recommendations. Use when the user asks about buying a stock, evaluating investment opportunities, analyzing watchlist candidates, or requests stock recommendations. Provides specific entry prices, position sizing, and conviction ratings.
Change the sync configuration of an existing data warehouse schema — switch sync_type, pick a different incremental_field, set primary_key_columns, choose cdc_table_mode, or change sync_frequency. Use when the user asks “switch my orders table from full refresh to incremental”, “this table is syncing too slowly / too frequently”, “I need to pick a different incremental column”, “set up CDC for this Postgres table”, or when diagnosis of a failing sync pointed to an incremental-field or PK misconfiguration.
Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.
Patterns for DeFi market analysis, screening, and comparison using DefiLlama MCP tools. Covers valuation ratios (P/S, P/F), growth screening with pct_change columns, multi-metric protocol comparison, category comparison, and cross-entity analysis. Use when users ask to compare protocols, screen for undervalued projects, analyze growth trends, or do sector analysis
The foundational library for creating static, animated, and interactive visualizations in Python. Highly customizable and the industry standard for publication-quality figures. Use for 2D plotting, scientific data visualization, heatmaps, contours, vector fields, multi-panel figures, LaTeX-formatted plots, custom visualization tools, and plotting from NumPy arrays or Pandas DataFrames.
Upgrades a project's Metabase Modular embedding SDK (@metabase/embedding-sdk-react) or Modular embedding (embed.js) version. Use when the user wants to upgrade their Metabase modular embedding integration to a newer version.
NocoBase 2 only; never use in a NocoBase 3 project. Create and manage NocoBase data models through the available data-modeling surface. Use when users want to inspect or change collections, fields, relations, or view-backed schemas in a NocoBase app
Protocol and DeFi risk evaluation covering hack history, oracle dependencies, treasury health, TVL concentration, and yield sustainability. Use when the user asks "is X safe", "how risky is", protocol security, risk analysis, or wants to evaluate risk before investing or depositing funds.
Guide AI agents to generate complete PageObject pattern web scraper projects using Playwright and TypeScript with Docker deployment. Supports agent-browser site analysis for automated selector discovery. Keywords: scraper, playwright, pageobject, web scraping, docker, typescript, data extraction, automation.
Use this skill when users ask how to implement Syncfusion Pivot Table/PivotView in Blazor. Trigger for Blazor components, data binding, OLAP analysis, aggregation, drill-down/drill-through, grouping, filtering, conditional formatting, exports (Excel/PDF/CSV), or pivot charts. Blazor-only, not React/Angular/Vue/JS.
Analyze CRISPR-Cas9 genetic screens — MAGeCK gene-level scores, sgRNA count QC, replicate correlation, hit prioritization, and pathway GSEA on screen output. Use for genome-wide essentiality screens, synthetic-lethality discovery, dropout vs positive-selection screen analysis, target identification, and resistance-screen interpretation. Includes screen-QC and statistical thresholds.
Continuously collects over 1,000 daily articles with 100,000+ reads from public WeChat accounts across the internet and recommends popular articles that reach 100,000+ reads. Use when users want popular WeChat articles across all fields, daily recommendations of articles with 100,000+ reads, or viral articles in a specific field
Implement and audit privacy controls in product and infrastructure — GDPR, CCPA / CPRA, LGPD, PIPEDA. Covers data minimization, lawful basis, consent management, data subject access requests (DSARs — access, deletion, portability), data processing agreements, DPIA / TIA, breach notification timing, data classification, and the technical implementation of 'right to be forgotten' across backups, caches, analytics, and third parties. Use when the user mentions 'GDPR,' 'CCPA,' 'CPRA,' 'data privacy,' 'privacy engineering,' 'data subject access request,' 'DSAR,' 'right to deletion,' 'right to be forgotten,' 'data portability,' 'consent management,' 'cookie consent,' 'data minimization,' 'DPIA,' 'data protection impact assessment,' 'breach notification,' 'DPA,' 'data processing agreement,' 'sub-processor,' 'cross-border data transfer,' 'SCCs,' or needs to implement or review privacy controls.
Comprehensive single-protocol analysis combining TVL, fees, revenue, yields, events, income, and user activity. Produces a full protocol report. Use when the user asks for a complete overview, deep dive, "tell me everything about" a protocol, or a protocol research report.
Comprehensive token analysis combining price, market cap, unlock schedule, DeFi deposits, and yield opportunities. Use when the user asks to analyze a token, research a token, check token fundamentals, or wants full token intelligence including vesting and DeFi usage.
VCF and variant analysis — parsing, annotation, classification (synonymous, missense, frameshift, stop_gained), VAF filtering, coding vs non-coding categorization, multi-condition variant comparison, variant-notation conversion (SPDI/HGVS/VCF/rsID interconversion, ALFA per-ancestry allele frequencies), European Variation Archive (EVA) lookups (per-study cohort variant data, RS-accession resolution), HGVS validation/normalization (Mutalyzer), gene-specific curated variants (LOVD), canonical cross-database allele IDs (ClinGen Allele Registry), automated ACMG/AMP classification (GeneBe), principal-transcript selection (APPRIS), Ensembl linkage disequilibrium (LD) for GWAS/fine-mapping, GRCh37/GRCh38 coordinate liftover and protein/cDNA-to-genomic mapping, and Ensembl ID utilities (stable-ID version history, cross-references, region/gene feature overlap, assembly/species metadata). Use for VCF parsing, variant fraction calculations (denominator = coding subset only, NOT all variants), per-sample mutation profiling, converting a variant between SPDI/HGVS/VCF-coordinate/dbSNP-rsID representations, cross-checking a variant against EVA's raw submitted study cohorts, validating an HGVS string's syntax, looking up curated variants for a well-studied gene, resolving a variant to its ClinGen CA ID, getting an automated ACMG verdict, or picking a gene's principal transcript.
Full blockchain ecosystem analysis covering TVL, top protocols, bridge flows, stablecoin supply, DEX volume, fees, and user activity on a chain. Use when the user asks about a blockchain's ecosystem, "what's happening on Solana", chain health, or a chain-level overview.
Access and analyze comprehensive drug information from the DrugBank database including drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. This skill should be used when working with pharmaceutical data, drug discovery research, pharmacology studies, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task requiring detailed drug and drug target information from DrugBank.
Write raw ClickHouse SQL for a SigNoz dashboard panel: timeseries, value, or table widgets that the builder UI cannot express (custom joins, window functions, regex extraction over log bodies, aggregations beyond builder syntax). Trigger when the user explicitly asks for a "ClickHouse query", a "raw SQL panel", a "custom SQL widget", or describes a SigNoz dashboard panel whose query needs SQL the builder cannot produce. Anchored to dashboard-panel SQL specifically. For ad-hoc data exploration that does not need to land in a panel, use `signoz-generating-queries` instead.
Guide for querying DeFi flow data and events using DefiLlama MCP tools. Covers bridge flows, ETF inflows/outflows, stablecoin supply, institutional/DAT holdings with mNAV ratios, hacks and exploits, fundraising rounds, CEX volumes, open interest, and protocol treasuries. Use when users ask about bridge volume, ETF flows, stablecoin supply, MicroStrategy holdings, DeFi hacks, funding rounds, exchange volume, or treasury data.
Detect and analyze adverse drug event signals using FDA FAERS reports, drug labels, and disproportionality statistics (PRR, ROR, IC). Generates quantitative safety signal scores (0-100) with evidence grading. Use for post-market surveillance, pharmacovigilance, drug safety assessment, regulatory submissions, and detecting rare AE signals not visible in clinical trials.
Helps developers read Chainlink price feeds with AggregatorV3Interface and latestRoundData. This is not a Data Streams report. REST and WebSocket report streams go to chainlink-data-streams-skill. It applies to price feed integration, feed address lookup, consumer contracts, multi-chain feeds, MVR bundle feeds, SVR and OEV feeds, feed monitoring, historical data, L2 sequencer checks, rates and volatility feeds, and SmartData and RWA feeds.
Route observability work from the current packet into one monitoring brief. Use when the main job is deciding service-health signals, telemetry rollout, dashboard/alert coverage, pipeline freshness/schema monitoring, or game live-ops visibility; choosing between service reliability, telemetry foundation, review audit, data/pipeline, and live-ops modes; and naming one smallest implementation slice. Route outage-log root cause to `log-analysis`, code-level failure isolation to `debugging`, bottleneck tuning to `performance-optimization`, rollout execution to `deployment-automation`, LLM-specific tracing to `langsmith`, and engine-profiler interpretation to `game-performance-profiler`.
Implement Syncfusion Blazor Query Builder component for building dynamic, customizable query interfaces with complex filtering logic. Use this when creating advanced search interfaces, implementing business rule engines, or building data filtering workflows with nested condition groups and AND/OR logic. Supports rule management, drag-drop UI, state persistence, and extensive customization options.
This skill should be used when the user asks about "token price", "market data", "technical analysis", "sentiment", "trending tokens", "price chart", "market cap", "token research", "what's the price of", "analyze token", or any market research query. Provides guidance on token research, analysis, and market intelligence.
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.