Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
This skill has instructions to setup a Envio HyperIndex indexer to capture onchain smart contract events. Use when user wants a historical feed or activity feed or some similar tracking feed or feature in their app or wants to capture onchain smart contracts events as a trigger to perform some other actions in their app. Also use this skill when the user wants to debug, restart, promote or delete and existing Envio indexer deployed on Envio Cloud
Use when creating, extending, debugging, or publishing a Lightweight Charts™ plugin—a custom series, a series primitive, or a pane primitive—or when turning a chart idea (“I want the chart to show/draw X”) into a working plugin. Covers choosing the plugin type, scaffolding with create-lwc-plugin, building on @tradingview/lwc-toolkit instead of hand-rolled helpers, which official plugin packages to use as references, where the docs are, and the autoscale, whitespace, visible-range, hit-test, and conflation mistakes every plugin author makes once. Use whenever the user mentions a custom series, primitive, renderer, drawing on the chart canvas, lwc-plugin, plugin-examples, the toolkit, or the plugin catalog—even if they never say the word “plugin”.
Cancer cell-line selection and profiling for experimental model choice. Cross-references DepMap, Cellosaurus, COSMIC, and PharmacoDB to provide identity verification, mutation/CNV profiles, gene dependencies, drug sensitivities, and druggable targets. Use to answer “Which cell line should I use for studying gene X?” or “Is this cell line a good model for cancer Y?” Outputs ranked recommendations with rationale, growth characteristics, and known pitfalls.
Computational vaccine candidate design: peptide/subunit vaccines via MHC-I/MHC-II epitope prediction (IEDB), population HLA coverage optimization, B-cell epitope identification, and cross-strain conservation analysis. Use for vaccine epitope prediction, HLA allele coverage, multi-epitope construct design, and immunogenicity assessment. Combines predicted MHC binding with experimentally validated IEDB epitopes for higher-confidence designs
Functional annotation of protein variants — ProtVar structural/functional context, ClinVar clinical classifications, gnomAD population frequencies, CADD deleteriousness, ClinGen gene-disease validity, plus FAVOR one-call comprehensive GRCh38 annotation. Use for variant annotation pipelines, missense effect prediction, and protein-level variant interpretation with functional context.
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.
Use Bright Data's Discover API for intent-ranked, AI-relevance-scored web search at scale, not keyword SERP. Trigger a discovery job and retrieve ranked results (link, title, description, relevance_score) with optional parsed page content. Use for semantic or intent-based web search, finding pages about a topic that match a goal, web-grounded retrieval for an LLM, or results filtered by relevance rather than raw keyword rank. Covers the REST API (POST/GET /discover), the CLI (`bdata discover`), and the Python/JS SDKs (`client.discover`), including the standard/zeroRanking/deep/fast modes. This is the foundation skill for `live-research` and `rag-pipeline`. For keyword SERP use `search`; for structured platform data use `data-feeds`.
Investigate LLM spend in PostHog: total cost over time, cost by model, provider, user, trace, or custom dimension, token and cache-hit economics, and cost regressions. Use when the user asks "how much are we spending on LLMs?", "which model / user / feature is most expensive?", "why did cost spike?", wants to build a cost dashboard or alert, or pastes a trace URL and asks about its cost.
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.
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.
Educator morning course health check for Canvas LMS. Shows submission rates, struggling students, grade distribution, and upcoming deadlines. Trigger phrases include "morning check", "course status", "how are my students", or any start-of-day teaching review.
Plans new DataHub connectors by classifying the source system, researching it using a dedicated agent or inline research, and generating a _PLANNING.md blueprint with entity mapping and architecture decisions. Use when building a new connector, researching a source system for DataHub, or designing connector architecture. Triggers on: “plan a connector,” “new connector for X,” “research X for DataHub,” “design connector for X,” “create planning doc,” or any request to plan, research, or design a DataHub ingestion source.
Model best-case, worst-case, and likely revenue scenarios with sensitivity analysis for strategic planning. Use when: building financial forecasts; presenting board scenarios; planning headcount around revenue uncertainty; modeling pricing changes impact; preparing investor updates with upside/downside ranges
Design ObjectStack data schemas — objects, fields, relationships, validations, indexes, hooks, security, seeds, and datasources. Use when creating or modifying `*.object.ts` files or `src/data/*.ts` seed modules, choosing field types, modeling relationships, writing `beforeInsert`/`afterUpdate` hooks, configuring per-object access control, pointing an object to an existing external database, or authoring bootstrap/demo data. Use for `visibleWhen`/`readonlyWhen`/`requiredWhen` rules that belong on fields. Do not use for querying data (see objectstack-query) or for plugin/kernel hooks (see objectstack-platform). For CEL expressions, load objectstack-formula alongside
Orchestrate multi-simulation campaigns: generate parameter sweep configurations (grid, linspace, or Latin Hypercube sampling), initialize and track batch job campaigns, monitor job completion status, and aggregate results with summary statistics across all runs. Use when running a parameter study across dt, kappa, or other simulation inputs, managing dozens or hundreds of simulation configurations, combining outputs from completed batch runs to find the best result, or automating the generate-run-collect workflow for systematic studies, even if the user only says “I need to try many parameter combinations” or “how do I organize a sweep.”
Implements Syncfusion® .NET MAUI Cartesian Chart (SfCartesianChart) for data visualization with 20+ chart types including line, area, column, bar, financial, statistical, and stacked charts. Use when implementing cartesian charts, line charts, area charts, or financial charts (candle, OHLC). Covers chart axes, legends, tooltips, trackball, zooming and panning, chart annotations, and trendlines.
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.
Alicloud OSS AI Content Awareness Skill. Use for enabling and querying OSS semantic search with AI-powered content understanding. Triggers: “OSS AI Content Awareness”, “OSS semantic search”, “OSS vector search”, “search by text”, “text-to-image search”, “text-to-video search”, “OSS MetaQuery”, “OSS data index”, “OSS AI内容感知”, “OSS语义检索”, “OSS向量检索”, “以文搜图”, “以文搜视频”, “OSS数据索引”
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
Expert performance marketing guidance for paid acquisition, CRO, and growth optimization. Use when creating ad campaigns, writing ad copy, optimizing landing pages, setting up A/B tests, analyzing CAC/LTV, building attribution models, or planning retargeting strategies. Use for Google Ads, Meta Ads, LinkedIn Ads, conversion tracking, budget allocation, and funnel optimization.
Transforms data into compelling visual narratives by applying narrative structure, annotation techniques, scrollytelling patterns, and honest framing to data journalism, presentations, and infographics. Use when creating data-driven articles or reports, designing infographics with narrative, building scrollytelling experiences, annotating charts to guide interpretation, or when user mentions data storytelling, presentation design, annotated chart, narrative visualization.
Query, audit, and optimize Google Ads campaigns. Use an attached browser or the Google Ads API for campaign, keyword, budget, conversion-tracking, and wasted-spend analysis, or when the user explicitly requests a reviewed account change. Defaults to read-only reporting; account mutations require a bounded preview and action-time approval.
Creates scoped key-value stores, reads and writes state entries, lists keys, and performs partial updates across functions. Use when persisting data between invocations, managing user sessions, caching computed values, storing feature flags, sharing state between workers, or building a KV data layer as an alternative to Redis or DynamoDB.
Registers state-type triggers that automatically fire functions when key-value state is created, updated, or deleted within a scope. Use when building reactive side effects, change watchers, audit logs, cache invalidation, notification dispatchers, or any observer pattern where data changes should trigger downstream processing.
Plan and create Meta (Facebook + Instagram) advertising campaigns end-to-end via the Hyper MCP, defaulting to Advantage+ automation. Use when the user wants to launch Meta ads, Facebook ads, Instagram ads, Advantage+ campaigns, carousel ads, dynamic creative ads, set up Meta conversion tracking, analyze performance, audit a Meta ads account, or build Meta performance dashboards. Also triggers on phrases like meta campaign, facebook campaign, advantage+, or meta account audit.
Use this skill whenever the user asks for a forecast, projection, extrapolation, or run-rate (MRR, ARR, revenue, or subscribers N months out; revenue to the end of the month or year), or asks what ad spend or acquisition is needed to hit a growth target. Load it before pulling charts for the projection.
Translate technical analysis into business language. Use when explaining statistical concepts to non-analysts, simplifying technical findings, or bridging communication between data teams and business stakeholders.
Interpret hits from CRISPR-KO/CRISPRi/shRNA screens by integrating DepMap essentiality, gnomAD constraint scores, pathway context (Reactome, STRING), druggability (DGIdb), and clinical evidence (CIViC, COSMIC). Use for screen-hit prioritization, essentiality ranking, and turning a list of screen hits into a prioritized target shortlist.
Standalone evaluation of an existing PDB directory with Proteina-Complexa. Use this skill whenever the user wants to "evaluate PDB files", "re-fold these designs", "compute interface pAE", "compute i_pLDDT for a folder", "run AF2 / RF3 / ESMFold on my designs", "score binder candidates", "designability of this folder", "scRMSD for designs", "motif RMSD for these PDBs", "complexa analysis", "complexa evaluate from a PDB directory", "evaluate from pdb dir", or score third-party outputs (BindCraft, AlphaProteo, RFdiffusion, hand-curated decoys). It picks the correct `evaluate_*.yaml` config, wires `++dataset.pdb_dir` and the folding backend, runs `complexa analysis` (the evaluate → analyze chain), parses the result CSV, reports pass-rates against the right `result_type` thresholds, and emits a replayable `eval_manifest.json`. Reach for this skill before hand-rolling refolding scripts.
Builds reactive real-time backends on the iii engine. Use when building event-driven apps where state changes automatically trigger side effects, clients receive live updates via streams or websockets, or you need a real-time database layer with pub/sub and CRUD endpoints.
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.