Skills
100,928 packaged capabilities and playbooks for agents. Install any of them with one command.
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Install, configure, and start FireRed-OpenStoryline from source on a local machine. Use when a user asks to set up OpenStoryline, troubleshoot installation, download required resources, fill config.toml API keys, or launch the MCP and web services, as well as Chinese requests like “安装 OpenStoryline”, “配置 OpenStoryline”, “启动 OpenStoryline”, “把 OpenStoryline 跑起来”, “修复 OpenStoryline 安装问题”, or “排查 OpenStoryline 启动失败”.
Creates or updates a GitHub pull request for the current branch. Use when the user asks to publish committed branch changes as a PR or refresh the body of an existing PR. Do not use for draft-only PR copy, PR review, CI repair, review-comment fixes, or a push that does not include creating or updating a PR.
Expert framework for assessing and achieving product-market fit. Combines PMF measurement methodologies, Sean Ellis survey, retention analysis, segment-specific PMF, and post-PMF scaling strategy. Use when determining if product has PMF, measuring user engagement, running PMF surveys, or deciding whether to scale or keep iterating.
Build, revise, and debug Bayesian models with PyMC. Use when choosing likelihoods and priors, specifying model/data dimensions, fitting hierarchical models, GPs, time series, mixtures, BART or splines, using pymc-extras distributions, marginalization, state-space models or model-building tools, selecting inference methods, resolving failed initial evaluation or model/data shape errors, generating predictions, or testing model code with simulated data and simulation-based calibration (SBC). Covers PyMC 6+, PyTensor 3+ and ArviZ 1.0 DataTree workflows.
Use this skill when the user asks to “follow red team methodology,” “perform bug bounty hunting,” “automate reconnaissance,” “hunt for XSS vulnerabilities,” “enumerate subdomains,” or needs security researcher techniques and tool configurations from top bug bounty hunters
Extracts figures and sub-figures from academic PDF papers. Supports Fig/Figure, Scheme, Chart, Supplementary Figure, Extended Data Figure (Nature), and Chinese equivalents (图/方案/示意图/附图/补充图). Sub-figure label recognition supports (a)/(A)/a)/(i)/(1)/a. formats. High-quality PNG output at configurable DPI. Use when user asks to "extract figure", "截取文献图片", "提取子图", "get figure from paper", "Scheme", "方案图", "补充图", "Supplementary Figure", or "Extended Data".
Audit and generate structured data (JSON-LD) for a page — detect, validate, and complete Tier-1 schema.org types (Article, Organization, Person, Product/Offer, BreadcrumbList, LocalBusiness, Review, VideoObject, Event), flag microdata/RDFa and deprecated-for-rich-results types (FAQPage/HowTo), and produce ready-to-inject JSON-LD blocks. Module M5. Feeds both the Search SEO and AI Visibility scores.
Sends, receives, and tracks email via the Mailgun (Sinch) API. Use when the user wants to send email, manage domains, configure webhooks, query email events/logs, manage templates, handle suppressions (bounces, unsubscribes, complaints), set up inbound routes, manage mailing lists, DKIM keys, or IP warmup using Mailgun
Comprehensive ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) profiling for drug candidates. Integrates ADMET-AI predictions, SwissADME drug-likeness, PubChemTox experimental toxicity, ChEMBL clinical data, Lipinski rule-of-five, and CYP interaction data. Use for drug-likeness assessment, BBB penetration, bioavailability, hepatotoxicity prediction, ADME/PK profiling, or screening compound libraries before lab testing
Universal data access patterns for downloading and parsing scientific data when ToolUniverse tools don't cover the source, only return metadata, or you need bulk records. Use for VCF/h5ad/BAM/SDF/GCT parsing, multi-step API workflows (search to filter to download to parse), thousands of records at once, or sources with no dedicated tool. Write Python code via Bash for every step
Protein 3D structure prediction from sequence — ESMFold de novo prediction, AlphaFold database retrieval, experimental structures from RCSB, ProtVar variant impact assessment, ProtParam sequence properties. Use for structure prediction when no experimental structure exists, fold-confidence scoring, and structure-guided variant interpretation.
Expert advisor on Vietnam Personal Data Protection Law (PDPL) compliance for Law No. 91/2025/QH15 and implementing Decree 356/2025/ND-CP (effective January 1, 2026). Use this skill for gap analysis against the Vietnam PDPL, data subject rights fulfilment workflows, cross-border data transfer impact assessments, privacy notices and internal policies, breach notification procedures, sector-specific obligations (finance, AI, cloud, blockchain), and DPO qualification reviews. Trigger whenever a user mentions Vietnam data privacy, VN-PDPL, Nghị định 356, Vietnamese personal data, or cross-border transfers involving Vietnamese citizens' data.
Generates XCUITest UI tests for iOS/iPadOS apps in Swift. Apple's native testing framework for reliable, fast UI automation. Supports local simulators and TestMu AI cloud real devices. Use when the user mentions "XCUITest", "XCTest", "iOS UI test", "Swift test", or "XCUIApplication". Triggers on: "XCUITest", "XCTest UI", "iOS UI test", "Swift UI test", "XCUIApplication", "TestMu".
Comprehensive guide for the XState v5 ecosystem, including state machines, actors, @xstate/store, and TanStack Query integration. Use when implementing state machines, event-driven stores, client state management, or integrating XState with React and TanStack Query for data-fetching orchestration.
Use when measuring whether an agent works: eval suites, trajectory judging, traces as regression fixtures, a calibrated LLM judge, and release gates. Triggers: “agent eval” / “эвалы агента”, “LLM judge” / “LLM-судья”. Not for ordinary unit tests or model benchmarks; the loop is agent-orchestrator.
Author useful, low-noise log alerts on services in a PostHog project. Use when the user asks to set up alerts for their logs, suggest alerts they should add, or evaluate whether a service is worth monitoring. Covers service triage, baseline characterisation, threshold drafting, back-testing via simulate, and shipping with a notification destination.
Expert AWS Cloud Advisor for architecture design, security review, and implementation guidance. Leverages AWS MCP tools for accurate, documentation-backed answers. Use when user asks about AWS architecture, security, service selection, migrations, troubleshooting, or learning AWS. Triggers on AWS, Lambda, S3, EC2, ECS, EKS, DynamoDB, RDS, CloudFormation, CDK, Terraform, Serverless, SAM, IAM, VPC, API Gateway, or any AWS service. Do NOT use for non-AWS cloud providers or general infrastructure without AWS context.
Use when building a storefront app or UI on the Bagisto Shop API — a customer-facing storefront, catalog, cart, checkout, customer account, wishlist, compare, reviews, or any page or component of a shop on the API, whether web, mobile or custom. Ask the client's platform and stack first, and treat the api-docs as the source of truth for exact shapes. Trigger phrases include "products", "cart", "checkout", "coupons", "customer login", "customer account", "wishlist", "storefront on the API".
Build professional 3D maps and GIS applications with MapV-Three—a 3D mapping library based on the Z-up coordinate system, with geospatial visualization features including map editing, measurement tools, feature drawing, and data management. Suitable for creating Web-GIS applications such as map editors, measurement tools, and spatial data visualizations.
Operate a reusable technical book manuscript workspace with writing structure, reader persona SSOT, review rules, and optional Markdown to Re:VIEW/PDF support. Use when organizing a book manuscript repo, defining or reviewing target readers, standardizing chapter/section files, setting writing/review agents, handling publisher proof comments, or assessing an existing writing workspace. Triggers on book writing workspace, reader persona, reader audience, 読者ペルソナ, persona SSOT, technical book project, 執筆ワークスペース, manuscript workflow, Re:VIEW workspace, proof PDF, annotated proof, publisher proof comments, 校正, 校正注釈, 初校, 入稿後の修正, and late-stage revision.
Take a PRD and build a dark factory around it: a repository that takes work in as an issue and ships validated code out with nobody at the keyboard, one component at a time, in the user’s actual repo. Covers five components in construction order: the guidance layer, validation harness, workflow-driven repo, deployment, and the trigger that makes it autonomous. It is agnostic about which coding agent runs underneath (Claude Code, Codex, Archon, the Agent SDK, Cline, Goose, Amp, Pi). It encodes the AI coding process the user already runs rather than replacing it. Requires a PRD as input and deliberately does not write one. Use when the user wants to build a dark factory, an autonomous or self-driving repository, a software factory, an agent that ships its own code, an unattended or overnight coding loop, asks how to reach level 4 or 5 of AI coding autonomy, or mentions dark factory, lights-out coding, autonomous PRs, or a repo that maintains itself.
Builds Nango Function implementation patterns for createTool() and createSync() without choosing a local CLI or remote API workflow. Use only when the user asks to create or update a Nango tool or sync and it is unclear whether the work should happen in a checked-out project via CLI or through Nango remote APIs. Do not load when building-nango-functions-locally or building-nango-functions-remotely applies; those skills overlap with this content and add workflow-specific validation and deploy details.
CustomShader authoring — vertexShaderText and fragmentShaderText against VertexInput, FragmentInput, FeatureIds, Metadata, czm_modelMaterial. Use when reading EXT_mesh_features or EXT_structural_metadata property textures/tables, vertex displacement, or shading VoxelPrimitive
Post-mortem analysis when a client churns. Takes client history, engagement data, support tickets, usage logs, and exit feedback to produce a comprehensive churn autopsy with root cause classification, timeline of decline, and preventive measures.
Auto-generates code flow diagrams from Python module analysis. Detects when architecture diagrams become stale (code changed, diagram didn't). Use when: creating new modules, reviewing PRs for architecture impact, or checking diagram freshness. Generates mermaid diagrams showing imports, dependencies, and module relationships.
Improve, debug, and extend an existing Contentful App Framework custom app in a customer's own repository. Use when users provide a bug report, feature request, support note, customer feedback, or direct change request for an existing custom app, including app configuration, sidebar, field editor, dialog, page, home, App Action, Function, installation parameters, local validation, or PR preparation. Also triggers on “fix my Contentful app”, “improve a custom app”, “enhance App Framework app”, “debug custom app”, “update sidebar app”, and “custom app feature request”. Not for creating a brand new app from scratch (contentful-custom-app-from-scratch), generic API examples (contentful-api), migrations (contentful-migration), or website integration (contentful-nextjs)
Query the DatoCMS Content Delivery API (CDA) — the read-only GraphQL API — using @datocms/cda-client. Use when users ask for GraphQL content reads: fetching posts/pages/projects, filtering by date/text/fields, sorting/order, pagination/load-more, text pattern matching via regex filters, localization and fallback locales, modular content fragments, Structured Text (DAST) with blocks/inline records, responsive images (srcset/blur-up/imgix), SEO metadata (_seoMetaTags, favicons, global SEO), video/Mux fields, draft or preview reads, environment-targeted reads, cache tags via rawExecuteQuery, why responses miss the CDN cache or hit rate limits, and Content Link metadata for visual editing. Also use for CDA query type generation with gql.tada or GraphQL Code Generator
Provides comprehensive guidance for draw.io architecture diagrams including diagram creation, shapes, templates, and collaboration. Use when the user asks about draw.io architecture, needs to create architecture diagrams, design system diagrams, or collaborate on diagrams.
Migrate legacy Salesforce UI stacks onto modern LWC — Aura → LWC conversion completeness verification and Lightning Out Beta → Lightning Out 2.0 host-page migration. TRIGGER on \"verify Aura to LWC migration completeness\", \"migrate Lightning Out Beta to LO 2.0\", \"upgrade $Lightning.use() to <lightning-out-application>\", \"replace hardcoded LO tokens with OAuth PKCE\", \"write an LO 2.0 host page\", or an external Lightning Out page that stopped rendering; also `.cmp`/`.js-meta.xml` files alongside LWC. DO NOT TRIGGER for the initial Aura-to-LWC conversion (use experience-aura-lwc-migrate), a React-to-LWC migration, or building a new LWC (use experience-lwc-design-generate).
Create new genre documentation files for the bitwize-music genre library. Use when the user wants to add a genre, says “/genre-creator”, “neues Genre erstellen”, “Genre hinzufuegen”, “add genre”, or asks to create genre documentation. Takes a genre name as an argument.
Data-driven resource harvesting (mining, logging, foraging) for Godot 4: apply_hit tool/tier validation via HarvestToolData enums, HarvestResourceData yields, harvestable_node shake/deplete, respawn_manager world persistence, UNIX offline progress, autosave, and noise vein proc-gen. Trigger keywords: apply_hit, HarvestResourceData, HarvestToolData, offline UNIX, respawn_manager, tool tier, harvestable_node, FastNoiseLite veins.
Search the web, news, and images through the Serper API. Use when the user asks to search the web, find current information online, verify recent facts, search Google, find images, or gather search results with source links.
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.