Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
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Use when writing, reviewing, or modifying unit/integration tests, adding test cases, assertions, or mocks, or deciding whether a piece of code is worth testing — especially when tempted to add tests for coverage, over-mock dependencies, or write formalistic tests that just restate the implementation.
End-to-end feature testing — browser QA, API verification, eval tests, or any combination. Covers browser interactions (via agent-browser CLI), Google Workspace operations (gws CLI), API calls, and LLM eval tests. Can also persist tests as reusable QA flows or eval files.
Automatically suggest tests for new functions and components. Use when new code is written, functions added, or user mentions testing. Creates test scaffolding with Jest, Vitest, Pytest patterns. Triggers on new functions, components, test requests, testing mentions.
Audit and refactor UI code so every color value comes from the theme. Replace hex codes, rgba(), hsl(), oklch() literals, and named CSS colors with theme palette tokens (primary, secondary, error, warning, info, success, background, text) and the alpha() helper for transparency. Use when writing or reviewing any UI component, when starting a new MUI or design-system theme, when a designer hands off colors as hex annotations, when seeing color literals scattered across component files, or when an LLM produced styling with hardcoded hex values. Counterweight to LLM training corpora dominated by tutorial code that inlines hex codes and rgba literals instead of role-based theme tokens.
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
An end-to-end thesis writing assistance system for Chinese undergraduates. Supports an end-to-end workflow from topic selection to submission, including plagiarism-reduction optimization, AIGC reduction, and local detection features. Triggered when the user says 「帮我写论文」 or 「帮我降重」 and similar.
Use when reviewing or managing Things 3 through the sole Things++ MCPHub group `things`: capture, triage, planning, projects, headings, tags, dates, checklists, UI handoffs, cleanup, and reports. NOT for calendars, email, other task managers, MCP setup, direct database/raw automation, or secrets.
Improve documentation and comment prose so it describes the current state of the code directly and reads clearly in plain language, cutting history, transitions, and trivial detail. Works in two modes: on the current changes (session edits, uncommitted work, or the branch diff) or on named files/folders. Use when the user wants to clean up, tighten, or improve docs or comments — in a file, folder, project, or in what was just changed ('tidy the comments in this diff', 'clean up the docs we just edited', 'fix docs before committing') — make docs clearer / more concise / more readable, remove 'previously / now / no longer / migrated from / instead of' phrasing, make docs timeless, or asks to 'improve docs prose'.
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.
Guides TinyRobot Vue AI chat UI implementation, setup, and code generation. Use when the user mentions TinyRobot, OpenTiny TinyRobot, Bubble, Sender, Prompts, chat container, message list, conversation tools, or asks to build chat interfaces with TinyRobot components.
Current Ethereum development tools, frameworks, libraries, RPCs, and block explorers. What actually works today for building on Ethereum. Includes tool discovery for AI agents — MCPs, abi.ninja, Foundry, Scaffold-ETH 2, Hardhat, and more. Use when setting up a dev environment, choosing tools, or when an agent needs to discover what's available.
Comprehensive chemical safety and toxicology assessment integrating ADMET-AI predictions, CTD toxicogenomics, FDA label safety data, DrugBank safety profiles, and STITCH chemical-protein interactions. Performs predictive toxicology (AMES, DILI, LD50, carcinogenicity), organ/system toxicity profiling, chemical-gene-disease relationship mapping, regulatory safety extraction, and environmental hazard assessment. Use when asked about chemical toxicity, drug safety profiling, ADMET properties, environmental health risks, chemical hazard assessment, or toxicogenomic analysis.
Guide for building Graph Neural Networks with PyTorch Geometric (PyG). Use this skill whenever the user asks about graph neural networks, GNNs, node classification, link prediction, graph classification, message passing networks, heterogeneous graphs, neighbor sampling, or any task involving torch_geometric / PyG. Also trigger when you see imports from torch_geometric, or the user mentions graph convolutions (GCN, GAT, GraphSAGE, GIN), graph data structures, or working with relational/network data. Even if the user just says 'graph learning' or 'geometric deep learning', use this skill.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
Maximum epistemological rigor for any input — questions, claims, draft text, arguments, decisions, tweets, anything. Always runs the full truth-seeking pipeline: strips prestige, malformed framing, false confidence, adversarial framing, and heuristic overreach. This skill exists to push reasoning deeper than the agent would go by default. Use for anything where you want honesty over agreeableness. Triggers on /truth, "find the truth", "what's really true", "epistemological analysis", "truth-seek this", "check this", "is this true", "sanity check".
Explain and use Truto's core concepts and APIs — unified/proxy/custom APIs, integrated accounts, environments, webhooks, connection flows — and write application code against them. Covers what each concept is, how to call it, and data-access patterns for the user's codebase.
Improve one existing shipped skill from concrete feedback or a failed run via bounded PDCA. Use when skill instructions or package behavior look wrong and the fix belongs in that one package; otherwise route to the owning workflow. Triggers: tune-skill.
Enforce portable Turborepo + workspace monorepo house style: apps/packages layout, catalog pins, turbo.jsonc transit/cache rules, package scopes and exports, env ownership, scripts, filters, and dependency boundaries. Use when scaffolding a monorepo, adding a workspace, reviewing turbo/package layout, or when the user asks for turborepo-architecture. Optional with-* overlays for catalog, Knip, Oxlint/Oxfmt, Vitest workspaces, env packages, Effect packages, typegen, nested scopes, Docker prune, boundaries, and local compose. Not a Turbo CLI docs skill.
Harden code with patient, layered defense. The turtle carries its shell — bone-deep protection grown from within, not strapped on. Use when building new features to ensure they're secure by design, or when auditing existing code for deep vulnerabilities that slip through standard reviews.
Define tutorial scope, target audience, prerequisites, learning objectives, and a running example; output a tutorial spec for downstream planning. **Trigger**: tutorial spec, scope, audience, prerequisites, learning objectives, running example, 教程规格. **Use when**: the starting point of a tutorial pipeline (C1), where you need to lock down teaching goals and boundaries before moving to concept graph / module planning. **Skip if**: you are not producing a tutorial (or already have a clear tutorial spec that must not be changed). **Network**: none. **Guardrail**: structured spec first; avoid writing long tutorial prose too early (prose comes in C3).
Expert tvOS decisions for iOS developers: when to use custom focus effects vs system defaults, Siri Remote gesture trade-offs, Top Shelf content strategies, and 10-foot UI adaptation patterns. Use when building tvOS apps, debugging focus issues, or designing TV-optimized interfaces. Trigger keywords: tvOS, Focus Engine, @FocusState, isFocused, focusable, focusSection, Siri Remote, Top Shelf, TVTopShelfContentProvider, 10-foot UI, CardButtonStyle, large cards
Navigate Taiwan fintech regulations including FSC oversight, electronic payment laws, VASP rules, AML/KYC requirements, and the regulatory sandbox. Use this skill when the user is building a fintech product in Taiwan, needs to understand licensing requirements, assess crypto/VASP compliance, or apply for the regulatory sandbox — even if they say 'do we need a license', 'crypto regulation in Taiwan', 'KYC requirements', or 'fintech sandbox application'.
Write data-driven, evidence-first long-form Twitter posts on medicine and cardiology. Use when the user wants to: (1) Create thought leadership content in the style of Eric Topol, Peter Attia, Andrew Huberman, or Rhonda Patrick, (2) Present clinical evidence with charts, data, and Q1 journal citations for educated non-specialist audiences, (3) Write confident, matter-of-fact medical content that is rigorous without being inaccessible, (4) Explain trials, drugs, or medical phenomena using data visualization and systematic evidence review, (5) Build authority through methodological rigor and clear conclusions backed by evidence. NOT for newsletters or Substack. For Twitter long-form posts only.
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects.
Automates non-PHP TYPO3 upgrade migrations with Fractor for FlexForms, TypoScript, Fluid, YAML, XLIFF translation files, Htaccess, and composer.json changes. Use when running or configuring Fractor, upgrading non-PHP TYPO3 files, migrating FlexForms or TypoScript, modernizing Fluid templates, or combining Rector and Fractor for v14 work.
Dual-engine web search: Grok AI search (real-time web access + AI analysis) + Tavily search (structured results + web scraping). Any task that requires searching the web, finding the latest information, consulting documentation, getting news, or accessing the internet must use this Skill first. This is the primary search mechanism, replacing all other search methods.
Uninstall community skills installed through this hub. Confirms before deleting files, refuses to touch first-party plugin skills, and logs every action. Use when the user wants to fully remove a community skill ("uninstall [skill]," "remove this skill") rather than just disable it.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control
Translate text, files, and conversations between any languages. Auto-detects source language. Preserves formatting (markdown, code blocks, tables). Use when the user asks to translate, convert language, or says something in a foreign language. Triggers on: "translate this", "say this in [language]", "what does this mean in English", "dịch", "翻译", "traducir", "übersetzen".
Convert a public webpage URL into Markdown and save it as a reusable `.md` file with the bundled script. Prefer `https://r.jina.ai/<url>` first, and only fallback to `https://markdown.new/` if `r.jina.ai` is unavailable. Use this whenever the user wants to turn a public webpage, article, documentation page, blog post, release note, or reference URL into Markdown for reading, archiving, summarizing, extraction, RAG prep, or downstream agent reuse, even if they do not explicitly mention markdown or saving a file.
Quickly judge whether a processing activity requires a Personal Information Protection Impact Assessment, triggers the statutory assessment obligation under Article 55 of the Personal Information Protection Law, or can proceed directly — while also checking for personal information processing rule conflicts and routing to the correct next step. Use when the user asks "does this need a PIA," "triage this feature for privacy," "do a privacy check on X," "is this OK from a privacy standpoint," or describes a new personal information processing activity, product feature, or vendor relationship.
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.