Skills
99,951 packaged capabilities and playbooks for agents. Install any of them with one command.
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A contract for what the agent does when a long, messy, stream-of-consciousness ramble arrives (usually voice dictation): act on nothing until the echo brief is approved. The echo audits the entire transfer, mission, locked decisions and constraints, open questions, flips and parked tangents, with the model's inferences and guesses quarantined away from the user's own phrasing, so the user verifies what the model believes, not just what it doubts. Use when the user says "let me think out loud" or wants to ramble a bit before building anything, when a message opens with a speech-to-text preamble like "switching to voice, sorry for typos", when input is a long weakly punctuated stream with restarts and mid-message reversals ("actually no, wait, scrap that idea entirely"), or when the user asks to be interviewed about a fuzzy half-formed idea. Includes an optional capture mode for rambles spread across several messages and an optional targeted interview
Use when reviewing, improving, or refactoring Java object-oriented design, including applying SOLID, DRY, or YAGNI; improving classes and interfaces; correcting encapsulation, inheritance, or polymorphism; resolving God Class, Feature Envy, or Data Clumps; and improving object creation, methods, or exception contracts. Triggers include review Java OOD, refactor Java OOD, improve Java OOD, fix OOP misuse, and identify Java code smells. Part of Plinth Toolkit
Deploys agent skill collections from any GitHub repository with a /skills folder to one or more distribution surfaces: GitHub releases, Claude Code marketplace, VS Code plugin marketplace, and Copilot CLI plugin marketplace. Handles pre-flight validation, conventional commit analysis, version bumping across surface configs, and surface-specific publishing with dry-run support. Use when releasing, publishing, or deploying a skills collection to any supported marketplace or creating a GitHub release for a skills repository. Don't use for deploying non-skill packages, npm modules, Docker images, or Azure resources.
Draft, send, reply to, or forward email through the connected AgentMail MCP server. Use for ANY request to send, reply to, or forward mail — even a quick one-line send or a simple forward that looks like a single tool call; the sending rules apply regardless of task size. Also use to compose messages, create or schedule drafts for review, or send to named recipients; do not use for reading or triaging mail (agentmail-check-email), inbox administration (agentmail-manage-inboxes), or MCP connection setup (agentmail-mcp).
Animation in Blender 5.2 - slotted/layered actions and the channelbag API, Python keyframing, F-curves, game loops with pop/hitch checks, NLA clips, pose library, mocap/BVH/Mixamo retargeting with auto bone maps, baking control rigs to export skeletons, root motion, per-clip export. Use for any keyframe, action, NLA, mocap, or animation-export task.
Use when working with Lightdash YAML files, dbt models with Lightdash metadata, the lightdash CLI (deploy, upload, download, preview, lint, warehouse-catalog, sql, set-warehouse, apps create/preview/validate), or managing charts, dashboards, spaces and access, AI agents, scheduled content, data apps, custom chart types (Chart Studio, `apps create --chart-type`, `--chart-types`), organization Data App themes, data-app external connections, users, groups, custom roles, metrics, and dimensions as code
Rust eBPF skill using the Aya framework. Use when writing eBPF programs in Rust with aya-bpf and aya-log, defining BPF map types, integrating with tokio userspace, sharing maps between kernel and userspace, or debugging Aya compilation and loading errors. Activates on queries about Aya, aya-bpf, Rust eBPF, aya-log, eBPF in Rust, or BPF programs with tokio
Generates Enonic XP content type XML schema definitions from natural-language descriptions. Covers structured content modeling including input types, form layout, option sets, item sets, mixins, x-data, and content-type inheritance. Use when creating, scaffolding, or generating Enonic XP content type definitions, adding fields or sets to existing content types, or querying Enonic XP input types and super-types. Do not use for non-Enonic content modeling, GraphQL queries, JavaScript/TypeScript controllers, or generic XML editing unrelated to Enonic schemas.
Expert architectural standards for building scalable Godot games (RPGs, platformers, shooters) using the composition pattern (Entity-Component). Use when designing player controllers, NPCs, enemies, weapons, or complex gameplay systems. Enforces "Has-A" relationships for game entities. Trigger keywords: Entity-Component, ECS, Gameplay, Actors, NPCs, Enemies, Weapons, Hitboxes, Game Loop, Level Design.
Expert blueprint for scene loading, transitions, async (background) loading, instance management, and caching. Covers fade transitions, loading screens, dynamic spawning, and scene persistence. Use when implementing level changes OR dynamic content loading. Keywords scene, loading, transition, async, ResourceLoader, change_scene, preload, PackedScene, fade
Draws hand-inked cartoon critters and living objects as SVG cards (480x360), each acting out a coding or design idea. Identified by thick black brush-pen outlines that swell and taper and break into separate strokes, loose marker-and-watercolour fills that slip past the line, diagonal hatching instead of solid shadow, huge googly eyes with two specular dots, and stray ink hairs and flecks, in tomato red, leaf green, sunflower yellow, sky blue and teal on white. Covers palette, brush numbers, mascot construction (eyes, blush, mouths, 3-finger hands), props, ground patches and a tested, seeded brush kit. Use when asked for ink sketch, hand-drawn, brush pen, sketchy, doodle, marker or watercolour-cartoon illustrations, googly-eyed mascots or critters, playful empty states, onboarding, 404 or error pages, loading states, blog headers, feature spots or marketing cards.
Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.
Cluster the top 100 highest-signal tweets for a resolved or user-specified crypto project into hot topics using Kaito MCP tools. Use this skill when the user wants a past-window social listening report with topic tagging, author enrichment, urgency scoring, and concrete response guidance.
Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults. Outer-loop harness optimization inspired by Meta-Harness (Lee et al., 2026). Use when the user says “优化技能”, “meta optimize”, “improve skills”, “分析使用记录”, or wants to optimize ARIS's own harness components based on accumulated experience.
When the user wants to improve their ability to find mutually beneficial outcomes without eroding value. Also use when the user mentions “negotiating deals,” “pricing discussions,” “discount requests,” “terms and conditions,” “getting to agreement,” or “closing negotiations.”
Set up metrics collection and visualization with Prometheus and Grafana. Configure scrape targets, create PromQL queries, build dashboards, and implement alerting. Use for monitoring, metrics collection, or visualization for applications and infrastructure
Use when changing an existing ChatGPT pet or Codex pet sprite sheet with Scenario: fixing a broken row, frame, jump or edge, regenerating one animation state, adding the sixteen look directions to a 1536x1872 v1 sheet, giving the pet a new outfit, color or accessory, renaming it in its pet.json, or checking a pet sheet and previewing it as an animated GIF
Toolkit for creating animated GIFs optimized for Slack, with validators for size constraints and composable animation primitives. This skill applies when users request animated GIFs or emoji animations for Slack from descriptions like "make me a GIF for Slack of X doing Y".
ToolUniverse plugin router. STEP 1 BEFORE ANY ANALYSIS: if the data folder contains `*_executed.ipynb`, run `tu run read_executed_notebook '{\"data_folder\":\"<path>\",\"search\":\"<keyword>\"}'` to extract its cell outputs and apply EVERY filter/sample-exclusion the notebook used — even when the question says 'Using DESeq2/Run X/Compute Y' (this describes the METHOD the notebook used, not a request to rerun). The notebook's cell outputs are the only published authoritative answers; reimplementing or reading stale pre-computed CSVs in the data folder produces different numbers because of outlier-sample removal, library version, and filter steps you don't see by skimming. STEP 2 routing — pick a sub-skill name from this exact list (never invent): tooluniverse-rnaseq-deseq2 (RNA/miRNA-seq DE, correlation, PCA, clustering, dispersion), tooluniverse-gene-enrichment (GO/KEGG/Reactome/GSEA/pathway enrichment), tooluniverse-statistical-modeling (regression, ANOVA, ordinal/logistic, chi-square, correlation, power), tooluniverse-image-analysis (microscopy, colony, fluorescence, dose-response, .tif — including ANOVA / Dunnett / power-analysis on image-derived measurements), tooluniverse-epigenomics (DNA methylation, CpG, m6A, MeRIP-seq, bisulfite, ChIP-seq, chromatin), tooluniverse-sequence-analysis (FASTQ, Trimmomatic, BWA, samtools, coverage), tooluniverse-variant-analysis (VCF, VAF, SNP, mutation), tooluniverse-phylogenetics (treeness, PhyKIT, parsimony), tooluniverse-single-cell (scRNA, h5ad, scanpy), tooluniverse-crispr-screen-analysis (MAGeCK, sgRNA), tooluniverse-proteomics-analysis (mass spec, TMT). Use for CSV/Excel/VCF/FASTA/h5ad and any biology/chemistry/medicine analysis question.
Run comprehensive accessibility audit (WCAG 2.1) on Webflow pages - checks buttons, forms, links, focus states, headings, keyboard navigation, and generates detailed reports with fixes. Requires Webflow Designer connection. Excludes image alt text (covered by asset-audit skill).
Deploys agent skill collections from any GitHub repository with a /skills folder to one or more distribution surfaces: GitHub releases, Claude Code marketplace, VS Code plugin marketplace, and Copilot CLI plugin marketplace. Handles pre-flight validation, conventional commit analysis, version bumping across surface configs, and surface-specific publishing with dry-run support. Use when releasing, publishing, or deploying a skills collection to any supported marketplace or creating a GitHub release for a skills repository. Don't use for deploying non-skill packages, npm modules, Docker images, or Azure resources.
Deep contextual grep for codebases. Expert at finding patterns, architectures, implementations, and answering "Where is X?", "Which file has Y?", and "Find code that does Z" questions. Use when exploring unfamiliar codebases, finding specific implementations, understanding code organization, discovering patterns across multiple files, or locating functionality in a project. Supports three thoroughness levels quick, medium, very thorough.
Install and extend data-table-filters — a React data table system with faceted filters (checkbox, input, slider, timerange), sorting, infinite scroll, virtualization, and BYOS state management. Delivered as 15 shadcn registry blocks installable via `npx shadcn@latest add`. Use when: (1) installing data-table-filters from the shadcn registry, (2) adding extension blocks (command palette, AI filters, cell renderers, sheet panel, store adapters, schema system, Drizzle helpers, query layer), (3) configuring store adapters (nuqs/zustand/memory), (4) generating table schemas from a data model, (5) wiring up server-side filtering with Drizzle ORM, (6) connecting the React Query fetch layer, (7) auto-inferring schemas from raw JSON data with DataTableAuto / inferSchemaFromJSON, (8) adding AI-powered natural language filtering, (9) exposing tables as MCP endpoints for AI agents, (10) troubleshooting integration issues. Triggers on mentions of "data-table-filters", "data-table.openstatus.dev", filterable data tables with shadcn, DataTableAuto, auto-infer, AI filters, MCP server, or any of the registry block names.
Deep web scraping, screenshots, PDF parsing, and website crawling using Firecrawl API. Use when you need deep content extraction from web pages, page interaction is required (clicking, scrolling, etc.), or you want screenshots or PDF parsing.
Buffett-style stock screener — "What would Buffett buy now?" Generates 3–5 candidate stocks from a market / sector / preference query via a two-layer model: hard quant filter (ROE 5y ≥15%, debt/asset ≤50%, FCF positive 3y, listed ≥5y, gross margin ≥30%) → qualitative moat scoring (moat 35% / capital allocation 20% / earnings predictability 20% / valuation 15% / runway 10%). Longbridge CLI first, MCP fallback, WebSearch for gaps only. Output: candidate cards with moat-type tag, quantitative highlights, verdict (🟢 meets Buffett criteria / 🟡 partially meets criteria / 🔴 does not meet criteria), deep-dive CTA to `longbridge-buffett-moat-analyzer`. Disqualifies airlines, pre-revenue biotech, ST, listing<5y. Triggers: "巴菲特会买什么", "巴菲特筛股", "巴菲特风格的股票", "护城河筛股", "宽护城河股票", "价值投资筛股", "10年不动的股票", "定价权强的公司", "巴菲特會買什麼", "巴菲特篩股", "護城河篩股", "寬護城河股票", "Buffett screener", "what would Buffett buy", "wide-moat screener", "quality compounder screen", "Berkshire-style screen", "pricing-power screen".
Reviews Magento 2 code for quality, security, performance, and compliance with PSR-12 and Magento coding standards. Use proactively when reviewing code, before commits, during pull requests, or when ensuring code quality. Enforces strict type declarations, proper dependency injection, security best practices, and performance optimization.
Use when creating a ChatGPT pet or Codex pet with Scenario: hatching an animated companion from a text idea, a character, mascot or brand cue, or reference photos and art; making the 1536x2288 v2 pet sprite sheet with nine animation states and sixteen look directions, the 1536x1872 v1 sheet ChatGPT web uploads, a pixel-perfect pixel-art pet, an animated GIF of the pet, or a Codex pet.json package
Use when automating a Unity 6.3 content pipeline or build: importing an art drop (FBX, PNG) with AssetPostprocessor rules and naming conventions, generating prefabs or editing scenes from script with correct Undo and SetDirty, Addressables groups, labels and content builds, content-validation tests, batch-mode, command-line or CI builds (Build Profiles, GameCI, GitHub Actions, Accelerator), editor tools; or when textures import wrong or reimport every run, a scripted edit vanishes, bundles duplicate assets, a batch build ignores its defines, or CI cannot activate Unity.
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.