Skills
100,344 packaged capabilities and playbooks for agents. Install any of them with one command.
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Image-based visual product search across Amazon sites, supporting reverse image search and discovery of visually similar products across 8 sites. Trigger this skill when the user mentions reverse image search, image search, visual search, finding the same item, visually similar products, finding products from an image, competitor image search, similar product discovery, image search, Amazon visual search, find similar products, reverse image lookup, visual search, similar items, competitor image search, or product image match. Also trigger when the user provides an image URL and wants to find matching or similar products on Amazon, even without explicitly mentioning image search.
Use multimodal AI to analyze product main images and extract visual features and prompts. Trigger this skill when users mention analyzing product images; extracting visual attributes from product images; identifying colors, shapes, materials, or styles in product listings; reverse-engineering image prompts; batch visual feature extraction; turning product image information into structured data; visual attribute statistics; image-based product classification; or main image analysis, image feature extraction, visual attribute recognition, product image analysis, image classification, or batch image analysis. Trigger it even if users do not explicitly mention “image analysis,” as long as their needs involve extracting structured information from product main or secondary images.
Tokenizes and analyzes product titles to extract attribute dimensions such as word frequency, scene terms, audience terms, and material terms. Use this skill when the user wants to analyze product titles, extract high-frequency title terms, tokenize titles, discover scene or audience terms, compare title keyword usage across products, optimize Listing titles based on word frequency, identify common attribute patterns across a group of ASINs, or perform title tokenization, word frequency analysis, scene keyword extraction, audience keyword analysis, title optimization, attribute keyword extraction, or keyword frequency analysis. Trigger this skill even if the user does not explicitly say “title analysis,” as long as they want to break product titles into meaningful phrases, count keyword frequency, or group products by extracted attributes.
Search and browse Walmart product listings by keyword, category, price range, and other criteria. Trigger this skill when the user mentions Walmart product search, Walmart product listings, Walmart price comparisons, Walmart competitor analysis, Walmart product selection research, Walmart market data, finding products on Walmart, Walmart search, Walmart products, Walmart product selection, Walmart pricing, Walmart competitors, or Walmart market. Trigger it even if the user does not explicitly mention “Walmart search,” as long as their request involves searching for products on Walmart, checking product availability, comparing Walmart prices, or analyzing Walmart product listings.
Creates comprehensive Magento 2 frontend solutions. Use when developing frontend features, working with layout XML, templates, JavaScript, or responsive design. Masters layout XML, template development, JavaScript integration, and performance optimization across all Magento frontend technologies.
Connects Render services over the private network—internal DNS, service discovery, and cross-service communication. Use when the user needs to wire services together, resolve internal hostnames, troubleshoot connectivity between services, configure environment isolation, or understand which services can reach each other.
Use when turning a reference video into 3D character animation through the Scenario MCP: markerless motion capture from a phone clip or a generated performance, auto-rigging an uploaded FBX, GLB, or OBJ character and applying the captured motion, raw motion on a Mixamo or MetaHuman skeleton to retarget yourself, in-place locomotion, looping clips, facial capture, or FBX exports for Blender, Maya, Unreal, Unity, or Roblox. Keywords: mocap, video to motion, video23d, animation from video.
RNA-seq differential expression analysis with DESeq2, edgeR, and limma-voom — DEG lists, fold changes, dispersion estimation, design formulas including covariates, multi-condition contrasts, and Venn-set operations across groups. Routes across DESeq2 (default), edgeR (QL-F / exact test for small replicate counts), and limma-voom (large n / complex designs). Use when you have a count matrix + metadata, want to find DEGs, or need dispersion/PCA/clustering analysis. Includes RULE ZERO precedence (read executed.ipynb if present).
Use this skill when the user asks to "create a style sheet", "style guide", "house style", "keep the voice consistent", "voice drift", "British or American spelling", "character voices", "lint the prose", "prose check", "filter words", "said-bookisms", "overused words", "repeated phrases", "similar character names", "voice fingerprints", or wants to record and enforce the voice and surface conventions of a story project. NOT for rewriting dialogue to make the voices distinct when everyone sounds the same (use line-editing), or a character's profile or arc (use character-management).
MUST be used for Vue.js tasks. Strongly recommends Composition API with `<script setup>` and TypeScript as the standard approach. Covers Vue 3, SSR, Volar, vue-tsc. Load for any Vue, .vue files, Vue Router, Pinia, or Vite with Vue work. ALWAYS use Composition API unless the project explicitly requires Options API.
Claude Code Bash tool patterns with hooks, automation, git workflows. Use for PreToolUse hooks, command chaining, CLI orchestration, custom commands, or encountering bash permissions, command failures, security guards, hook configurations.
Configures the analytics side of a PostHog experiment — exposure criteria (server-resolved default exposure event vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude from analysis" vs "Use first seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a secondary metric tracking 'downloaded_file' per user"), sets up a ratio metric (e.g. "revenue from purchase_completed / pageviews"), sets up a retention metric (e.g. "$pageview → uploaded_file, 7-day window"), configures custom exposure (e.g. "only count users who hit /checkout"), changes multivariate handling, or asks "who is in the analysis?", "how do I measure impact?", "is this winning?", "what's the confidence level?", or "should I ship?"
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).
Search the internet for technical documentation using the llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when the user needs: (1) the latest documentation for libraries or frameworks, (2) documentation in llms.txt format, (3) GitHub repository analysis, (4) documentation without direct llms.txt support, or (5) multiple documentation sources explored in parallel
Use when adding metadata to commits without changing history, tracking review status, test results, code quality annotations, or supplementing commit messages post-hoc — provides git notes commands and patterns for attaching non-invasive metadata to Git objects.
Expert patterns for Godot 3D lighting including DirectionalLight3D shadow cascades, OmniLight3D attenuation, SpotLight3D projectors, VoxelGI vs SDFGI, and LightmapGI baking. Use when implementing realistic 3D lighting, shadow optimization, global illumination, or light probes. Trigger keywords: DirectionalLight3D, OmniLight3D, SpotLight3D, shadow_enabled, directional_shadow_mode, directional_shadow_split, omni_range, omni_attenuation, spot_range, spot_angle, VoxelGI, SDFGI, LightmapGI, ReflectionProbe, Environment, WorldEnvironment
Expert blueprint for RPG stat systems (attributes, leveling, modifiers, damage formulas) using Resource-based stats, stackable modifiers, and derived stat calculations. Use when implementing character progression OR equipment/buff systems. Keywords stats, attributes, leveling, modifiers, CharacterStats, derived stats, damage calculation, XP
Structured logging with proper levels, context, PII handling, and centralized aggregation. Use for application logging, log management integration, distributed tracing, or when encountering log bloat, PII exposure, or missing-context errors.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Collect and analyze on-device performance metrics and crash diagnostics using MetricKit. Use when setting up MXMetricManager, handling MXMetricPayload or MXDiagnosticPayload, processing crash/hang/disk-write diagnostics via MXCallStackTree, adding custom signpost metrics, or uploading telemetry to an analytics backend
Migrate Python applications from the Claude Agent SDK to Pydantic AI and, only when needed, Pydantic AI Harness. Use when source code imports `claude_agent_sdk` or relies on Claude Code's agent loop, sessions, built-in tools, hooks, permissions, skills, or subagents. Do not use for the Anthropic Messages SDK or Claude Managed Agents.
Migrate Python Google Agent Development Kit (ADK) applications to Pydantic AI. Use for `LlmAgent`, `Runner`, sessions, state, memory, tools, callbacks, plugins, graph or dynamic workflows, resumability, events, artifacts, MCP, and ADK deployment boundaries.
Integrate Apple Music playback, catalog search, and Now Playing metadata using MusicKit and MediaPlayer. Use when adding music search, Apple Music subscription flows, queue management, playback controls, remote command handling, or Now Playing info to iOS apps.
Extract content from news sites. Supports 12 platforms: WeChat Official Accounts, Toutiao, NetEase News, Sohu News, Tencent News, BBC News, CNN News, Twitter/X, Lenny's Newsletter, Naver Blog, Detik News, and Quora. Activate when the user needs to extract news content, scrape official account articles, crawl news, or obtain news in JSON/Markdown.
Add, integrate, or build Preline UI components and blocks into HTML files via the Preline MCP server. Use when the user mentions "preline", says "/preline", asks to add a UI component, or requests a Preline block (a ready-made page section) using Preline UI.
Configures custom domains and TLS certificates on Render—DNS setup, CNAME records, apex domains, wildcard domains, and certificate troubleshooting. Use when the user needs to add a custom domain, configure DNS, set up HTTPS/TLS, troubleshoot certificate issuance, disable the onrender.com subdomain, or add a wildcard domain. Trigger terms: custom domain, DNS, CNAME, TLS, SSL, HTTPS, certificate, apex domain, wildcard domain, onrender.com, domain verification.
Use when writing or fixing Godot 4.7 shaders: .gdshader code (spatial, canvas_item, particles, sky, fog), VisualShader graphs built in code, stylized or toon water, dissolve or burn effects, hit flash, outlines, X-ray or portals with the stencil buffer, depth or screen-texture post-processing, global or per-instance uniforms, compute shaders and Texture2DRD, the shader baker; or when 'shader compiles but looks wrong', 'black screen from my post effect', 'my Godot 3 shader breaks', 'colors look washed out', 'first-launch shader stutter'.
Complete security remediation workflow. Scans code for vulnerabilities using Snyk, fixes them, validates the fix, and optionally creates a PR. Supports both single-issue and batch mode for multiple vulnerabilities. Use this skill when: - User asks to fix security vulnerabilities - User mentions "snyk fix", "security fix", or "remediate vulnerabilities" - User wants to fix a specific CVE, Snyk ID, or vulnerability type (XSS, SQL injection, path traversal, etc.) - User wants to upgrade a vulnerable dependency - User asks to "fix all" vulnerabilities or "fix all high/critical" issues (batch mode)
Programmatic UI sound design using Web Audio API and Tone.js. Use when creating click sounds, notification chimes, toggle feedback, hover sounds, success/error audio, whoosh effects, or building a sound library for UI interactions. Provides an iterative describe-generate-listen-refine workflow with audio engineering knowledge translated into plain English.
Synthesize qualitative and quantitative user research into structured insights and opportunity areas. Use when analyzing interview notes, survey responses, support tickets, or behavioral data to identify themes, build personas, or prioritize opportunities.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Reroll the Claude Code /buddy companion to a target species and rarity, or rename and customize its name and personality. Triggers on “reroll buddy,” “change buddy,” “legendary buddy,” “new companion,” “buddy hack,” “rename buddy,” “buddy name,” “buddy personality,” “换宠物,” “重新抽,” “传说宠物,” “改名,” “宠物名字,” “バディ変更,” “伝説バディ,” “バディ名前,” or similar.
Use when you need to review, improve, or refactor Java code for type design quality — including establishing clear type hierarchies, applying consistent naming conventions, eliminating primitive obsession with domain-specific value objects, leveraging generic type parameters, creating type-safe wrappers, designing fluent interfaces, ensuring precision-appropriate numeric types (BigDecimal for financial calculations), and improving type contrast through interfaces and method signature alignment. This should trigger for requests such as Review Java code for type design; Improve type design in Java code; Fix primitive obsession in Java code; Create value objects in Java code. Part of Plinth Toolkit
Use when you need to review, improve, or build Spring Boot 4.0.x applications — including proper usage of @SpringBootApplication, component annotations (@Controller, @Service, @Repository), bean definition and scoping, configuration classes and @ConfigurationProperties (with @Validated), component scanning, conditional configuration and profiles, constructor injection, @Primary and @Qualifier for multiple beans of the same type, bean minimization, graceful shutdown, virtual threads, Jakarta EE namespace consistency, and scheduled tasks. This should trigger for requests such as Review Java code for Spring Boot application; Apply best practices for Spring Boot application in Java code; Improve Spring Boot configuration properties and beans; Review Spring Boot component scanning and profiles; Tune Spring Boot graceful shutdown or virtual threads. Part of Plinth Toolkit
Catalyst QuickML — no/low-code ML, Generative AI, and ready-to-use AI platform. Covers (1) Prediction: ML pipelines, classification/regression, text analytics, recommendation, forecasting, clustering, anomaly detection, AutoML, prediction endpoints; (2) Generative AI: LLM Serving (chat, VLM), RAG, Knowledge Base, GenAI endpoints; (3) Zia Model Library: pre-built no-training models; (4) QuickML pricing — subscription plans and pay-as-you-go rates. Trigger on 'QuickML', 'AutoML', 'ML pipeline', 'train a model', 'model endpoint', 'LLM Serving', 'RAG', 'Knowledge Base', 'no-code ML', 'MLOps', or QuickML pricing/cost/billing/plan questions. DC availability: Prediction models all DCs; Generative AI (LLM Serving, RAG, Knowledge Base) NOT in AU, SA, or CA; Zia Model Library IN only.
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.