Skills
100,928 packaged capabilities and playbooks for agents. Install any of them with one command.
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Enterprise AI adoption platform for Claude Code — measures team usage via OpenTelemetry, syncs skills/MCP servers/hooks from a central dashboard, and delivers context-aware skill suggestions at prompt time. Solves the Intention-Action Gap: organizations that deploy Zeude see 3x adoption improvement (6% → 18%). Requires Supabase (config) and ClickHouse (analytics). Triggers on: zeude, ai adoption, claude code adoption, enterprise claude, opentelemetry claude, skill sync, team claude management.
Expert knowledge for Azure Logic Apps development, including troubleshooting, best practices, decision-making, architecture and design patterns, limits and quotas, security, configuration, integrations and coding patterns, and deployment. Use for building Logic Apps with Azure/OpenAI, SAP/B2B, private endpoints, DevOps deployments, DR/multi-region designs, and other Azure Logic Apps development tasks. Not for Azure Functions (use azure-functions), Azure App Service (use azure-app-service), Azure Data Factory (use azure-data-factory), or Azure Integration Environments (use azure-integration-environments)
Turn a task or prompt into a deeper version of itself, not a bigger one. Before rewriting, say what a top professional in the field would do that the user isn't asking for, the rawest source material they would start from, the specific methods and tools they would use, and what (other than the user or the model) would show the result is right. Then rewrite the prompt to ask for exactly that. USE WHEN: /be-ambitious, "be ambitious", "make this prompt deeper", "what would an expert do here", "raise the bar on this task", "rewrite my prompt like a pro would ask it". NOT FOR: expanding scope, adding features, or general prompt polishing for tone or length
Start here for any Canvas component task to enforce the canonical Canvas component contract. Use for create, modify, refactor, review, migrate, or validate work. Establishes the canonical Canvas component contract, assuming repository components are Canvas targets, and guides either (1) transforming existing components to meet Canvas requirements or (2) creating new Canvas-ready components
Define valid component.yml metadata for Canvas components, including props, slots, and enums. Use when (1) creating a new component, (2) adding or modifying props, (3) troubleshooting “not a valid choice” or prop type errors, or (4) mapping enums to CVA variants.
Use when previewing, importing, cutting or joining images, video or audio in VN: cloud import through a link and QR code, rough cuts, slideshows, local drafts, /cawcut-vn, every delivery handoff. Generated media is imported by `asset_id` plus signed URL and never re-uploaded; cloud import needs login but no local VN install. NOT for changing picture content with AI (cawcut-workflow) or generating media.
Browser debugging, performance profiling, and automation via Chrome DevTools MCP. Use when user says "debug this page", "take a screenshot", "check network requests", "profile performance", "inspect console errors", or "analyze page load". Do NOT use for full E2E test suites (use playwright-skill) or non-browser debugging.
Write SEO-optimized blog posts, landing pages, and content improvements following Google's E-E-A-T and Helpful Content guidelines. Handles new content creation from a keyword or topic, and improving existing pages. Use when asked to "write a blog post", "create a landing page", "improve this page", "write content about X", "content for keyword X", "draft an article", "blog post about", "landing page for", "service page", "product page copy", "rewrite this page", "make this page rank better", "content brief", "how-to guide", "listicle", or any content creation or improvement task for a website.
Master Eugene Schwartz's 5 Stages of Awareness framework from "Breakthrough Advertising" (1966) to write copy that meets prospects where they are. Use when: Writing copy and unsure how "aware" your audience is; creating multi-stage funnels with different messaging per stage; building email sequences that nurture from cold to ready-to-buy; optimizing ads for different audience temperatures; diagnosing why existing copy isn't converting
Designs and builds ETL/ELT data pipelines. Takes data sources, destination, transformation requirements. Generates pipeline code (Python/SQL), scheduling config, error handling, monitoring setup, and data quality checks. Outputs data-pipeline-spec.md + implementation files.
Analyzes existing code to generate structured learning entries documenting patterns, decisions, and concepts. Works on files, directories, or entire projects. Supports selective (3–5 per file) and exhaustive modes, plus source annotations for fine-grained control.
Guides users through distributing Tauri applications on Windows, including creating MSI and NSIS installers, customizing installer behavior, configuring WebView2 installation modes, and submitting apps to the Microsoft Store.
Django migration patterns and safety workflow for PostHog. Use when creating, adjusting, or reviewing Django/Postgres migrations, including non-blocking index/constraint changes, multi-phase schema changes, data backfills, migration conflict rebasing, and product model moves that require SeparateDatabaseAndState. Also use for any deletion or removal of a model, table, column, product, or app — including deleting migration files or retiring a feature — even when no migration is written.
An agent orchestrator for cross-border e-commerce product sourcing. Use this skill when the user needs a complete Temu product selection workflow, five recommended products, or end-to-end product analysis. It automatically calls skills such as amazon-movers-shakers, temu-competitor-search, ali1688-sourcing, and temu-pricing-calculator to produce a complete product selection report meeting the V4.1 standard.
Review and create distinctive, production-grade frontend interfaces with high design quality and design system compliance. Evaluates using three pillars: frictionless insight-to-action, quality craft, and trustworthy building. Use for: PR reviews, design reviews, accessibility audits, design system compliance checks, creative frontend design, UI code review, component reviews, responsive design checks, theme testing, and creating memorable UI. Do not use for: backend API reviews, database schema reviews, infrastructure or DevOps work, pure business logic without UI, or non-frontend code
Professional UI/UX design expertise for React applications. Covers design thinking, user psychology (Hick's/Fitts's/Jakob's Law), visual hierarchy, interaction patterns, accessibility, performance-driven design, and design critique. Use when designing features, improving UX, solving user problems, or conducting design reviews.
Expert blueprint for console platforms (PlayStation, Xbox, Nintendo Switch) covering controller-first UI, certification requirements (TRCs/TCRs), platform services (achievements, cloud saves), and performance compliance. Use when targeting console releases or implementing gamepad-only interfaces. Keywords: console, PlayStation, Xbox, Switch, TRC, TCR, certification, controller, gamepad, achievements.
Expert blueprint for VR platforms (Meta Quest, PSVR, SteamVR, Pico), covering the XR toolkit (OpenXR), comfort settings (vignetting, snap turning, teleportation), motion controls, hand tracking, and 90+ FPS requirements. Use when targeting VR headsets or implementing immersive 3D experiences. Keywords: VR, XR, OpenXR, Meta Quest, motion sickness, comfort, locomotion, XRController3D, foveated rendering.
Generates monthly/quarterly investor updates. Takes KPIs, milestones, challenges, financials. Writes professional investor-update.md with highlights, metrics dashboard, product updates, team news, financial summary, upcoming milestones, asks. Multiple tones from seed-stage casual to Series B formal. Use when founders need to communicate progress to investors.
Manages all forms of test suite assignment for DevOps Center pipeline stages via the Connect API testSuiteStages endpoint. Covers three modes: (A) attaching a single suite to a stage as a one-off add, (B) bulk-mapping multiple suites to a stage as a testing strategy with a mandatory impact-preview table before any changes, and (C) adding or removing individual test classes within a suite assignment with governance rules that exclude rejected tests and re-present the final list before committing. TRIGGER when: a suite is found unlinked from a pipeline stage and the user wants to assign it; the user wants to configure suite-to-stage mappings across a pipeline or assign multiple suites to stages as part of a testing strategy; the user wants to add or remove tests in a suite, sync reviewed tests into a suite, or promote tests to a suite. DO NOT TRIGGER when: authoring new test classes (use generating-apex-test) or running tests directly (use running-apex-tests).
Applies n8n's RBAC scope decorators to REST endpoints. Use when creating a new @RestController, adding any @Get/@Post/@Put/@Patch/@Delete route to an existing controller, or reviewing endpoint authorization. Every authenticated endpoint must be gated by @ProjectScope or @GlobalScope.
Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".
Calculate comprehensive ROI for AI implementation projects. Takes current costs, manual process time, team size, and hourly rates. Generates detailed roi-analysis.md with executive summary, cost-benefit tables, sensitivity analysis, break-even timeline, and comparison scenarios. Use when evaluating AI investments, building business cases, or justifying automation spend.
Check whether your rules file (CLAUDE.md or AGENTS.md) still matches the codebase after recent changes — run before a merge, or fold into your code-review pass. Reports stale/now-false rules, drifted architecture-map entries, and any new invariant worth adding, each with the minimal edit. Advisory and anti-bloat: it keeps the rules file true, never longer than it needs to be.
Generates comprehensive operational runbooks for any system or process. Reads codebase, infrastructure config, and deployment scripts to produce structured runbook.md files formatted for on-call engineers. Use when you need operations documentation, incident response guides, deployment procedures, or disaster recovery plans.
Build and run AI-generated Bright Data scrapers from the terminal via `bdata scraper create` and `bdata scraper run`. Use this skill whenever the user wants to generate a scraper from a natural-language description, build a custom scraper without writing code, turn a URL + plain-English description into a reusable scraper, run an existing Bright Data collector against a URL, or batch-scrape a list of URLs through one collector. Triggers on phrases like 'build me a scraper for', 'create a scraper that extracts', 'generate a scraper from a description', 'turn this URL into a scraper', 'run this scraper on', 'run my collector', 'batch scrape', 'scrape these URLs', 'scrape a list of URLs', 'competitive pricing table', 'scraper studio', `scraper create`, `scraper run`, `--urls`, `--input-file`, `collector_id`, `automate_template`, or `/dca/`. Covers the AI flow (template create → trigger AI generation → poll progress), the single-URL run flow (async + poll by default, `--sync` for fast pages), the multi-URL batch flow (`--urls` / `--input-file` → one `/dca/trigger` call with array body), and the silent auto-fallback to the batch endpoint when a URL expands past the realtime page limit. Requires the Bright Data CLI.
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Use when the user asks to threat model a codebase or path, enumerate threats or abuse paths, or perform AppSec threat modeling. Do NOT use for general architecture summaries, code review, security best practices (use security-best-practices), or non-security design work.
Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.
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.