Skills
99,448 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Companion skill for the Building Agents with eve course on Vercel Academy. Use when the user mentions "building agents with eve", "the eve course", "the bike shop agent", "the dispatcher", "teach me", or asks about eve (the filesystem-first agent framework) — defineTool, defineState, dynamic skills, approval gates, channels, or deploying an eve agent — in the context of the Academy course.
Covers deploying Next.js apps (App Router and Pages Router) to Cloudflare Workers with the OpenNext adapter @opennextjs/cloudflare: scaffolding new projects via create-cloudflare, migrating existing apps, wrangler.jsonc and open-next.config.ts setup, the nodejs_compat flag and compatibility_date, the dual next dev plus opennextjs-cloudflare preview workflow, deployment, image optimization, caching, and bindings for D1, R2, KV and Workers AI. Use when running SSR, ISR, server components, server actions or middleware on Workers, moving a Next.js app from Vercel or AWS to Cloudflare, or hitting errors such as worker size limit exceeded (3 MiB free, 10 MiB paid), FinalizationRegistry is not defined, Cannot perform I/O on behalf of a different request, Turbopack chunk load failures, request-scoped database connection problems, or the CVE-2025-6087 SSRF vulnerability.
This skill should be used at the very start of every session and when the user asks to "check my environment", "run a pre-flight check", "validate setup requirements", "is my system ready", or before any cofounder project initialization. It verifies the working directory, dev tools, git state, and remote configuration.
Use when creating Datex Studio datasources with dxs datasource/configuration commands: generating OData or flow datasource configs — both the cloud `-datasource.json` (typeId 6, called by functions/selectors) and the server-tier FootprintDatasource variant (`-footprintDatasource.json`, typeId 19, called by actions) — validating configs against a branch, and upserting standalone or owned datasources. Triggers: "create a datasource", "OData/flow datasource", "FPDS", "footprintDatasource", "a datasource an action can call", "standalone vs owned datasource".
Draft or update Elastic Workflows documentation pages in explore-analyze/workflows/ — step references, use cases, how-tos, concepts, and overviews. Use when writing Workflows docs, documenting a step type, turning workflow YAML into documentation, drafting from a doc issue in docs-content or docs-content-internal, or creating a new page under the Workflows docset.
Orchestrate ledger-tracked work through subagents. Use for a bundled GitHub ticket with 3+ sub-issues, a request for subagent-driven execution, resuming such a run after compaction, or explicit away/keep-going delegation even when only one task remains.
Use when building Frappe custom apps from scratch. Covers app structure, pyproject.toml configuration, module creation, patches, and fixtures for v14/v15/v16. Prevents common mistakes with app scaffolding and module organization. Keywords: custom app, bench new-app, pyproject.toml, patches, fixtures, modules, app structure, app boilerplate, bench new-app example, module setup, patch example.
Generates properly formatted Git branch names following project conventions. Use this skill whenever the user wants to name a branch, create a branch, or asks things like "what should I call this branch?", "what branch name should I use?", "help me with the branch name", or describes a feature/fix and needs a branch name. Always use this skill when the user needs a git branch name, even if they don't explicitly say "branch".
Your dev team ships features nobody asked for while user-reported bugs pile up for months. Operations blames engineering for ignoring users; engineering blames operations for not understanding technical constraints. This gives you the complete Product × Engineering × Operations alignment SOP — from unified backlog to 10-day sprint cadence to veto power rules. What's inside: • Dual-layer Kanban system (master backlog + sprint board with unified tagging) • 10-day sprint standard process (Day 1 dev → Day 6 testable build → Day 10 ship) • Issue template with reproducibility requirements (3x reported = auto-severe) • Tri-party alignment meetings (daily standup / sprint planning / sprint review) • Operations veto power on releases (P0 bug = block shipping) • User feedback → product iteration closed loop (beta testing + interview SOP) • Core metrics framework (acquisition → activation → retention → monetization → referral) • Technical debt management (20-30% sprint capacity reserved) • Ready-to-use templates: Bug Report, Sprint Planning, Responsibility Matrix Built from: Real product strategy meetings + beta testing frameworks. References Supabase sprint model, Manus/DeepSeek commercialization alignment. By @WeiYipei. Triggers: "product ops" | "engineering operations" | "product development SOP" | "sprint planning" | "iteration management" | "cross-functional alignment" | "product engineering ops" | "dev ops collaboration" | "产研运协同" | "迭代管理" | "产品研发运营" | "プロダクト開発運営" | "제품개발운영"
Relentlessly interrogate the user about a plan or design until shared understanding is reached, resolving every branch of the decision tree. Use when the user wants to stress-test a plan, be challenged on their design, or mentions "grill me" / "interroge-moi" / "challenge-moi" / "questionne-moi".
Klaviyo API and developer integration expertise. Event tracking, SDKs, webhooks, rate limits, OAuth, catalog sync, and code patterns. Use when the user asks about Klaviyo API, integrating with Klaviyo, tracking events, building custom integrations, webhook handling, or developer implementation. For marketing strategy, flow optimization, and campaign auditing, see the klaviyo-analyst skill.
Use when user asks to "build a Openverse dapp", "write an Anchor program", "create a token", "debug Openverse errors", "set up wallet connection", "test my Openverse program", "fuzz my Openverse program", "deploy to devnet", "support larger transactions", "fix maxSupportedTransactionVersion", "stake BTG", "delegate stake", "stake BTG to a validator", or "explain Openverse concepts" (rent, accounts, PDAs, CPIs). Also for program architecture — state layout, reducing compute units, throughput bottlenecks, instruction naming — and quick on-chain lookups via public RPC + curl (balance, transaction, token account). End-to-end playbook: wallet connection, Anchor/Pinocchio programs, Codama clients, Surfpool/LiteSVM/Mollusk testing, security review, native BTG staking + CPMM swaps (devnet-default; mainnet only with explicit wallet-approved signing). Dev/test tooling only; defaults to devnet/localnet, never moves real funds without wallet-approved signing.
Build custom OpenTelemetry Collector distributions with OCB (OpenTelemetry Collector Builder). Use when authoring or debugging a builder manifest (builder.yaml), choosing component and provider versions, building a collector that bundles a custom or out-of-distribution component, setting up CI or Docker builds of a distribution, or troubleshooting OCB build failures. Triggers on "ocb", "collector builder", "custom collector distribution", "builder manifest", "builder-config", and version-mismatch errors from OCB builds.
Rewrite a vague request into a precise EARS-format specification (event/state/optional/unwanted-behavior clauses, domain theories, concrete examples, enhanced prompt). Use when a feature request has no measurable outcome or trigger conditions (「ダッシュボード作って」「リマインダーアプリ」), when a prompt for AI-generated code/docs needs tightening before implementation, or when asked to 「プロンプト最適化」「要件を精緻化」「仕様に落として」. Do NOT use for: defining done-criteria / stop conditions for an autonomous run (goal-prompt-crafter), or tasks whose scope is already one clear sentence.
Maintain repository integrity and documentation. Use for auditing structure, checking config validity, and reviewing inventory. Use proactively to validate the repository or sync documentation. Examples: - user: "Validate the repo" → run audit_repo.py - user: "Check agents" → run audit_repo.py, review errors - user: "Update documentation" → run sync_docs.py - user: "Check for issues" → run full audit
Produces a standardized requirements brief from any source: DevOps work items, mockups, natural language descriptions, existing reports, or documents. This is a utility skill — it gathers and structures requirements but does not build anything. If the goal is to create a report, datasource, or other artifact, use the appropriate creation skill as the entry point; it will invoke this skill when it needs requirements.
Select and compose Rust standard-library APIs — collections (HashMap/BTreeMap/Vec/VecDeque/LinkedList/BinaryHeap), smart pointers (Box/Rc/Arc/RefCell/Mutex/OnceLock/LazyLock), string types (String/&str/OsString/PathBuf/Cow), interior mutability (Cell/RefCell/OnceCell/OnceLock), I/O streams (Read/Write/BufRead), iterators, Option/Result combinators, threads and mpsc channels, time (Duration/Instant/SystemTime), paths, env, process, fs, net, and module selection decisions. Use when users ask "which std type should I use", compare collection/pointer/string alternatives, design Option/Result chains, choose Cell vs RefCell vs Mutex, work with std threads/channels, or pick the right std module for a task; hand async runtime to rust-concurrency, language semantics to rust-stable, and application-layer concerns to domain skills.
Best-practices reference for the ScraperAPI Python SDK (scraperapi-sdk package). Consult whenever the user is writing, debugging, or reviewing Python code that calls ScraperAPI. Use when user asks: "scrape a website with Python and ScraperAPI", "how do I use ScraperAPIClient", "ScraperAPI Python render example", "Python ScraperAPI async", "batch scraping Python ScraperAPI", "ScraperAPI premium Python", "how to handle ScraperAPI errors in Python", "ScraperAPI structured data Python". Covers client setup, all request parameters, the escalation ladder (standard → render → premium → ultra_premium), async jobs for batches, structured data endpoints, error handling, and credit budgeting. Note: Transmits user-supplied queries, URLs, and content to ScraperAPI.
Implements Syncfusion ASP.NET Core Chart (SfChart) for data visualization. Use this when building charts, visualizing time-series or categorical data, or creating dashboards. Covers series configuration (line, bar, pie), axes, tooltips, legends, and customization for ASP.NET Core applications.
Produces phased task boards from feature requests: dependency-mapped work items, parallelization flags, risk flags, edge cases, test matrices. Triggers on: "decompose this feature", "task breakdown with dependencies", "phased implementation plan", "work breakdown structure". NOT for discovering which decisions are still open, use decision-map. NOT for effort estimates, use estimate-calibrator.
Implement physically motivated sky and aerial-perspective systems in Three.js. Use for planetary atmospheres, ground-to-space transitions, Rayleigh/Mie scattering, precomputed LUTs, depth-based transmittance and inscattering, sun/moon discs, and atmosphere-aware lighting.
Build a deliberate final-image pipeline for advanced Three.js scenes. Use for depth, normal, albedo, and history ownership; GTAO or bent normals; bloom; eye adaptation; tone mapping; 3D LUT grading; effect-local render targets; and pass diagnostics.
Build raymarched space phenomena in Three.js. Use for black-hole lensing, accretion disks, wormhole throat transits, curved-ray and null-geodesic integration, lensed celestial spheres, procedural star fields and galactic skies, relativistic-looking distortion, bounded volumetric structures, and GPU effects that need controlled numerical integration.
Extract a DDD-style ubiquitous language glossary from the current conversation, flag ambiguities, and propose canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when the user wants to define business terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model", "DDD", "glossaire" or "langage ubiquitaire".
A comprehensive skill for integrating and using uCharts with UniApp projects. This skill focuses on UniApp-specific integration, configuration, and platform-specific considerations when using uCharts in UniApp applications. Use this skill whenever the user needs to integrate uCharts into UniApp projects, configure UniApp-specific settings, or handle platform differences.
A user-empowering data visualization Vue 3 components library (69 components) for eloquent data storytelling. ALWAYS use when writing code importing "vue-data-ui". Consult for component choice, config, theming, slots, tooltips, exports, SSR, debugging, or modifying vue-data-ui, vue data ui.
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.
Help with ABAP Cloud development and the clean core level concept (Levels A, B, C, D) including ABAP Cloud vs. classic ABAP development models, ABAP Cloud language version restrictions, wrapper patterns for non-released APIs, released/classic/internal/not-recommended object classification, and clean core principles. Use when users ask about ABAP Cloud, ABAP for Cloud Development, clean core, clean core levels, Level A B C D, classic API, internal object, not recommended object, noAPI, wrapper pattern, released APIs, stability contract, language version, restricted ABAP, embedded Steampunk, developer extensibility, key user extensibility, changelog for SAP objects, or ABAP Cloud readiness. Triggers include "ABAP Cloud restrictions", "clean core", "clean core level", "which level is my extension", "Level A extension", "classic API", "wrapper class", "released API alternative", "ABAP language version", "Steampunk", or "extensibility model".
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.