Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
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Use this skill to create multiple social media assets as a coordinated pack. Triggers: "social media content", "content pack", "social assets", "campaign assets", "instagram content", "tiktok content", "launch kit", "marketing kit", "content series", "social media kit", "multiple posts", "content calendar", "batch content" Orchestrates: multiple images, short videos, and audio for social platforms.
Triage a pasted batch of comments, mentions, and DMs from LinkedIn, X, Instagram, Facebook, or Threads, and draft on-voice replies where they're warranted. Use when the user says "help me reply", asks you to "draft responses to these comments", says "triage my mentions", or asks you to "answer these DMs". Each item gets bucketed as question, praise, objection, lead signal, or troll/spam, assigned a recommended action — reply, react-only, DM, or ignore — and, where a reply is warranted, a draft written in the user's voice. It reads social-context.md for brand voice, product facts, and escalation boundaries so replies sound like the user and never invent answers. Lead signals get flagged prominently with a suggested next step; legally or PR-sensitive items get escalated with a reason, not drafted.
Mine one long-form source — a blog post, video transcript, podcast episode, or talk — for its strongest atomic ideas and turn it into a full week of platform-shaped drafts for LinkedIn, X (Twitter), and Instagram, plus a short-video script. Use when someone says "repurpose this", "turn my blog into a week of posts", "slice this video into content", or "get a week of content from this". The output is a 7-day plan: two LinkedIn posts from different angles, one X thread, three single X posts, an Instagram carousel outline, and a short-video beat sheet — each standing alone with no "as I wrote in my blog" self-reference. For the same message posted across platforms at once, use social-crosspost instead. Reads social-context.md for brand voice and audience setup so every piece sounds like the author, not a summarizer.
Orchestrates a multi-module design session — prereq self-check, frontend routing stamp, issue clustering, module/seam design via codebase-design, TDD-ready issue rewrite, and batch tracker mutation — for a PRD + published backlog that spans two or more modules. Use when module and seam choices are still implicit after /to-issues has run.
Turn articles into hand-drawn explainer video B-roll. Given a WeChat Official Account article (text or link), prioritize extracting its original images, then turn its logic into an animated explainer video in a hand-drawn line-art style. Call real video models (Volcano Engine Seedance 2.0 or libtv Agent) to generate “hand-drawn growth” animation frame by frame, then assemble the final video. White background, black single-line icons, a single blue accent, thin curved arrows, 4:3 by default, designed to play under narration. Trigger when the user says “turn an article into an explainer video,” “hand-drawn explainer B-roll,” “animated whiteboard,” “make this article into an animated explainer,” or “generate B-roll with Seedance.”
Structures feature work for AI coding agents into gated phases — research, spec, plan, tasks, implement, validate — each producing a short reviewable artifact that constrains the next. Use when requirements are informal or drift-prone, when the same prompt produces different implementations across sessions, or when a feature touches auth, database schema, or API contracts. Keywords: spec-driven development, SDD, spec.md, plan.md, tasks.md, constitution.md, acceptance criteria, drift detection.
Pulls sports scores, standings, rosters, player/team stats, public sports news, editorial, wiki/video content, and betting odds through the Crawlora API — ESPN, SofaScore, MLB, Strava, DraftKings Sportsbook, Cricinfo, and Sportskeeda. Use for scores/stats or explicitly requested public sports-media research; Strava routes and clubs can reveal location-sensitive patterns.
Create Spotify playlists using spoti-cli CLI. Use when: (1) user wants a playlist, (2) user says "playlist", "spotify", "music for", "songs for", (3) user describes a mood or activity implying music ("deep work", "chill", "workout"), (4) user asks for music based on their day/vault/logs. Supports vault-aware playlist generation by reading Obsidian daily logs to infer mood and context.
Spring AOP (Aspect-Oriented Programming) per Spring Boot 3.x. Covers @Aspect, pointcut expressions, @Around/@Before/@After advice, custom annotations, logging, security, caching, and transaction patterns. Use for cross-cutting concerns. USE WHEN: user mentions "aspect", "AOP", "cross-cutting", "logging aspect", "pointcut", asks about "how to intercept methods", "apply logic to multiple methods", "@Around advice" DO NOT USE FOR: security configuration - use `spring-security` instead, transaction management - use `spring-data-jpa` instead
Spring WebSocket for real-time communication in Spring Boot 3.x. Covers STOMP over WebSocket, SockJS fallback, message brokers (simple and RabbitMQ/Redis), security, session handling, and testing. Use for chat, live notifications, and real-time updates. USE WHEN: user mentions "spring websocket", "STOMP", "SockJS", "real-time Spring", "@MessageMapping", "@SendTo", "WebSocket security", "message broker Spring", "chat application Spring", "live notifications" DO NOT USE FOR: REST APIs - use `spring-rest` skill, server-sent events only - use simpler SSE endpoints, NestJS WebSocket - use `nestjs-websocket` skill
Analyze sprint velocity data and produce an engineering team health report covering delivery trends, capacity utilization, and improvement recommendations. Use when asked to analyze sprint velocity, review team delivery health, identify delivery risks, or produce a retrospective data analysis. Produces a velocity trend analysis, health diagnosis table, top improvement recommendations with implementation steps, and a next-sprint capacity forecast.
Use this skill for reinforcement learning tasks including training RL agents (PPO, SAC, DQN, TD3, DDPG, A2C, etc.), creating custom Gym environments, implementing callbacks for monitoring and control, using vectorized environments for parallel training, and integrating with deep RL workflows. This skill should be used when users request RL algorithm implementation, agent training, environment design, or RL experimentation
Diagnose Kotlin + Spring failures from stack traces, startup logs, runtime logs, and related metric anomalies, then separate root causes from wrapper exceptions and propose safe next steps. Use when the application fails to start, an endpoint crashes, logs are noisy or deeply nested, or the agent must produce both a quick mitigation and a proper long-term fix without guessing.
Turn a contract review into a summary that business stakeholders will actually read. Not a legal memo — a two-minute answer to "can we sign? what do we need to know?" Use when the user says "summarize it for the business," "write it for [stakeholder]," "explain it to procurement," "non-legal summary," or needs to send something to non-lawyers after a review is complete.
Expert guidance for StarRocks database operations including table management, data loading, query optimization, materialized views, partitioning strategies, and cluster configuration. Use when working with StarRocks databases, OLAP queries, data warehousing, ETL pipelines, or when the user mentions StarRocks, distributed analytics, or columnar storage.
Iteratively build multi-page websites using Stitch. Reads next-prompt.md (the baton), generates the next page with Stitch MCP, integrates it into the site, then updates next-prompt.md to continue the loop. Works with stitch-design-md and stitch-ui-prompt-architect for consistent multi-page output.
Build, review, debug, configure, migrate, or plan Storybook 10 UI workshops with current docs. Use for storybook, create storybook, CSF3, CSF Next, Meta, StoryObj, definePreview, preview.meta, args, argTypes, decorators, parameters, tags, autodocs, play functions, storybook/test, @storybook/react-vite, @storybook/nextjs-vite, @storybook/addon-docs, @storybook/addon-a11y, @storybook/addon-vitest, portable stories, composeStories, main.ts, preview.ts, ESM config, Chromatic, @storybook/addon-mcp, componentsManifest, storybook skills/tools agent CLI, and upgrades from Storybook 8/9 (10.6.x current).
Guides organizational and business storytelling—narrative structure (setup, tension, resolution), audience-tailored stories for executives, customers, boards, and teams, honest data and metrics framing, product and strategy narratives, incident and postmortem storytelling, and actuarial or insurance risk narratives for non-technical audiences. Covers story spine, key messages, and visual or slide narrative outlines. Use when the user says "tell the story", "storytelling", "narrative for executives", "data story", "board presentation narrative", "explain with a story", "story arc", "key message", "compelling narrative", "pitch story", or "incident story"—not cross-department reframing only (cross-department-translation), company-wide comms cadence and crisis wording packs (communication-lead), long-form creative fiction or screenwriting, brand copy without strategy context, or technical documentation and API reference (tech-writer-researcher).
Expert knowledge for Supabase database, RLS, and backend patternsUse when "supabase, row level security, rls, postgres, database policy, supabase storage, supabase realtime, supabase, postgres, rls, database, backend, storage, realtime" mentioned.
Design and audit support deflection, knowledge bases, help-center search, article quality, macros, chatbots, in-product help, diagnostics, escalation paths, unresolved-user recovery, support analytics, and product feedback loops. Use when reducing tickets while preserving customer trust and fast human help for high-stakes issues.
Forecast and audit customer support workforce plans across channels, languages, queues, SLAs, severity tiers, launches, incidents, seasonality, shrinkage, occupancy, escalation, QA, macros, deflection, BPO/vendor coverage, and burnout risk. Use when support demand must be staffed without sacrificing quality or trust.
Flip Claude's default from validation to adversarial critique. Use when you are about to make a high-stakes decision, commit to a plan, or pitch something you have not stress-tested. Produces structured challenges, steelmanned counter-arguments, and the strongest case against your position — a genuine thinking partner, not a mirror.
Implement Calendar, DatePicker, DateRangePicker, DateTimePicker, and TimePicker components using Syncfusion JavaScript (EJ2) calendars library. Covers date/time selection, formatting, validation, localization, masking, accessibility, and advanced customization patterns.
Comprehensive guide for implementing Syncfusion EJ2 JavaScript Notification components including Message, Skeleton, and Toast. Use this when displaying contextual messages with severity indicators (Normal, Success, Info, Warning, Error) and display variants (Text, Outlined, Filled); creating animated loading placeholders with shapes (Circle, Square, Rectangle, Text) and shimmer effects (Wave, Pulse, Fade); configuring toast notifications with positioning, animations, templates, and dismissal patterns; or customizing notification appearance and accessibility.
Comprehensive guide to implementing, configuring, and customizing Syncfusion React Form Builder forms. Use when creating a Vite React form designer, loading an initial schema, configuring Form Builder props, choosing toolbox fields, defining templates, editing field properties, previewing JSON, importing or exporting schemas, or preparing a schema for Form Renderer. Read the schema references for validation, conditions, expressions, dependent dropdowns, dynamic ranges, remote data, and Data Grid fields.
Comprehensive guide to implementing, configuring, and customizing Syncfusion React Form Renderer forms from JSON schemas. Use when building or troubleshooting React forms, choosing supported field widgets, configuring field UI and templates, arranging panels, tables, tabs, and cards, binding dropdown, multiselect, and checkbox-group options to remote data, configuring grid data sources, conditional data, columns, expressions, validation, remote search, sorting, filters, and paging, adding built-in or custom validation, applying conditional rules, dependent dropdowns, dynamic min/max ranges, expression-driven values, or individual and grouped form actions. Check the component support matrix before applying conditional rules.
Use when the user has a messy tabular data dump (CSV/TSV/parquet/Excel/JSON) and wants it iteratively cleaned to an inferred data contract — a checklist of deterministic pass/fail checks, not a quality score. A single agent profiles the table, synthesizes a per-column contract compiled into binary checks (types, nulls, duplicates, inconsistent categories, format/range violations, outliers), then applies one targeted transform at a time, keeping it only if it reduces its target check's violations with no regression and no guardrail breach. Stops deterministically when every check passes, every remaining check is an unfixable residual, or a budget is hit; emits a replayable pipeline and an auditable ledger. Not for open-ended analysis of an already-clean dataset, diagnosing one known anomaly, or verifying a claim against sources — those are analytical loops; this rewrites the data to a contract.
TanStack Query (React Query) v5 best practices for data fetching, caching, mutations, and server state management. Use when building data-driven React applications, setting up query configurations, implementing mutations/optimistic updates, configuring caching strategies, integrating with SSR, or fixing v4→v5 migration errors.
Enforce portable TanStack Start app architecture: file-route trees, page folders with index.tsx, route colocation (-components/-hooks/-lib), reuse-gated src/modules, naming, and import boundaries. Use when scaffolding a Start app or feature, adding pages/layouts, reviewing or reorganizing route/module layout, or when the user asks for tanstack-start-architecture / Start house style. Optional with-* overlays for generated OpenAPI clients, Better Auth client, TanStack Query, route gates, TanStack Form, env, client authorization, UI package, Effect, and Vitest.
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.