Skills
99,951 packaged capabilities and playbooks for agents. Install any of them with one command.
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Prevents crashes due to problematic scope-related API misuse caused by agent escalation into internal scope framework objects. Use when configuring properties of scope-related Simulink blocks or MATLAB objects — constrains the agent to documented APIs and directs users to the scope UI when a property is not programmatically accessible.
Diagnose and fix parfor errors in MATLAB. Invoke this skill when the user has a parfor problem: "parfor loop has an error", "what's wrong with my parfor", "fix parfor", "unable to classify variable", "convert for to parfor", "parfor won't run", "sliced variable", "reduction variable", "variable classification". Also invoke when you read a .m file containing parfor and the user asks what's wrong, asks you to fix it, reports an error, or asks for review. Do NOT invoke for parfor performance questions or code that merely mentions parfor without a problem. ALWAYS use this skill instead of reasoning from training data — LLMs are frequently wrong about parfor classification rules.
Convert Markdown documents to PowerPoint presentations or generate presentations from scratch using AI. Use when users want to create PPT/PPTX files, convert MD to slides, generate presentations, make slideshows, or ask for help with PowerPoint creation. Supports custom templates, multiple themes (business, tech_dark, education, neumorphism), and intelligent content layout.
Video/audio/image processing with FFmpeg and ImageMagick. Tools: FFmpeg (video/audio), ImageMagick (images). Capabilities: format conversion, encoding (H.264/H.265/VP9/AV1), streaming (HLS/DASH), filters, effects, thumbnails, watermarks, batch processing, hardware acceleration (NVENC/QSV). Actions: convert, encode, resize, crop, compress, extract, merge, stream, transcode media. Keywords: FFmpeg, ImageMagick, video encoding, audio extraction, image resize, thumbnail, watermark, HLS, DASH, H.264, H.265, VP9, AV1, codec, bitrate, framerate, resolution, aspect ratio, filter, overlay, concat, trim, fade, batch processing. Use when: converting video/audio formats, encoding with specific codecs, generating thumbnails, creating streaming manifests, extracting audio from video, batch processing images, adding watermarks, optimizing file sizes.
How to benchmark and analyze memory usage in Turso using the memory-benchmark crate and dhat heap profiler. Use this skill whenever the user mentions memory usage, memory profiling, allocation tracking, heap analysis, memory regression, memory benchmarking, dhat, or wants to understand where memory is being allocated during SQL workloads. Also use when investigating memory growth in WAL or MVCC mode. IMPORTANT - If you modify the perf/memory crate (add profiles, change CLI flags, change output format, etc.), update this skill document to reflect those changes so it stays accurate for future agents.
Loads a fitted Meridian model and generates standard visualization reports: Model Results Summary. Use when the user wants to load a saved model and view results (model performance, fit, health). Don't use for running budget optimization (use meridian-budget-optimization) or building/fitting the model (use meridian-model-building).
Control the brain's information-processing flow through three metacognitive stages. Use when you "know what to do but can't do it", can't think rationally after being hijacked by emotions, or need to systematically improve the quality of your brain's information processing. Three stages: control input (attention gatekeeps the information entry point) → control the brain (discard/store/process information) → control output (execute thinking results at high quality). Not applicable to urgent situations requiring fast instinctive reactions. Key trigger signals: "know but can't do", "I got emotional again", "my mind is a mess", "I learned it but can't use it".
Port a Selenium WebDriver or Selenide (Java) test suite to CodeceptJS 4. Trigger when the project contains `pom.xml` declaring `selenium-java` / `selenide` / `webdrivermanager` / `junit-jupiter` / `testng`, a `build.gradle{,.kts}` with `org.seleniumhq.selenium` / `com.codeborne:selenide`, a `src/test/java/` tree with `*Test.java` / `*IT.java` / `*Steps.java`, imports from `org.openqa.selenium.*` (`WebDriver`, `By`, `WebDriverWait`, `ExpectedConditions`, `Actions`) or `com.codeborne.selenide.*` (`Selenide`, `SelenideElement`, `Condition`), JUnit/TestNG annotations (`@Test`, `@BeforeEach`, `@DataProvider`, `@FindBy`, `@ParameterizedTest`), `PageFactory.initElements(...)`, `new ChromeDriver(...)` / `Selenide.open(...)`, or Cucumber-JVM step defs (`@Given` / `@When` / `@Then`).
Migrates existing Nango TypeScript createSync implementations from nango.lastSyncDate, legacy incremental syncType, and non-resumable full refreshes to checkpoint-based syncs. Use when updating customer Nango sync code to define checkpoint schemas, call getCheckpoint/saveCheckpoint/clearCheckpoint after every batchSave (including inside paginate loops), test dryruns with --checkpoint, and fix deletion handling for checkpointed incremental or full syncs.
Generate Minecraft item/block textures (16x16 / 32x32 PNG) from AI-generated art. Use when the user asks to create, convert, or post-process Minecraft textures — e.g. "生成一个原味鸡的 MC 材质" or "把这张图做成 16x16 的 Minecraft 材质" — including white-background removal and per-block color sampling. Pairs with the `imagegen` skill for generation and the `minecraft-modding` skill for using textures in mods.
Research-driven UI/UX improvement using Mobbin. Use when user explicitly requests design pattern research ("use Mobbin", "research design patterns", "find UX patterns for X"). Requires Mobbin account and browser automation (claude-in-chrome MCP). Searches Mobbin for relevant UI patterns, extracts design principles, generates a spec document for approval, then implements. NOT for general UI work—only when user wants research-backed design.
Practical guidance for Go package design with minimal public APIs, single-responsibility boundaries, stateless-first flow, one-way state transitions, and orchestration-to-capability separation. Use when creating, refactoring, or reviewing Go architecture, package boundaries, interfaces, handlers, managers, builders, and execution flows.
MOEX ISS and ISS+ mechanics for raw REST endpoints, public iss.moex.com access, authenticated apim.moex.com access, output formats, iss.only, iss.json, start pagination by returned row count, response block normalization, discovery and history routes, calendars, boardgroups, and websocket/STOMP concepts.
How to write benchmarks in Motoko using bench-helper. Covers project setup (mops.toml), bench file layout in bench/*.bench.mo, the Bench.Schema rows/cols model, and safe patterns for encode/decode, hashing, crypto, and allocation benches.
Parallel multi-AI cross-validation research workflow (major version). Dispatch N internal sub-agents + grok + gemini in parallel, automatically cross-validate findings, tier by confidence (strong consensus / partial / conflict / insufficient), generate tiered action items with arbitration. Use when user says "multi-ai research", "cross-validate", "independent consensus", "three-brain research", "multi-ai research", "parallel research", "cross-validate", or needs deep research that benefits from internal data + external 2026 consensus. NOT for quick factual Q&A, pure code reasoning, or tasks needing deep project context.
Using the dbt-materialize adapter to manage Materialize streaming pipelines with dbt. Covers materializations (source, source_table, view, materialized_view, sink, table, seed), profile configuration, index creation, blue/green deployments (deploy_init, deploy_promote, deploy_cleanup), cluster management, strict mode, and testing. Use this skill whenever the user asks about writing dbt models for Materialize, configuring dbt profiles for Materialize, running dbt against Materialize, blue/green or zero-downtime deployments with dbt, creating sources or sinks in dbt, troubleshooting dbt-materialize issues, or migrating existing dbt projects to Materialize. Also trigger when the user mentions dbt-materialize, materialized_view materialization, deploy_init, deploy_promote, deploy_await, strict_mode, refresh_interval, retain_history, or partition_by in a dbt context.
Use when a Materialize object is behind wall-clock time — high lag in mz_wallclock_global_lag, a stale or lagging materialized view, index, or sink, a freshness alert, results that keep showing old data, or a dataflow whose output cannot keep up with its input.
n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.
Chinese web-novel character naming. Use when the user needs names for protagonists, female leads, villains, supporting characters or elders, wants to rename them, finds the names too common/too AI/overused (such as 叶辰苏念林婉儿), or says "I can't come up with names". Produces fitting, memorable character names by genre/era/status/gender, avoiding the cookie-cutter names churned out by web-novel pipelines.
Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose
Neta API content research and recommendation skill — provides keyword/tag/category suggestions, category path validation, and multi-mode content recommendation feeds, supporting progressive exploration from broad to precise. Use this skill when the user has no clear goal, wants to find creative subjects or trending directions, or needs systematic content filtering by keyword/category; it does not directly generate images/videos/songs (handled by neta-creative), and community interaction is handled by neta-community.
Associative memory with spreading activation for persistent, intelligent recall. Use PROACTIVELY when: (1) You need to remember facts, decisions, errors, or context across sessions (2) User asks "do you remember..." or references past conversations (3) Starting a new task — inject relevant context from memory (4) After making decisions or encountering errors — store for future reference (5) User asks "why did X happen?" — trace causal chains through memory Zero LLM dependency. Neural graph with Hebbian learning, memory decay, contradiction detection, and temporal reasoning.
Use this skill for Next.js App Router patterns, Server Components, Server Actions, Cache Components, and framework-level optimizations. Covers Next.js 16 breaking changes including async params, proxy.ts migration, Cache Components with "use cache", and React 19.2 integration. For deploying to Cloudflare Workers, use the cloudflare-nextjs skill instead. This skill is deployment-agnostic and works with Vercel, AWS, self-hosted, or any platform. Keywords: Next.js 16, Next.js App Router, Next.js Pages Router, Server Components, React Server Components, Server Actions, Cache Components, use cache, Next.js 16 breaking changes, async params nextjs, proxy.ts migration, React 19.2, Next.js metadata, Next.js SEO, generateMetadata, static generation, dynamic rendering, streaming SSR, Suspense, parallel routes, intercepting routes, route groups, Next.js middleware, Next.js API routes, Route Handlers, revalidatePath, revalidateTag, next/navigation, useSearchParams, turbopack, next.config
Select and refine a profitable, focused niche for a solopreneur business. Use when deciding which market segment to serve, narrowing a broad idea into a defensible position, or evaluating whether a niche is worth committing to. Covers niche generation, multi-criteria scoring, validation checks, and the Who+What+Why positioning formula. Trigger on "pick a niche", "what niche should I target", "narrow my market", "find my niche", "choose a niche", "is this niche viable", "niche down".
Complete "topic notebook build" workflow for Google NotebookLM — deep web research, sequential source loading (with known-failing domain skips), full Studio artifact generation, and curated chat-prompt library. Use this skill whenever the user wants to create a new NotebookLM notebook on a topic, build a full research notebook from scratch, generate a "{topic} :: docs" notebook, compile sources from forums (Reddit/HN/GitHub/Discord/Quora) into a notebook, produce a full Studio (audio + video + mind map + reports + flashcards + quiz + infographic + slide deck + data table) for an existing notebook, or prepare curated NotebookLM prompts for a topic. Triggers on phrases like "build a notebook on X", "create cmux :: docs", "research and build NotebookLM", "full studio for my notebook", "entire studio", "NotebookLM prompts for topic Y", "turn this into a NotebookLM notebook". Apply even when the user does not explicitly say "NotebookLM" — if they ask you to assemble a research notebook on a topic with sources and derivative artifacts, this is the right skill.
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
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.