Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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Internal UI/UX design review pass of the agentic-workflow review pack — composed in-turn by review-change and product-audit; not a menu entry. Checks the changed UI against the project's design doc: consistency, states, responsiveness, and reuse — applies only when the project has a UI and the change touches it. Findings only; never edits code.
Internal performance review pass of the agentic-workflow review pack — composed in-turn by review-change and product-audit; not a menu entry. Checks the changed paths for algorithmic and resource regressions: N+1s, hot-path allocations, asset weight, and leaks. Findings only; never edits code.
Internal security review pass of the agentic-workflow review pack — composed in-turn by review-change and product-audit; not a menu entry. Checks secrets, input validation, injection, authn/authz, PII exposure, and dependency risk on the changed surface. Findings only; never edits code.
Internal SEO review pass of the agentic-workflow review pack — composed in-turn by review-change and product-audit; not a menu entry. Checks changed web pages/routes for indexability, metadata, and structured data — applies only to public web surfaces. Findings only; never edits code.
Adversarially review a Technical Design Document and its ADRs, actively looking for gaps, risks, and weak decisions instead of validating them. Use when the user asks to challenge, stress-test, get a second opinion on, or adversarially review a technical design document, architecture decisions, or ADRs.
Use Riverpod family providers to pass parameters and cache per parameter; FutureProvider.family, NotifierProvider.family, autoDispose with family, overriding in tests. Use when fetching data by ID, pagination, or any provider that depends on a parameter. Use this skill when the user asks about family, provider parameters, or caching by ID.
Filesystem-based Roblox development with Rojo + Wally + Luau LSP + StyLua + selene. Use when setting up, modifying, or debugging .project.json sync, package manifests, toolchain pinning, sourcemap regen, editor integration, CI builds, or any filesystem-to-DataModel question. Tooling layer only — language rules live in luau-expert; runtime behavior lives in roblox-dev; UI libraries live in roblox-ui.
Maps the buying committee at a target account — identify decision-makers, influencers, champions, and blockers, then recommend a multi-threading strategy. Use when stuck single-threaded in a deal, don't know who the real decision-maker is, can't figure out the right entry point at a target account, deal stalled because you're not talking to enough people, or unsure how to map the buying committee. Do NOT use for building prospect lists across many accounts or general account research (use /sales-prospect-list), deal health assessment (use /sales-deal-inspect), or ZoomInfo-specific org chart config (use /sales-zoominfo).
Salla app monetization: plans and addons live in the publication's pricing section (no separate pricing endpoint), billed by Salla. Use when pricing the app, tracking plan/addon state, or gating features by entitlement. Track state from app.subscription.* / app.trial.* events (one family—item_type splits plan vs addon), reconcile via salla_apps action=subscriptions, meter usage against the balance. Signatures → salla-webhooks; tokens → salla-app-auth; wiring → salla-app-lifecycle; in-app purchase UI → salla-addon-purchase / salla-addon-purchase-embedded; server-computed amounts (credits, top-ups) → salla-checkout-sdk-purchase
The Salla app's App Store listing page (the page merchants see before installing). Use when customizing that listing page. Build it via the `app_page_builder` MCP tool as an ordered list of blocks; editing a block's elements writes shared listing content (name, description, logo, screenshots, benefits) into the app's draft publication. Prerequisite: call `app_publish action=open` first to create the draft — the builder is disabled until then. Upload media with `salla_upload`. Draft/publish flow and `short_description` → salla-publication-consistency. Schemas → salla-docs.
Owns native look-and-feel for a Salla app's EMBEDDED (dashboard) UI — the Partner-dashboard iframe on the Embedded SDK design system. Use WHENEVER an embedded/dashboard page draws visible UI (settings, analytics, addon flows). Its five binding gates must all pass — none skippable — and the final gate is a live demo-store screenshot. Not done until verified. Storefront UI → salla-storefront-ui; SDK/auth wiring → salla-embedded-app.
Preserve useful project knowledge through StrictDoc, Magic Context, and available memory tools, including overlapping storage where useful. Maintain readable current norms in StrictDoc; update them when a genuine decision change is clear and briefly inform the user, without routinely churning the canon. Ordinary memories and explanatory docs can evolve more freely. Favor concise phrases, lists, tables, and occasional PS explanations; choose storage, detail, and timing with judgment.
Prepare manuscripts for Science and the Science family of journals (Science, Science Advances, Science Translational Medicine, Science Robotics, Science Immunology, Science Signaling), covering Research Article vs Report formats, abstracts and one-sentence summaries, reference and notes style, Supplementary Materials, data/code policies, figure requirements and the initial-submission vs revision workflow. Use when targeting a Science journal, converting a manuscript to Science style, or checking a submission against Science author instructions.
Covers classical machine learning in Python with scikit-learn (sklearn): classification and regression estimators, clustering and dimensionality reduction, preprocessing, Pipeline and ColumnTransformer, cross-validation, metrics, and GridSearchCV hyperparameter tuning. Use when training or comparing classifiers and regressors on tabular or text data, clustering data and choosing the cluster count, building leakage-free preprocessing pipelines, evaluating models with cross-validation and metrics, or tuning hyperparameters. Not for deep learning; use a dedicated neural network framework instead.
Search award flight availability across 27 mileage programs via the Seats.aero Partner API or the official seats.aero MCP server. Find cheapest award flights, compare programs, and get booking links. The MCP works with no key for flights in the next 60 days. Pro sign-in on the MCP adds live search, alerts, award hotels, upgrades, and deals.
Guidance for Microsoft Security Copilot - the generative-AI security platform that helps analysts investigate, hunt, summarise, and respond using natural language, plugins, promptbooks, and embedded experiences. Covers SCU provisioning, plugins, promptbooks, governance, and the standalone vs embedded experience choice. WHEN: Microsoft Security Copilot, AI for SOC, security copilot units SCU, promptbooks, Copilot plugins, natural language investigation, summarise incident with AI, Copilot for Security setup, how do I use AI in my SOC, explain a KQL query with AI, summarise an alert for a stakeholder. DO NOT USE when the goal is configuring autonomous triage or remediation agents (use security-copilot-agents).
Use when reviewing code for security vulnerabilities, implementing authentication or authorization, handling user input, managing secrets, or auditing dependencies for known CVEs. Triggers: auth implementation, input handling, secrets management, dependency audit, pre-deployment security check, OWASP compliance review.
Review Sentry Python and Django changes for bug patterns drawn from real production issues. Use when reviewing a backend diff or PR, checking Warden findings, auditing the current branch, reviewing production-error patterns, or looking for common regressions in `src/` and `tests/`.
Guided entry point for using Sentry through your agent. Orients you to your current setup and, for a new project, sets up Sentry end to end with sane defaults — provision a project, install the SDK (errors, tracing, and whatever it enables by default), and confirm real telemetry reaches Sentry. Routes other intents (adding more signals, fixing issues) to the right skill.
Comprehensive SEO analysis for any website, page, business, or topic. Full site audits, SEO checks, single-page analysis, technical SEO (crawlability, indexability, Core Web Vitals with INP), schema markup, content quality (E-E-A-T), image optimization, sitemap analysis, GEO for AI Overviews/ChatGPT/Perplexity, and SEO best-practice planning. Industry detection for SaaS, e-commerce, local, publishers, agencies. Triggers on: SEO, audit, full SEO check, SEO best practices, optimize my site, ranking, organic search, schema, Core Web Vitals, sitemap, E-E-A-T, AI Overviews, GEO, technical SEO, content quality, page speed, structured data.
E-E-A-T + CITE quality audit for an EXISTING piece of content. Scores Experience, Expertise, Authoritativeness, Trustworthiness, and citation-readiness for AI search; surfaces veto items that block publication; produces a publish / publish-with-fixes / no-publish verdict. Distinct from `seo-content-brief` (produces a NEW article from a topic) and from `seo-page` (URL-level keyword/traffic intelligence). Use when the user asks "content quality audit", "E-E-A-T check", "is this content good", "review this article", "content audit", "citation readiness", or "AI search readiness".
Generate a writer-ready SEO content brief from a target domain and topic. Pulls domain overview, competitors, keyword gaps, SERP analysis, related and question keywords, AI Search citations, and existing internal-link sources, then synthesises a complete editorial brief a freelance writer can start from immediately. Use when the user asks for a content brief, blog brief, article outline, editor brief, or wants to capture organic traffic their competitors have.
Reviews serde serialization code for derive patterns, enum representations, custom implementations, and common serialization bugs. Use when reviewing Rust code that uses serde, serde_json, toml, or any serde-based serialization format. Covers attribute macros, field renaming, and format-specific pitfalls.
Call tRPC procedures directly from server code using t.createCallerFactory() and router.createCaller(context) for integration testing, internal server logic, and custom API endpoints. Catch TRPCError and extract HTTP status with getHTTPStatusCodeFromError(). Error handling via onError option.
Use when you have a rough product idea and want a complete PRD without sitting through an interactive grilling. Claude walks the full decision tree (edge cases, modules, schema, testing, security), self-answers with software-engineering best practices, streams the Q&A live so you can override, and writes the PRD locally with an option to push as a GitHub issue.
Run the standard post-change validation flow after a fix, refactor, or new feature. Use when implementation work is done and you should validate the latest changes by invoking the repo's review skills, starting with review-changes and then repo-doc-maintainer, before giving the final close-out.
Design simplified and reduced-complexity views of interfaces for users who need less visual noise and fewer options. Use when designing settings, dashboards, complex tools, or any interface that could benefit from a simpler mode. Triggers on: simplified view, simple mode, easy mode, basic view, reduce complexity, less clutter, overwhelmed, too many options, beginner mode, essential view, focus mode.
Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Gemini CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".
Specify algorithms for Model-Based Design: system specs, architecture specs, implementation plans, test plans. Use when creating specifications for controllers, signal processing, diagnostics, estimators, or other algorithms authored in Simulink, Stateflow, System Composer, or MATLAB Function blocks.
Use this skill when writing, reviewing, or refactoring Elixir, OTP, Ecto, or Phoenix/LiveView code. It corrects the staff-level judgment calls a capable model gets wrong by default — reaching for a GenServer as the universal tool, rescuing instead of letting processes crash, N+1 Ecto access, non-atomic writes, unbounded/linked Task fan-out, atom exhaustion from user input, eager Enum where Stream fits, and calling Repo from the web layer. Applies whenever the work touches process design, error handling, concurrency, data access, or LiveView, even if the user doesn't name them.
Provides investment advice based on Stanley Druckenmiller's investment philosophy and strategies. Drawing on the thinking of a legendary investor with a 30-year undefeated record and nearly 30% annual returns, it offers practical guidance on macroeconomic analysis, risk management, position building, and reading market cycles. Use when consulting on investment decisions, market analysis, risk management, or portfolio construction.
Check a TLA+ model of a system that moves between states, such as a product flow, a protocol, or a service, and draw it as a Mermaid statechart. The report gives the shortest path to each state that breaks a rule. Use for /statechart, or to show a bug as a path through states.
Advanced statistical modeling and hypothesis testing. Complementary to SciPy's stats module, it provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. Use for linear regression, GLM, time series analysis, ANOVA, survival analysis, causal inference, and statistical hypothesis testing. Load when working with OLS, WLS, logistic regression, Poisson regression, ARIMA, SARIMAX, statistical diagnostics, p-values, confidence intervals, or R-style statistical analysis.
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.