Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
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(NS) Generate E2E test task markdown for Cypress/TypeScript during SDD planning after frontend tasks exist. Use when planning Cypress coverage per feature — not for writing specs (use create-e2e-tests). Requires data-testid contract from frontend task. Device-aware desktop/tablet/mobile structure.
Perform RFM (Recency, Frequency, Monetary) customer segmentation from transaction data. Use this skill when the user needs to segment customers by purchase behavior, identify high-value buyers, design retention campaigns, or prioritize marketing spend by customer value — even if they say 'who are our best customers', 'which customers are at risk of churning', or 'how do we target our marketing'.
E-commerce image set generation assistant. Triggered when the user explicitly asks to generate e-commerce image sets, product hero images, selling-point images, scene images, model images or similar image content. Supports the size specifications of domestic platforms (Taobao, JD, Pinduoduo, Douyin) and international cross-border platforms (Amazon, standalone sites). Trigger examples: "帮我生成这件T恤的电商套图", "做一套淘宝主图", "生成亚马逊listing图片". Should not be triggered when the user merely uploads an image without an explicit image generation request.
Apply supply and demand analysis to explain price determination, market equilibrium, and the effects of policy interventions. Use this skill when the user needs to analyze how prices are set in a market, predict the effect of taxes/subsidies/price controls, or understand shifts in supply or demand curves — even if they say 'why did the price go up', 'what happens if the government sets a price cap', or 'how does a tariff affect the market'.
Edit one or more existing Phat prototype pages by prototype revision ID while preserving unrelated pages and confirmed requirements. Use when the user references an ID such as home-v1 or booking-v2 and wants targeted visual, layout, content, state, navigation, or interaction changes before specification.
Design, refactor, and review Effector state management using modern v23+ patterns. Use when tasks involve createStore/createEvent/createEffect modeling, dataflow with sample/attach/split, scope-safe SSR with fork/allSettled/serialize/hydrate, React integration with useUnit, Solid/Vue integration patterns, fixing scope loss, or replacing anti-patterns such as business logic in watch, imperative calls in effects, and direct getState business reads.
Use when the user wants to analyze EKS application logs during or after a FIS experiment. Triggers on "analyze app logs", "application log analysis", "check application behavior", "分析应用日志", "查看应用表现", "应用日志分析". Supports two modes: real-time monitoring (during experiment) and post-hoc analysis (after experiment). Reads experiment context from aws-fis-experiment-prepare/execute outputs.
Guide to building conversational AI voice agents on the ElevenLabs Agents Platform (ASR, LLM, TTS, turn-taking model). Covers agent configuration and system prompts, workflows, multi-voice, pronunciation dictionaries and speed control, knowledge base RAG, client/server/MCP/system tools, Scribe real-time STT, WebRTC and WebSocket connections, testing and evaluation, analytics, cost optimization, GDPR/HIPAA/SOC 2 compliance, and agents-as-code CLI workflows. Includes production templates for @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, Next.js, Swift and Cloudflare Workers, plus 17+ documented fixes: deprecated @11labs packages, Android audio cutoff, CSP violations, missing dynamic variables, case-sensitive tool names, webhook authentication failures and WebRTC misconfiguration. Use when building, configuring or debugging an ElevenLabs voice agent.
Operate the Poseidon deployment platform via the poseidon command. Use this package when the user asks for Poseidon operations such as project queries, app creation, app queries, config creation, config queries, building configs associated with apps, app deployment, or app log queries. metadata(search-git,page-apps,page-apps-simple,list-project-entries,list-project-envs,list-project-products,list-app-types,list-app-types-simple,list-build-tools,list-build-tools-simple,list-base-images,list-base-images-simple,get-app,create-app,list-configs,list-configs-simple,create-config,update-config,delete-config),build(trigger,page-builds,page-builds-simple,list-build-params,build-overview,get-log),ops(deploy-app,search-logs,log-context,restart-app),atomic(rebuild-and-deploy,runtime-errors).
Operate Qingtui lightweight apps via the qingtui command. Use this package when the user asks to operate Qingtui or its lightweight apps; it supports user queries, user resolution, openid resolution, and text sending operations. list-users, resolve-users, send-text.
TRIGGER THIS when creating or updating employee handbooks, documenting HR policies, developing code of conduct, building benefits guides, or creating leave/PTO policies. Creates comprehensive, legally compliant, accessible employee handbooks covering company policies, culture, benefits, code of conduct, and all required disclosures.
External SSL VPN / remote-access appliance attack matrix — Cisco ASA/AnyConnect, Fortinet FortiGate/FortiOS, Citrix NetScaler/ADC, Palo Alto GlobalProtect, Pulse Secure / Ivanti Connect Secure, SonicWall, F5 Big-IP. Covers version fingerprinting, CVE matrix (2018-2026), AAA backend identification, default credentials, configuration-disclosure paths, pre-auth RCE/SSRF/path-traversal exploits where applicable. Built from authorized-engagement Cisco ASA testing plus 2024-2026 enterprise VPN CVE landscape. Use whenever the target's perimeter exposes any SSL VPN appliance or remote-access gateway — these are the most common initial-access points in 2024-2026 actor TTPs.
Route contract issues to the right approver using the escalation matrix in the review playbook, and draft the escalation note. Use when the user says "who needs to approve this", "escalate this", "does this need the legal lead's sign-off", "route this for approval", or when another skill finds an issue beyond the reviewer's authority.
Covers the EvolutionaryScale/Biohub `esm` Python SDK: ESM3 generative protein design (sequence, structure and function tracks, chain-of-thought), ESMC embeddings, inverse folding, ESMFold2 structure prediction, and hosted Forge/Biohub inference with ESM_API_KEY. Use when generating or completing proteins with ESM3, extracting ESMC embeddings for classification or similarity, folding a sequence or designing sequences from a structure, or choosing between esm3-open, esmc_300m and Forge-hosted models. Use when batching async Forge or Biohub API calls. Not for other protein models such as AlphaFold or generic Hugging Face transformers usage.
Analyze, manipulate, compare, annotate, and visualize phylogenetic or other hierarchical trees with ETE 4. Use for Newick/Nexus tree I/O, topology edits and pattern matching, Robinson-Foulds comparisons, gene-tree evolutionary events and reconciliation, NCBI/GTDB taxonomy, SmartView exploration, and publication rendering. Do not use it to infer trees from raw sequences; align sequences and infer a tree first.
Create editable Excalidraw diagrams in Obsidian, standard or animated formats. This skill MUST be used when the user names Excalidraw. It SHOULD be selected from natural-language requests for standalone diagrams, concept relationships, mind maps, editable whiteboards or diagrams whose elements appear in sequence (draw, flowchart, mind map, relationships, whiteboard, step-by-step presentation), without requiring the user to know the skill name. Choose by content and destination; illustration or photo requests need other tools. For diagrams inside HTML Artifacts, MUST prefer HTML/CSS/SVG or the artifact's existing diagram tools; use Excalidraw there only when explicitly requested or a concrete Excalidraw capability is needed. Hand-drawn styling alone is insufficient. Explicit Mermaid requests MUST use mermaid-visualizer instead.
Perform comprehensive, deep analysis of a system and its subsystems to identify bugs, race conditions, stale documentation, dead code, and correctness issues. Use when asked to "audit this system", "exhaustive analysis of X", "analyze for correctness", "root out issues in...", "deep dive into...", "verify this code is correct", "find bugs in...", or when reviewing agent-written code for production readiness. Automatically decomposes systems into subsystems, applies appropriate analysis checklists, and produces structured findings with severity classification.
Daniel Kahneman's behavioral economics and cognitive bias framework. Load with expert-engine for decision quality audits, bias detection, planning calibration, and debiasing strategies. Covers System 1/2, WYSIATI, Prospect Theory, and major heuristics.
Assemble a panel of experts to assess a problem from multiple professional perspectives, surface agreement and disagreement, and deliver a chaired recommendation with clear tradeoffs. Use when the user wants multi-expert judgment, a second opinion, design critique, option comparison, or a recommendation backed by distinct expert viewpoints.
Use when the user wants an autonomous ML research loop that explores the space broadly rather than hill-climbing one approach. A temperature scheduler replaces the usual hypothesis step: it forces several wild, diverse swings (full rewrites, different architectures/regimes) early, then enters an adaptive phase that picks swing / merge / exploit per iteration — with a hard stagnation guard that bans further small-step exploits once they run too long, forcing a pivot back to a swing or merge. Tracks an approaches.md registry and a move_type per iteration; analyses every run before the next move. One change per iteration; loops forever until interrupted. Not for the standard analysis-first ml-autoresearch (which lets analysis alone choose each change), one-off training runs, or sweeps.
Runs Fastly Compute WASM binaries locally and serves as the authoritative reference for Compute platform internals. The fastlike source code is highly readable and covers the host ABI, caching and purging APIs, KV/config/secret store interfaces, rate limiting with counters and penalty boxes, ACL lookups, the full request lifecycle, backend fetch semantics, and a built-in per-request profiler with hostcall spans, backend waterfalls, native CPU samples, and optional deep metrics (body bytes, cache outcomes, header summaries, wasm heap curve). Use when working with Compute runtime internals or host calls, understanding how edge data stores behave at runtime, profiling local Compute apps, or testing WASM binaries locally. Prefer this skill over Viceroy for any non-Rust Compute work — its source code is easier to understand as a Fastly Compute API reference.
Builds MCP (Model Context Protocol) servers in Python with FastMCP, covering tool, resource, and prompt definitions, storage backends (memory, disk, Redis, DynamoDB), server lifespans, the 8 built-in middleware types, server composition via import and mount, OAuth Proxy and authentication, OpenAPI integration, client configuration, and FastMCP Cloud deployment. Includes templates for basic servers, storage, middleware, composition, OAuth proxy, API integrations, testing, and production architectures, and prevents 25+ common errors such as storage misconfiguration, lifespan and middleware-order mistakes, circular imports, module-level server issues, async/await confusion, OAuth security holes, and cloud deployment failures. Use when creating or debugging a Python FastMCP server, defining mcp tools, resources, or prompts, wiring fastmcp storage or middleware, mounting sub-servers, setting up MCP OAuth, or deploying to FastMCP Cloud.
Helps beginners find their first AGENTIC project through pain point identification. Guides through questioning, analysis, project suggestion, and folder setup. Use when someone asks 'what project should I build?' or 'help me get started with Claude Code'.
Stock prices, gold, silver, crypto, macro indicators, bank rates, price charts, and company financials (income statement, balance sheet, cash flow, ratios). Use when user asks about stock prices, gold/silver prices, interest rates, macro data, price history charts, or company financial statements.
Control the user's Firefox from a terminal. Use when your task needs the user's browser or authenticated session, page navigation, tab/window control, screenshots, DOM reads, waits, or page interactions in Firefox. Do not use it as a web search replacement.
Analyze and optimize FiveM and RedM resources for client/server resmon, Lua/native CPU, Wait(0) loops, hitch warnings, TriggerServerEvent / TriggerClientEvent / TriggerLatent* spam, payload size, broadcasts (-1), state bags, first-GET cache, MySQL load-at-start, neteventlog, profiler, and bandwidth. Use when reviewing, refactoring, debugging, or optimizing FiveM/RedM Lua performance or network traffic. Use when the user runs /fivem-redm-performance-network or $fivem-redm-performance-network.
Audit and fix HTML metadata including page titles, meta descriptions, canonical URLs, Open Graph tags, Twitter cards, favicons, JSON-LD structured data, and robots directives. Use when adding SEO metadata, fixing social share previews, reviewing Open Graph tags, setting up canonical URLs, or shipping new pages that need correct meta tags.
Archive or delete a stale GrowthBook feature flag, walking the user through inlining the flag's effective value at call sites in the codebase before removal. Use when the user says "delete this flag", "remove this stale flag", "clean up flag X", "archive this flag", "we don't need this flag anymore", or "get rid of this flag and its experiment-ref rule". For finding stale flags first, use flag-search. For editing rules instead of removing the flag, use flag-targeting. For stopping an experiment that uses the flag, use experiment-stop.
Set up a monitored progressive rollout ("safe rollout") for a GrowthBook feature flag — combining a ramp schedule with guardrail metric monitoring, automated signals, and optional auto-rollback. Use when the user says "roll this out safely", "monitor the rollout with guardrail metrics", "set up a safe rollout", "I want to ramp this with automatic rollback if metrics regress", "configure monitoring on the ramp", "check the monitoring status of this rollout", "approve the next monitored step", or "roll back because guardrails are failing". For unmonitored ramps (just progressive coverage, no metrics), use flag-ramp directly. For simple on/off time windows, use flag-schedule.
Add, remove, or inspect feature-level prerequisites on a GrowthBook feature flag. Use when the user says "gate flag X on flag Y being enabled", "add a prerequisite", "flag X should only evaluate if flag Y is on", "remove the prerequisite on flag X", "what does this flag depend on", or "this flag should require the new-checkout flag to be true first". Feature-level prerequisites gate the entire flag — when the prerequisite flag is off, this flag returns its default value for every user. The prerequisite must be a boolean flag. For prerequisites scoped to a single rule (not the whole flag), use flag-targeting. For tracing the full dependency graph, use flag-graph.
Generate or train flashcards for legal provisions — Leitner-style memory buckets, stored as Markdown per subject, with a self-assessment training mode. Use when the user says "train flashcards", "make flashcards from [material]", "quiz me on the cards", or wants to memorize legal provisions.
Read, inspect, and write Flow Cytometry Standard (FCS) 2.0, 3.0, and 3.1 files with FlowIO. Use for low-level FCS metadata and channel inspection, NumPy event extraction, multi-dataset files, table export, and FCS 3.1 creation; use FlowKit for compensation, cytometry transforms, gating, or FlowJo workspaces.
Retrieve ClinGen gene-disease validity assertions for a public gene or disease, and review source-linked public evidence and literature for one supported GRCh38 germline nuclear SNV or simple indel through Folklore Clinical Variant Interpretation MCP. Use when a scientific agent must branch deterministically on resolved, ambiguous, not-found, invalid, unsupported, or unavailable variant outcomes; chain a resolved public variant into related literature or publication details; or preserve evidence provenance without accepting patient, phenotype, family, segregation, or private case data.
Analyzes food science topics including nutritional composition, food chemistry, food safety hazard analysis, sensory evaluation design, and food processing optimization; trigger when users discuss nutrients, food additives, HACCP, shelf life, or food product development.
Fortytwo Prime: collective multi-agent inference for high-stakes questions. ALWAYS use when the user says "Ask Fortytwo", "Ask Prime", "Ask Fortytwo Prime", or calls ask_fortytwo_prime. When the user doubts your answer ("try again", "that's wrong", "are you sure?"), wants more depth ("go deeper", "elaborate", "full picture"), or asks a question spanning multiple domains where a single model may fall short — suggest Fortytwo Prime but wait for confirmation before calling (this is a paid service). Even if the user doesn't mention Fortytwo by name, suggest it for contested topics, niche expertise, and high-stakes decisions.
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.