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Found 2,826 Skills
Strategic thought-leadership book collaborator for founders, experts, and operators turning voice notes, fragments, and positioning into structured first-person chapters.
Adapt an ML paper's writing, structure, positioning, and paragraph-level narrative to a target conference such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or similar venues. Use this skill whenever the user wants to submit, rewrite, polish, restructure, or tailor a paper for a specific conference; asks what good accepted/oral papers at a venue look like; wants reviewer-friendly writing; or wants section-by-section or paragraph-by-paragraph paper guidance. This is a writing and presentation skill, not an experiment-design skill.
Use this skill when building, debugging, or answering questions about Liveblocks. Liveblocks gives you the building blocks and infrastructure to enable people and AI to work together inside your app, powering realtime collaboration. Liveblocks features include collaboration, rooms, organizations, workspaces, comments, composer, threads, notifications, multiplayer, conflict resolution, realtime presence, avatar stacks, AI collaborators, AI agents, text editors, Tiptap, BlockNote, Lexical, React Flow, Chat SDK. Common components include AiChat, Thread, InboxNotification, Composer, Toolbar (for Lexical Tiptap), FloatingToolbar, FloatingComposer, FloatingThreads, AnchoredThreads. Common hooks include useThreads, useStorage, useMutation, useOthers, useInboxNotifications, useAiChats. Common issues are related to authentication (ID tokens vs access tokens), permissions, room limits, connection errors, user info.
Jungle Scout ASIN Sales Estimate Query: Returns daily estimated sales volume and the latest known price for a specified ASIN over a period on a daily basis, covering 10 marketplaces including the US, UK, Germany, Japan, etc. This skill is triggered when users mention terms such as ASIN sales estimate, ASIN daily sales, sales estimate, competitor sales monitoring, average daily sales, sales trend, product sales tracking, Jungle Scout sales data, sales estimates, daily sales, estimated units sold, ASIN sales tracking, competitor sales monitoring, product sales trend, daily unit sales. Even if users do not explicitly mention "Jungle Scout", this skill should be triggered as long as their needs involve viewing daily sales estimate data for a specific Amazon ASIN over a period of time.
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.
Controls a running iOS, iPad, or Apple Watch Simulator via the serve-sim CLI (npx serve-sim) and streams it into the host agent's preview pane. Use whenever the user wants an AI agent to view or drive an Apple Simulator — streaming to preview, taps at normalized coordinates, multi-touch gestures, hardware buttons, rotation, memory warnings, CoreAnimation debug, synthetic camera injection, media drag-drop, or managing app privacy permissions. Triggers include "serve-sim", "iOS simulator", "Apple simulator", "iPad simulator", "Apple Watch simulator", "stream the simulator", "show the simulator in preview", "view the simulator here", "open simulator in preview", "simulator gestures", "tap on the simulator", "rotate the simulator", "inject camera feed", "grant simulator permissions", "allow push notifications in the simulator", or any request to drive or display an Apple Simulator visually. Do NOT use for Android emulators, building/installing an iOS app (use xcodebuild), booting a simulator from scratch (use xcrun simctl boot), in-app React Native runtime debugging (use rn-debugger), or real iOS hardware.
Generate or drill flashcards for black-letter memorization — Leitner-style buckets, per-subject markdown storage, drill mode with self-assessment. Use when the user says "drill flashcards", "make flashcards from", "quiz me on cards", or wants to memorize rules.
Locate parking garages, lots, and street parking near your destination using Camino AI's location intelligence with AI-powered ranking.
Expert guide for writing efficient GLSL shaders (Vertex/Fragment) for web and game engines, covering syntax, uniforms, and common effects.
Spatial data gridding and interpolation with a machine-learning style API. Process geographic and Cartesian point data onto regular grids. Use when Claude needs to: (1) Grid scattered spatial data onto regular grids, (2) Interpolate point data using splines, linear, or cubic methods, (3) Process geographic coordinates with projections, (4) Reduce large datasets using block averaging, (5) Remove polynomial trends from spatial data, (6) Cross-validate gridding parameters, (7) Create processing pipelines with Chain, (8) Grid vector data like GPS velocities.
Guide identification, measurement, and management of operational risk in trading and brokerage operations. Use when designing trade error detection and correction procedures, investigating trade breaks and reconciliation failures, classifying loss events under Basel taxonomy, developing key risk indicators (KRIs) and dashboards, responding to system outages or data feed failures or order routing errors, conducting root cause analysis after a trade error or settlement fail, planning business continuity and disaster recovery for trading desks, preparing for FINRA or SEC operational risk examinations, or assessing technology risk in OMS and market data systems. Also covers fat-finger errors, error account P&L, and corrective action tracking.