'consumer' 검색 결과

Maintain Remotion’s expert listings, portraits, and generated cards, then regenerate the homepage animation with transparency. The workflow covers separate Chrome and Safari video formats and checks that matching assets stay consistent across both homepage consumers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add or edit an expert listing
• Update portraits and regenerate expert cards
• Regenerate transparent homepage animations

Classify Remotion Studio settings as fixed at startup or reloadable, then wire every component that uses them consistently. Guide implementation and review of configuration reloads, default resets, CLI precedence, and render queue settings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add a Studio config setter or CLI option
• Review inconsistent setting updates across Studio components
• Keep preview and render queue settings aligned

Build command-line interfaces for graphical applications in Cursor using the CLI-Anything workflow. It supports creating and extending these interfaces, running tests, checking required criteria, and listing tools through slash commands or natural-language requests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a command-line interface for a graphical application
• Extend an existing CLI to cover more operations
• Run tests and validate a CLI implementation

Understand customer decisions and turn psychological principles into practical marketing ideas. The skill explains relevant thinking tools and behavioral patterns, then suggests ethical applications for pricing, trust, messaging, onboarding, retention, and deciding which marketing problems to address first.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Exploring why customers hesitate to purchase
• Reviewing how prices and plans are presented
• Building trust through testimonials and evidence

Investigate Cherry Studio code to identify unused behavior, duplicated state, and unnecessary abstractions. Turn a few well-supported findings into cleanup proposals that document current consumers, removal scope, risks, and observable acceptance criteria.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding unused code and unnecessary internal APIs
• Reviewing duplicated stores, caches, and events
• Assessing library replacements that reduce maintenance

Design and review API contract tests, which check agreed request and response behavior. Examine schemas, server output, and client parsing to identify compatibility problems, reproduce failures locally, and report gaps in test coverage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking client impact before changing an API response
• Investigating client and server disagreements at runtime
• Reproducing compatibility failures with local test data

Trace software artifacts from source and dependencies through builds, publishing, and runtime use in CTF sandboxes. Compare intended versions with shipped files to identify the earliest divergence and document the evidence linking each stage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing declared, resolved, and shipped dependency versions
• Tracing package or build tampering through CI/CD
• Identifying the artifact actually used at runtime

Investigate AI-agent and cloud infrastructure challenges in a CTF sandbox. Trace untrusted content into tool actions, compare deployment configuration with runtime behavior, and follow software artifacts from source through build and release to their actual consumers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Tracing untrusted content into agent tool actions
• Comparing deployment configuration with live behavior
• Following dependencies and artifacts through CI/CD

Choose and track startup metrics suited to the business model and funding stage. Calculate customer acquisition cost, customer lifetime value, retention, and cash usage, then organize trends and targets for operational reviews and investor reporting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose core metrics for a startup's stage and business model
• Calculate customer acquisition cost and lifetime value
• Review retention, growth efficiency, and cash usage

Develop and debug CopilotKit Inspector interfaces in a dedicated local workbench. It guides baseline screenshots, visual checks after each change, and additional narrow-screen or theme checks when layout or contrast is involved.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Fixing Inspector panes and overlay controls
• Checking narrow-screen layouts and the collapsed rail
• Comparing light and dark theme appearance

Retrieve stock prices, futures quotes, exchange rates, and economic indicators with the free Python library AKShare. The skill explains market-specific functions, symbol formats, and data preparation for analysis and testing strategies against historical data.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Retrieve historical prices for Chinese, US, and Hong Kong stocks
• Collect Chinese GDP and consumer price data
• Check futures quotes and foreign exchange rates

Package an existing custom diffusers block into a directory ready for Hub upload. Select a class from a Python file and save its source, configuration, and associated files so others can load the block.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a custom block for Hub distribution
• Selecting one block class from a Python file
• Creating the directory layout needed to load a shared block

Apply psychology and behavioral science to marketing decisions. The skill selects relevant thinking models, explains customer behavior, and suggests ethical changes to pricing, messaging, purchase journeys, and campaign priorities.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understand why customers hesitate to buy
• Review pricing plans and how prices are presented
• Simplify signup and purchase journeys

Convert LLMs to GGUF and reduce model size through quantization, which stores weights at lower numerical precision. Prepare models for CPU or Apple Silicon inference, compare compression levels, and integrate them with local AI tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing an LLM for CPU-only use
• Running a local model on Apple Silicon
• Comparing model size and quality across quantization levels

Run language models locally with llama.cpp on CPUs, Apple Silicon, or AMD and Intel GPUs. The skill guides model setup, memory-saving GGUF format choices, interactive chat, and serving models through an OpenAI-compatible API.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Running a language model on a CPU-only computer
• Setting up local chat on an Apple Silicon Mac
• Choosing model quantization to fit available memory

Make your local gbrain accessible to other devices and cloud agents through MCP, a connection interface for AI tools. Set up Tailscale access, assign limited permissions to each client, configure authentication, and verify connections.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Accessing gbrain from another laptop or phone
• Connecting cloud agents to your local gbrain
• Giving each client limited access permissions

Guide server-side Zoom integrations using Zoom Rivet SDK in JavaScript or TypeScript. Consult patterns for authentication, incoming event notifications, typed API calls, multiple modules, and webhook processing on AWS Lambda.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing Zoom authentication and token handling
• Building a Team Chat bot with API integration
• Combining multiple Zoom modules in one server

Build and update Mastra application interfaces using existing components from @mastra/playground-ui. Follow shared visual styles, arrange layouts with Tailwind utilities, and connect themes and stylesheets while avoiding duplicated components or unsupported appearance overrides.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building a new Mastra application screen
• Adjusting layouts with existing components
• Connecting shared themes and stylesheets

Apply behavioral science to marketing pages, pricing, ads, and customer journeys. Use a catalog of over 70 mental models to diagnose barriers to action and develop concrete recommendations suited to the audience and goal.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Diagnosing why a landing page gets few sign-ups
• Reviewing pricing tiers and discount presentation
• Improving email and ad messaging

Verify a local OpenSEO MCP server, which exposes tools to AI agents, through real DataForSEO calls and a headless Claude trial. Check protocol correctness alongside tool discovery, input rules, response size, errors, and asynchronous task recovery.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking an MCP tool after adding or changing it
• Testing whether an agent can choose tools from their descriptions
• Verifying queued tasks and recovery using taskId

Trace application behavior and explain data structures using compact text tree diagrams. The diagrams connect user actions to real functions, data types, state changes, and the components that render again as a result.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Tracing what happens after a user action
• Investigating why a component renders again
• Mapping data structures and their consumers

Collect and update 68 US economic and social indicators, then summarize trends over ten, five, two, and one years. Produce a report covering relationships between indicators, unusual patterns, and topics that warrant further research.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Refreshing US economic and social indicators
• Comparing short- and long-term economic trends
• Examining relationships across prices, jobs, and housing

Guides you through running large language models on CPUs, Apple Silicon, and AMD or Intel GPUs. Covers choosing GGUF model files, reducing memory through quantization, and starting an OpenAI-compatible chat server.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Running a local LLM on an Apple Silicon Mac
• Trying LLM inference on a CPU-only machine
• Choosing a model format that fits available memory

Convert language models to GGUF and reduce their size through quantization, which stores model weights at lower precision. Guides cover compression choices, local inference on CPUs and Apple Silicon, and integration with tools such as Ollama.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Running a language model on a CPU-only computer
• Choosing model compression for available memory
• Configuring Metal acceleration on Apple Silicon