ShuZhiyong

Complete feature development with structured options for merge, PR, or cleanup

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `use_figma` tool call. NEVER call `use_figma` directly without loading this skill first. Skipping it causes common, hard-to-debug failures. Trigger whenever the user wants to perform a write action or a unique read action that requires JavaScript execution in the Figma file context — e.g. create/edit/delete nodes, set up variables or tokens, build components and variants, modify auto-layout or fills, bind variables to properties, or inspect file structure programmatically.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill helps agents use Figma's use_figma MCP tool in the Slides context. Can be used alongside figma-use which has foundational context for using the use_figma tool.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detects and removes infostealer malware (credential stealers, data exfiltrators) via full-system file search, cryptographic hashing, and public threat-intelligence cross-checks (VirusTotal, MalwareBazaar). Primary method is always custom hash-based detection. Windows Defender (or any platform-native AV) is allowed **only when necessary** (e.g. inconclusive hashes or deep remediation) and **must never be the default option**. The agent must exhaust the custom workflow first. Works on Windows/macOS/Linux.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Scan a codebase for deepening opportunities, present them as a visual HTML report, then guide a user-directed decision loop for the selected candidate.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when the active client should create a new image, transform an existing image, or derive visual variants from references, and route through only the image tool or approved API actually exposed by that host.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate video, music, speech, or images with the operator's MiniMax Token Plan subscription through the codex-router media CLI. Use when the session runs a MiniMax custom (non-OpenAI) model (for example minimax-m3) with the MiniMax Token Plan provider connected, and the user explicitly asks to create a video, a song or music track, spoken audio, or an image. Do not use for reading or analyzing existing media.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Synchronize and verify code examples in documentation. Use when function signatures change, API interfaces update, imports shift, or documentation snippets become outdated and need correction.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Python research assistant with Context7 MCP. Use for Python library research, evaluating packages, enforcing strict Python coding standards, or fetching up-to-date library docs via Context7.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Force unrelated concepts together to discover emergent properties - "What if we treated X like Y?

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Scope the real change surface before editing. Use when planning a feature, bugfix, refactor, or review and you need a concrete map of likely touch points, dependencies, tests, and nearby risks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Templates and structural patterns for API docs, feature docs, config guides, and REST endpoint documentation. Use when structuring docs, applying Markdown templates, or standardizing doc formats.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

NVIDIA DeepStream SDK development guidance for Python pyservicemaker pipelines, video analytics, TensorRT integration, and streaming inference workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Control local apps through Computer Use (the @oai/sky runtime) inside the Codex app. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to control the computer, operate a desktop app's UI, use Safari or Chrome through computer use, click or type in an app, or take a screenshot of an app. Prefer purpose-built connectors, APIs, or CLIs when they exist.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create, list, read, message, wait on, fork, rename, archive, and pin Codex threads (sidebar tasks), plus automations and app navigation, using the app-native codex_app tools. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to create a thread or a new task or agent, list or read threads, send a message to a thread, wait for a thread, fork or rename a thread, archive or pin a thread, set up an automation or reminder, or open something in the Codex app.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Turn any codebase into a beautiful, interactive single-page HTML course that teaches how the code works to non-technical people. Use this skill whenever someone wants to create an interactive course, tutorial, or educational walkthrough from a codebase or project. Also trigger when users mention 'turn this into a course,' 'explain this codebase interactively,' 'teach this code,' 'interactive tutorial from code,' 'codebase walkthrough,' 'learn from this codebase,' or 'make a course from this project.' This skill produces a stunning, self-contained HTML file with scroll-based navigation, animated visualizations, embedded quizzes, and code-with-plain-English side-by-side translations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

two-stage review (spec compliance first, then code quality), refactoring, and quality improvement. Use when reviewing code, eliminating code smells, reducing technical debt, refactoring methods, running self-critique loops, or improving maintainability and readability.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Choose and compare cloud design patterns for distributed systems. Use when reviewing architecture, selecting workload patterns, or mapping reliability, performance, messaging, security, and migration concerns to concrete design options.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design philosophy docs and canvas-based visual creation. Use when articulating design principles, crafting multi-page design documents, or exploring aesthetic philosophy with intentional design thinking.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Interactive idea refinement using Socratic method to develop fully-formed designs

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.