practice
無料Guide a programming exercise using dsh-tui or a topic the user wants to learn. Use for practice and coaching requests, rather than requests to deliver a product change.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Guide a programming exercise using dsh-tui or a topic the user wants to learn. Use for practice and coaching requests, rather than requests to deliver a product change.
日本語の概要は準備中です。原文の説明を表示しています。
Make game-ready 2D characters, creatures, props, icons and FX as master stills, sprite sheets or animation clips. Plan size, motion and finish; generate the art (image generation is the default, through generate2dmedia route_media.py - the API when a key is configured, else the local Codex or Grok CLI); approve one master still per character; then key, slice, register, scale, palette, QA and export frames for a game engine (Aseprite JSON, Godot SpriteFrames or Sprite3D). HD finish by default, pixel finish on request. Character animation is one image-to-video clip per action from the master (video2dsprite); sheets are for FX, icons and props. Use for sprites, masters, sheets, frame-by-frame animation and packaging frames from any source. Not for maps, tiles or backgrounds (generate2dmap), video clips (video2dsprite), code-drawn art (codeart2d, only on request) or calling an image or video API by itself (generate2dmedia).
日本語の概要は準備中です。原文の説明を表示しています。
Plan and build 2D game maps and scenes - top-down and side-scrolling levels, tilemaps, prop packs, parallax backgrounds and HD-2D battle or story plates - with collision, navigation and reachability checks, environment motion, a playable HTML preview and export to Tiled, Godot 4 or LDtk. Map art (terrain, tiles, props, plates, parallax layers) is image generation by default, through generate2dmedia route_media.py (the API when a key is configured, else the local Codex or Grok CLI); map data (layout, collision, exits, spawns) is written as data. Use for any map, level, room, scene, background, terrain or prop-kit request. Not for characters, creatures, items or FX (generate2dsprite), character animation (video2dsprite), code-drawn tiles or maps (codeart2d, only on request) or calling an image or video API by itself (generate2dmedia).
日本語の概要は準備中です。原文の説明を表示しています。
Turn one approved master still into a character's whole animated sprite set - one image-to-video clip per action (idle, walk, run, attack, jump, hurt, cast and so on), all from that still, generated through generate2dmedia route_media.py (the xAI API when a key is configured, else the local Grok CLI) - then gate each take, key it with a soft matte, register it to the master, pick loops or retime actions, finish (HD by default, pixel on request) and package fixed-canvas frames, alpha WebM, packed MP4 for iPhone and a PNG fallback with engine metadata and a JS runtime. Also processes a supplied clip. Use for character and creature animation, fluid motion and any video-to-sprite work. Not for FX, icon or prop sheets (generate2dsprite), maps or plate loops (generate2dmap), code-drawn animation (codeart2d, only on request) or calling a video API by itself (generate2dmedia).
日本語の概要は準備中です。原文の説明を表示しています。
Delete one or more `.cs` script files from disk, refresh the AssetDatabase, and wait for Unity compilation to settle before delivering the final result via the request's `requestId`. Pair with 'script-read' to inspect files before deletion.
日本語の概要は準備中です。原文の説明を表示しています。
Install a Unity package from the registry, a Git URL, or a local path. Modifies `manifest.json` and triggers package resolution; may also trigger a domain reload — the final result is delivered after the reload via the request's `requestId`. Use 'package-search' / 'package-list' for discovery first.
日本語の概要は準備中です。原文の説明を表示しています。
Uninstall a UPM package from the Unity project. Modifies `manifest.json` and may trigger a domain reload — the final result is delivered after the reload via the request's `requestId`. Built-in packages and packages that are dependencies of others cannot be removed. Use 'package-list' to list installed packages first.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-AI research using available external providers (Double Diamond Discover phase) - Questions about best practices, patterns, or ecosystem research PRIORITY TRIGGERS (always invoke): "octo research", "octo discover", "co-research", "co-discover" DO NOT use for: simple file searches (use Read/Grep), questions Claude can answer directly, debugging issues (use skill-debug), or "what are my options" for decision support.
日本語の概要は準備中です。原文の説明を表示しています。
Queue open microsoft/apm pull requests (community fixes, PRs without an issue, or PRs that close an issue) and fan them out through an isolated pool (default 2) of autopilot-pr-triage-worker sessions. Advisory only. Never merges, never assigns, never requests reviewers, never runs autopilot-pr-review-worker. Activate on a mixed PR list or queue-open when the job is PR triage. Works in a local session, Copilot App automation, Cloud Agent, Remote Agent, or Agentic Workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Research an explicitly requested Marin question or coordinate a multi-session experiment; find prior work, assess evidence, and record results in the task's existing durable surface.
日本語の概要は準備中です。原文の説明を表示しています。
Explain NotFair's paid-ads skills, installation, platform boundaries, account connections, and current product capabilities. Use for questions about how NotFair works, what it supports, how to install or connect it, plans or limits, or paid-media troubleshooting that is not an account-performance request.
日本語の概要は準備中です。原文の説明を表示しています。
Coordinate safe, evidence-based paid-media work across Google Ads, Meta Ads, X Ads, LinkedIn Ads, Reddit Ads, TikTok Ads, Amazon, and ChatGPT Ads. Use for broad ads questions, multi-channel strategy, budgets, CPA or ROAS, campaign requests, spend, ad performance, or when routing to the right NotFair paid-ads skill.
日本語の概要は準備中です。原文の説明を表示しています。
Prepare and request a code review after implementation or before merge by assembling scope, requirements, git range, and reviewer instructions.
日本語の概要は準備中です。原文の説明を表示しています。
Direct-invocation specialist for clear, self-contained HTML plans that preserve source material while improving hierarchy, sequence, ownership, dependencies, and reviewability. Use when the user explicitly invokes html-plan or the broad html skill routes a plan request here. Do not activate independently from a general request.
日本語の概要は準備中です。原文の説明を表示しています。
Direct-invocation specialist for self-contained HTML diagrams whose layout, notation, and interaction clarify relationships, sequence, topology, state, hierarchy, or quantitative structure. Use when the user explicitly invokes html-diagram or the broad html skill routes a diagram request here. Do not activate independently from a general request.
日本語の概要は準備中です。原文の説明を表示しています。
Create or redesign self-contained single-file HTML artifacts with a visual direction shaped by the user's brief, project, and subject. Use when HTML is the deliverable for a report, explainer, landing page, presentation, tool, mixed artifact, or broad request. This is the collection's only implicit router. Route clear wireframe, prototype, mockup, plan, or diagram requests to the matching direct-invocation specialist when available. Do not use for ordinary application implementation when a standalone HTML file is not the deliverable.
日本語の概要は準備中です。原文の説明を表示しています。
Direct-invocation specialist for polished, responsive, self-contained HTML mockups and interactive prototypes grounded in the user's conversation, product context, and design language. Use when the user explicitly invokes html-prototype or the broad html skill routes a mockup or prototype request here. Do not activate independently from a general request. Treat a mockup as a noninteractive fidelity mode within this skill, not as a separate skill.
日本語の概要は準備中です。原文の説明を表示しています。
Direct-invocation specialist for low-fidelity, self-contained HTML wireframes that test information hierarchy, content, navigation, task flow, and responsive structure before visual design. Use when the user explicitly invokes html-wireframe or the broad html skill routes a wireframe request here. Do not activate independently from a general request. Do not use for polished mockups or production-like interaction; use html-prototype for those.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user explicitly requests research with Baizhi Agent Toolkit. Discover the connected MCP tools and their current schemas, agree a request budget, and produce a sourced result without exposing credentials.
日本語の概要は準備中です。原文の説明を表示しています。
Use when work in this repo depends on a change in a different repo that has its own running Claude session (frontend needing a backend endpoint, backend needing a client change, a shared package bump). Covers finding the peer session, what to put in the request so it needs no follow-ups, and how to handle the reply.
日本語の概要は準備中です。原文の説明を表示しています。
Discover current MuAPI image models and run one explicitly confirmed asynchronous image generation request with bounded polling. Use when an agent needs hosted image generation without hard-coding stale model endpoints or request IDs.
日本語の概要は準備中です。原文の説明を表示しています。
Fetch a real product's current price, stock, rating, or images from retailer pages over the Apify MCP server, and return them as typed fields rather than prose. Use when someone asks what a product costs right now, whether it is in stock, how it is rated, to compare a product across retailers, or to check a product URL they pasted. Also use when an agent would otherwise answer a product question from training data. Not for managing your own store's catalog, not for payments, and not for questions answerable without live retailer data.
日本語の概要は準備中です。原文の説明を表示しています。
Validate, prepare, or run public CodonFM Encodon masked-codon variant scoring and review compatibility of its scoring workflows. Use only when the user explicitly requests CodonFM or Encodon, or that context is already established in the conversation. Do not select this skill for a generic variant-scoring request without that context; ask for the variant and intended analysis first.
日本語の概要は準備中です。原文の説明を表示しています。
Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
日本語の概要は準備中です。原文の説明を表示しています。