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概要と使いどころ
Provider-independent asset continuity and version management for generated-media production. Use when an agent must track generated or reference assets, prompts, seeds, model/tool versions, manifests, approvals, edit decisions, derivatives, localization variants, metadata/provenance, and continuity QA across image, video, audio, avatar, product-ad, social, explainer, or film-style pipelines.
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Provider-independent performance direction for generated video, avatar/spokesperson clips, animation, ads, film scenes, social content, and voice-led media. Use when an agent must cast or direct synthetic performers, avatars, animated characters, talking heads, AI video characters, or voice performances; plan acting beats, objective/obstacle/action, blocking, gesture, eye-line, facial expression, body language, lip-sync, voice alignment, rehearsal prompts, iteration, continuity, consent, and performance QA.
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 this skill to turn generated, captured, scanned, or modeled 3D output into production-ready standalone assets for DCC, real-time engine, web, or interchange delivery. It covers requirements, topology repair, scale and axes, UVs, PBR baking, LODs, static and skeletal readiness, rig handoff, optimization, glTF/USD/FBX delivery, validation, QA, and rights/provenance. Do not use it for provider-specific generation prompts, full scene/world building, mocap operation, or exact CAD/manufacturing work.
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 this skill to plan, direct, finish, and QA provider-independent mono or stereo 180-degree, 360-degree, spherical, spatial, wide-FOV, and immersive video. It covers format choice, capture rigs, stitching, nadir and seam management, stereoscopic comfort, attention direction, stabilization, ambisonic and spatial audio, titles, captions, accessibility, edit, color, VFX, projection metadata, Vision Pro, YouTube, headset delivery, device QA, and privacy, location, and likeness rights. Do not use it for interactive XR apps, volumetric/world-model generation, game-engine experiences, or provider-specific video generation prompts.
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。
Provider-independent character design and continuity direction for generated media. Use when an agent must create, preserve, revise, or QA a recurring character across AI-generated images, video clips, avatars, animation, comics, ads, product mascots, serialized social posts, or multi-shot campaigns; especially when building character bibles, reference packs, prompts, expression/pose ranges, costume/hair/makeup/prop continuity, identity and likeness safeguards, iteration plans, handoff notes, or continuity reviews.
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。
Embedded hardware debugging workflow for probe-rs targets using embedded-debugger-mcp. Use when Codex or Claude Code needs to inspect debug probes, validate embedded debugger setup, start the MCP server, guide a user through ARM Cortex-M/RISC-V flashing/debugging/RTT workflows, or operate without installing an MCP client by using the CLI plus prompts.
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。
Generate free images with Agnes Image 2.1 Flash through the Agnes API, including text-to-image, image-to-image, high-density visual prompts, URL results, and local downloads. Use when the user asks for 免费图片, 免费的图片模型, free image API, Agnes image, Agnes Image 2.1 Flash, free AI image generation, image-to-image via Agnes, or wants a free image model Agent 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。
Draft and explain persistent goal-loop prompts for long-running agent work with clear stop conditions.
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 for creating, reviewing, or debugging GitHub Copilot reusable prompt files and slash commands in Visual Studio Code, including .github/prompts/*.prompt.md, inputs, context links, agent selection, and tool selection. Do not use for always-on rules, multi-step Agent Skills, custom personas, or VS Code extension commands.
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 implementing or debugging Formax permissions/policy/approval behavior and UI (allow/ask/deny rules, workspace boundaries, approval prompts, and /permissions overlay parity with Claude Code).
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。
影视概念美术专家 & 视觉导演技能——从剧本/故事/世界观文字中提取并设计 AI 视频所需的标准化视觉资产提示词。当用户要求"从剧本提取角色/场景/道具/载具提示词"、"生成角色定妆照 prompt"、"生成场景空镜 prompt"、"生成道具/载具/机械资产设定图 prompt"、"为 AI 视频做视觉资产设计"、"拆解剧本出图清单"时使用本技能。产出角色定妆（全身/半身）、场景空镜、道具/载具/机械资产设定图四类提示词，中英双语，含影调定调与色彩科学方案。
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 wants to design, rewrite, refine, or vary emotional acting prompts for live-action AI video characters. Translate abstract emotions, dialogue, subtext, and scene context into concise, observable, temporally ordered micro-performance directions. Preserve the user's existing character, scene, camera, and dialogue requirements unless they explicitly ask to change them. Do not use for general story writing, shot design, action choreography, or visual asset design when emotional performance is not the main task.
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 reviewing, auditing, scoring, or improving a real or synthetic MATLAB AI tutor transcript, tutoring prompt, generated lesson, exercise, feedback sequence, or skill behavior for MATLAB accuracy, active learning, assignment guardrails, feedback quality, debugging support, transfer prompts, and instructor-facing quality recommendations.
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。
Craft verifiable, tight goal prompts for AI coding agents (Claude Code /goal, Codex Automations, Pi), either from a standalone task interview or from an already-approved to-goal handoff. Use when the user says "给我一个 goal 提示词", "帮我写个 goal", "设置一个自动化任务", "我想让 agent 自动做 X", or asks to turn a task into a self-running loop. Ensures every goal has a checkable completion criterion so the agent knows when it's done.
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。
Generate visual prototype prompts from SCR- entries for Google Stitch (or equivalent UI generation tool). Triggers on: 'make a prototype', 'visualize screens', 'generate Stitch prompt', 'I need a visual demo', 'prototype the workflow', 'show me what this looks like', 'get this to a demo', 'visual gate'. Consumes SCR- (Screen Flow Definition), PER- (Personas), UJ- (User Journeys), DES- (Design Components). Outputs Stitch prompt blocks per SCR- entry + Feedback Capture Template. No new SoT IDs created — this skill makes existing SCR- entries visual and routes feedback back to them.
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。
WorkRally CLI (workrally) — 面向 AI Agent 的 AIGC 漫剧视频创作全流程工具集。支持 AI 生图、AI 生视频、视频提示词优化、画布生音频/音乐、混元 3D 模型生成、AI 生音频、项目/剧集/场次/分镜的完整 CRUD、资产库、媒资管理、无限画布、文件上传下载等。Use when user asks to generate images, generate videos, generate audio, generate music, generate 3d, optimize video prompts, manage projects, series, shots, upload files, download assets, manage materials, or interact with WorkRally platform via command line.
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。
DALL-E 3 API for AI image generation — text-to-image, image editing, and variations via OpenAI. Use when generating images from text prompts, creating product visuals, illustrating content, or editing images with an inpainting mask.
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。
Continue is an open-source AI code assistant for VS Code, JetBrains and the terminal (the cn CLI) that works with any LLM: Claude, GPT, Gemini, Ollama and other local models. Use when a user asks to configure Continue with config.yaml, add chat or tab autocomplete models, write rules or custom prompts, connect MCP servers, run cn headless in scripts, or migrate from config.json. Continue was acquired by Cursor in June 2026: the release from that month is final and the Hub is offline, so the skill covers local, self-configured use.
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。
You are an expert in Bolt.new by StackBlitz, the AI-powered full-stack development environment that runs entirely in the browser. You help developers go from idea to deployed app in minutes using natural language prompts — Bolt generates complete applications with frontend, backend, database, and deployment, all running in a WebContainer without local setup.
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。
Integrate Claude AI into applications with the Anthropic SDK. Use when a user asks to add Claude to an app, use Claude for text generation, build a chatbot with Claude, use Claude's long context window, implement tool use with Claude, stream Claude responses, use Claude for code generation, document analysis, or reasoning tasks. Covers Messages API, streaming, tool use, vision, system prompts, extended thinking, and batch processing.
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 & embed AI transcripts as Obsidian callouts. Args: <path>, all, refresh <path>. Prompts for URLs if empty.
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。
Audit experiment integrity against the evidence ledger. At L2 (repo + result files present) a fresh cross-model reviewer reads the eval code line-by-line for fake/derived ground truth, score self-normalization, phantom results (a paper number with no backing file/key), dead/uncalled metric code, verified-scope inflation, method-described ≠ method-evaluated drift, synthesized-looking results, placeholder/fake data still wired into a released result, code-output ≠ reported-number mismatch, and missing reproducibility artifacts (an empirical/agent/LLM paper shipping neither code nor the prompts/configs its results need) — every finding span-anchored to a ledger claim_id. At L0/L1 (PDF / source only) the same patterns are surfaced as info-level 'could-not-verify' signals where the ledger gives an anchor (observability_level_required:2) — NEVER a fraud verdict from a PDF. The reviewer PROPOSES findings; tools/adjudicate_findings.py computes the verdict. Detect-only. Triggers: "experiment forensics", "audit the results", "check the eval code", "实验诚实度".
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。
Improve and rewrite user prompts to reduce ambiguity and improve LLM output quality. Use when a user asks to optimize, refine, clarify, or rewrite a prompt for better results, or when the request is about prompt optimization or prompt rewriting.
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。
Practical prompt patterns and techniques for effective Claude Code usage. Reference when crafting prompts, planning workflows, or debugging interactions.
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。