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概要と使いどころ
Turn multiview fit reports into a sequential or parallel repair queue for aligning Blender products to source-of-truth templates. Use after validation shows disalignment, when the agent must iteratively fix wireframe, texture, lighting, or projection mismatches, and when skill gaps should trigger self-refinement before another rebuild.
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。
Design and validate texture-state transitions for Blender animations without ugly whole-image crossfades, texture popping, misregistered morphs, or target-engine-incompatible Python-only swaps. Use when animating between multiple source textures, mascot/logo states, style states, lightmaps, decals, or UI skins.
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。
Drive Blender from natural language: create or edit 3D models, materials, lighting, cameras, renders, animation, and exports through Blender MCP. Route complete scenes to domain skills and wireframe/reference requests to reconstruction skills. Also use for 3D requests that do not name Blender. Requires a configured official or ahujasid MCP backend.
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。
Render Blender scenes with the right engine and settings — Cycles for photoreal, EEVEE for speed/stylized, sample counts, denoising (OptiX/OIDN), light path tuning, color management (AgX/Filmic), file output (PNG/EXR/MP4), animation rendering. Use whenever the user asks to "render this", "produce an image", "render a frame / animation", "make a final image", "save the render", or any output-generation request. Make sure to use this skill even if the user does not say "render" — also covers "make a picture", "save the result", "produce a final image", "export as image".
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。
Detect texture-atlas regions and map each source part to its own UV rectangle or projected UV surface. Use when a texture pack must fit a Blender model 1:1, when textures look off/stretched, when alpha decals or lightmaps are provided, or before exporting a textured GLB for a brand mascot/logo.
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。
Lightweight design spec for small changes — tuning adjustments, minor mechanics, balance tweaks. Skips full GDD authoring when a system GDD already exists or the change is too small to warrant one. Produces a Quick Design Spec that embeds directly into story files.
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。
Pre-workflow rapid prototyping for exploring multiple game ideas before committing to a development workflow. Produces lightweight reports with no workflow commitment.
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。
Amazon reverse product selection: filter Amazon niches and keywords by 30+ business dimensions (market size & growth, price tiers & share, competition density & top concentration, demographics such as age/gender/income, review highlights & pain points) from a metrics pool aggregated from historical business insight reports. Trigger when users mention reverse product selection, metrics filtering, niche reverse lookup, blue ocean niche discovery, low-competition niche, newcomer-friendly niche, brand-fragmented market, pain-point entry, feature reverse lookup, pricing tier opportunity, demographic-based selection, or similar terms. Even if the user does not explicitly say "reverse product selection," trigger this skill whenever the request involves filtering Amazon niches that match specific business criteria.
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。
Query Amazon product historical time-series data, including price trends, BSR (Best Sellers Rank) trends, rating changes, seller counts, and monthly sales, supporting any ASIN across multiple Amazon marketplaces. Triggered when users mention price history, price tracking, BSR history, BSR trends, historical pricing, price fluctuations, Nexscope data, rank history, price drop alerts, lightning deal historical prices, Buy Box price trends, coupon prices, FBA/FBM price comparison, seller count changes, rating trends, sales history. Even if users do not explicitly mention "Nexscope" or "time-series data", this skill should be triggered whenever the task involves analyzing Amazon product-level historical data (such as price, rank, or sales trends over time).
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。
AI(ChatGPT·Claude·Gemini 등)가 쓴 한글 텍스트를 "사람이 쓴 글처럼" 윤문해주는 오케스트레이터 스킬. 번역투·영어 인용 과다·기계적 병렬·관용구·피동태 남용·접속사 남발·리듬 균일성·이모지/불릿 과다 등 10대 카테고리 70개 AI 티 패턴을 탐지·분류해 내용은 한 글자도 건드리지 않고 문체·리듬·표현만 자연스러운 한국어로 재작성한다. shim의 route_hint(light|standard|heavy)로 경로를 정해 잘 쓴 글은 1콜, 표준은 2콜, 중증·장문만 3+콜(진단→겨냥 윤문→finalize)로 처리한다. 트리거 — "AI 티 없애줘", "AI 같은 글 자연스럽게", "GPT/ChatGPT 문체", "AI 번역투 고쳐", "사람이 쓴 것처럼 윤문", "AI 윤문", "ChatGPT 티 제거", "한글 AI 탐지·윤문", "AI 글 사람처럼", "번역투 제거", "영어 인용 많은 글 윤문", "AI 글 티 안 나게", "휴머나이저", "humanize Korean", "AI detector bypass 한글". 후속 작업 — "특정 카테고리만 다시", "윤문 강도 조정", "장르 바꿔서", "이 문단만", "2차 윤문" 도 모두 이 스킬. 단순 맞춤법·오탈자 교정은 직접 처리, 번역은 번역 스킬, 내용 추가·삭제를 동반한 재작성은 별도 집필 스킬.
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。
Lightweight, script-driven variant of data2motion for turning data into a smooth, on-brand animated chart (one self-contained HTML) — built for a TEXT-ONLY model that cannot see its own output. You never write HTML/CSS/SVG/animation; you extract the data, pick a chart, fill a small JSON spec, and run one build script that owns 100% of the look and the motion, so the result cannot drift from the house template style or lose its smoothness. Use to turn a number/stat/table/CSV/paragraph into a quick animated chart, data reveal, or KPI when you want guaranteed template fidelity with minimal reasoning and no image feedback.
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。
Rapid codebase assessment — lightweight alternative to /gsd:map-codebase
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。
Govern mini-program release readiness and evidence across source branches, semantic versions, build artifacts, test flags, debug paths, sensitive data, permissions, privacy declarations, platform uploads, review submissions, staged versions, production releases, and rollback plans. Use when users ask for a release checklist, packaging, export, version bump, upload readiness, submission readiness, launch status, rollback preparation, or a precise judgment of what has and has not shipped. Defaults to read-only preflight, requires separate explicit authorization for every external state change, and never treats a Git push, successful build, platform upload, review submission, approval, or production publication as interchangeable.
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。
amazon-listing-doctor是由buluslan（公众号：新西楼.AI）研发的亚马逊Listing质检Skill，他会基于 CDQ算法 / A9 / COSMO / Alexa 四大底座知识，来给Listing进行全身体检和打分，输出一份诊断报告，帮你揪出"流量加倍、弯道超车"的机会点。 更多跨境电商 AI 实战内容，请关注公众号「新西楼.AI」。 Audits Amazon listing health across CDQ / A9 indexability / COSMO intent-coverage / Alexa discoverability, plus 2026 compliance rules (title 75-char, highlights 125-char, image defects). Pure diagnosis, zero dependencies, works offline. Trigger whenever the user mentions checking/auditing/scoring/diagnosing an Amazon listing's quality — in any language; 中文卖家说 listing 体检 / 质检 / 打分 / 诊断 / 健康度 / 质量分 时同样适用。
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。
Environment-aware pre-flight check. Use when starting work in a new environment, switching machines, or when 'works on my machine' bugs surface. Validates OS, runtime versions, installed tools, port availability, env vars, and disk space BEFORE coding starts. Like sentinel but for the environment, not the 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。
Pre-commit quality gate that catches 'almost right' code. Use when about to commit — auto-fires before commit to validate logic correctness, error handling, regressions, and completeness. Goes beyond linting.
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。
Deploy + marketing orchestrator. Use when user says 'launch', 'ship to production', 'deploy and announce', or 'go live'. Runs the full pipeline — pre-flight tests, deployment, live verification, marketing asset creation, and announcement.
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。
Parse PDFs, Office files, images, and HTML into Markdown/structured outputs with MinerU. Use when SciForge or Codex needs document parsing/OCR for scientific papers, supplementary files, PDFs, scanned documents, tables, formulas, or URL/local-file parsing through MinerU standard or Agent lightweight APIs.
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 Pierre Computer Company's `@pierre/trees` (path-first file tree) and `@pierre/diffs` (shiki-based code/diff renderer) in Kolu. Pierre ships Preact/vanilla cores with optional React wrappers — Kolu consumes the vanilla classes and wraps them in thin SolidJS components. Trigger when: wiring up a file tree, rendering unified diffs or syntax-highlighted files, replacing `@git-diff-view`, or any mention of `@pierre/trees` / `@pierre/diffs` / "pierre library".
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。
Runs Fable 5 and OpenAI Codex as co-founders on the Rocket Fuel operating system. Fable is the Visionary (vision, plan, standards, final review); Codex is the Integrator (filters the plan, executes the build, reports). Context-routed, one entry point, four functions: KICKOFF a new project, CLARITY BREAK to refactor an existing one, SAME PAGE MEETING to pressure-test a plan, BUILD A ROCK to hand Codex a scoped task. Use when the user says /rocket-fuel, wants to start or refactor a project with Codex, wants a plan reviewed by a second model, or wants to delegate a build to Codex.
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。
Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).
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 your Korea experience — Seoul's palaces and K-pop culture, Busan's beaches, Jeju Island's nature, Korean BBQ crawls, and K-beauty shopping. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planning, visa info, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).
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。
Find and compare car rentals — sedans, SUVs, and luxury vehicles with insurance options, pickup locations, and best rates for self-driving adventures. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planning, visa info, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).
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。
Pre-flight gas and balance check before deploying a warp route. Reads a Linear ticket, checks deployer wallet native gas balances per chain (warn if less than $10), and checks collateral token balance (need ~$1 for testing).
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。