Browser-based 3D design tool with visual editor, animation, and web export. Use this skill when creating 3D scenes without code, designing interactive web experiences, prototyping 3D UI, exporting to React/web, or building designer-friendly 3D content. Triggers on tasks involving Spline, no-code 3D, visual 3D editor, 3D animation, state-based interactions, React Spline integration, or scene export. Alternative to Three.js for designers who prefer visual tools over 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。
freshtechbro/claudedesignskills☆ 1,0542025年11月20日 更新
Blender to web export workflows for 3D models and animations. Use this skill when exporting Blender models to glTF for web, optimizing 3D assets for Three.js or Babylon.js, batch processing models with Python scripts, automating Blender workflows, or creating web-ready 3D pipelines. Triggers on tasks involving Blender glTF export, bpy scripting, 3D asset optimization, model compression, texture baking, or Blender automation. Exports models for threejs-webgl, react-three-fiber, and babylonjs-engine skills.
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。
freshtechbro/claudedesignskills☆ 1,0542025年11月20日 更新
When the user wants to improve E-E-A-T, add trust signals, or optimize for expertise and authority. Also use when the user mentions "E-E-A-T," "E-E-A-T signals," "experience expertise authority trust," "author bio," "YMYL," "trust signals," "expertise signals," "authority signals," "citations," "references," or "credibility." For headings, use heading-structure.
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。
kostja94/marketing-skills☆ 1,0392026年10月6日 更新
Use when an agent drives Godot 4.7 on macOS or Windows for any task: headless --script jobs, --import, --check-only, command-line exports, GUT tests, windowed screenshots, the headless editor (-e) or an MCP server into a running editor; when a run hangs or fails silently, a capture is black, Godot 3 code breaks in 4.x, 'Identifier not found', export templates are missing; or when a Godot brief (2D, 3D, shaders, VFX, UI, multiplayer, export) must go to the right scenario-godot-* specialist.
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。
scenario-labs/skills☆ 1,0092026年10月15日 更新
Use when a ZBrush sculpt, scan or AI-generated mesh must become production topology and files (ZRemesher and guides, the 2026 Retopo brush, reprojecting detail with Project All, rebuilding subdivision levels, UV Master or native unwrap, normal and displacement maps with Multi Map Exporter, GoZ, OBJ or FBX export, scale and axes, Decimation Master, "clean up an AI mesh in ZBrush"), or when detail is lost after ZRemesher, a map is upside down or an export arrives at the wrong size.
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。
scenario-labs/skills☆ 1,0092026年10月15日 更新
Use when writing or fixing Maya pipeline code in Python: mayapy batch jobs over many scenes, validating and auto-fixing scenes, FBX export for Unreal or Unity (static, skeletal, animation clips, Game Exporter), Alembic or GPU caches, USD export, stages and layers, references and namespaces, PySide6 tool windows, OpenMaya 2.0 plug-ins, or slow playback. Also when an FBX lands with wrong scale, normals, tangents or extra takes, a USD export has one frame or smoothed meshes, or one bad file kills a batch.
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。
scenario-labs/skills☆ 1,0092026年10月15日 更新
Compose pages and sites that read as their vertical: ecommerce-catalog storefronts that look like storefronts, hospitality-food sites that look like restaurants, b2b-manufacturer sites that look industrial. Use this skill whenever the user wants to build a site that looks like the vertical it serves, fix a build that reads as generic or off-vertical, build to an experience bar produced by competitor-experience-audit, or compose pages with the merchandising, density, and layout conventions a credible site in the category is expected to carry. Triggers on vertical conventions, storefront layout, ecommerce layout, retail conventions, merchandising layout, category page composition, site composition, build to the experience bar, make it look like the vertical, off-vertical, looks generic, build conventions for a vertical, site grammar. Also triggers when a build that is technically clean reads wrong for its category, and the cause is composition, not visual taste.
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。
rampstackco/claude-skills☆ 9652026年10月7日 更新
Audit the brand, UX, and site design of the leading sites in a vertical as a set of observable cross-site patterns, producing the experience bar a new build must meet or beat. Use this skill whenever the user wants to assess the competitive design field, capture vertical conventions, identify the design and UX bar of a category, or set the experience standard before a build. Triggers on competitor experience audit, UX audit, site design audit, brand audit, design conventions, what makes these sites good, vertical conventions, storefront patterns, merchandising patterns, layout density, primary task, design bar, category conventions, retail vs marketing register, what does the field do. Also triggers when an audit of the competitive field has captured technical signals (SEO, accessibility) but never named the brand, UX, or design conventions, and the build downstream will read as off-vertical without that bar.
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。
rampstackco/claude-skills☆ 9652026年10月7日 更新
Generate, evaluate, and narrow brand concepts during early ideation including positioning territories, naming candidates, mood directions, and narrative angles. Use this skill whenever the user is in the early phase of brand creation, exploring brand directions, brainstorming names, building moodboards, generating positioning options, or trying to choose between multiple brand directions. Triggers on brand ideation, brand concept, naming, brand name, name candidates, positioning, brand positioning, mood board, brand directions, exploring brands, early brand work, brand exploration, brand brainstorm, brand options. Also triggers when the user has multiple half-formed brand ideas and needs help converging on one, even if they do not say 'ideation' explicitly.
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。
rampstackco/claude-skills☆ 9652026年10月7日 更新
Produce honest product reviews and buying guides without fabricated first-hand experience, using disclosed evidence tiers: verified specs, owner-experience synthesis at scale, expert triangulation, and hands-on only when true. Use this skill whenever the user wants to write product reviews or buying guides without hands-on access, set up a review methodology, add evidence disclosure to review content, align reviews with Google's reviews system or FTC affiliate disclosure expectations, or decide when Review and Product schema are honest to use. Triggers on product review, buying guide, best-of list, review methodology, evidence basis, hands-on testing, we tested, affiliate review site, review disclosure, methodology block, original research, reviews system. Also triggers when review content claims testing that did not happen, or when an affiliate site needs a trust mechanism that survives scrutiny.
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。
rampstackco/claude-skills☆ 9652026年10月7日 更新
Export Administration Regulations (EAR, 15 CFR Parts 730-774) compliance advisor — ECCN classification across all 10 CCL categories and 5 product groups (A-E), EAR99 determination, jurisdiction analysis (EAR vs ITAR order of review), license requirement analysis via Country Chart, all license exceptions (LVS, GBS, CIV, TMP, RPL, GOV, TSU, ENC, TSR, APP, BAG, AVS, ACE), end-user/end-use controls (Entity List, Denied Persons List, Unverified List, MEU List), deemed export rules, Foreign Direct Product Rule (FDPR), de minimis thresholds, 10 General Prohibitions, SNAP-R license applications, voluntary self-disclosure, civil/criminal penalties, Export Compliance Program (ECP) design, and EAR vs ITAR jurisdiction determination. Use for any dual-use export control, CCL classification, or BIS compliance question.
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。
Sushegaad/Claude-Skills-Governance-Risk-and-Compliance☆ 9592026年10月10日 更新
Use when the user asks to "design an experiment", "build a predictive model", "run A/B test analysis", "perform causal inference", "engineer features", "evaluate model performance", "set up MLOps pipeline", "analyze time series", "calculate sample size", or "deploy a model to production". Expert data science covering statistical modeling, experimentation, causal inference, feature engineering, ML deployment, and advanced analytics with Python, R, and SQL.
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。
borghei/Claude-Skills☆ 9152026年10月7日 更新
When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.
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。
Nexus-JPF/note-companion☆ 8692026年10月13日 更新
Export Administration Regulations (EAR, 15 CFR Parts 730-774) compliance advisor — ECCN classification across all 10 CCL categories and 5 product groups (A-E), EAR99 determination, jurisdiction analysis (EAR vs ITAR order of review), license requirement analysis via Country Chart, all license exceptions (LVS, GBS, CIV, TMP, RPL, GOV, TSU, ENC, TSR, APP, BAG, AVS, ACE), end-user/end-use controls (Entity List, Denied Persons List, Unverified List, MEU List), deemed export rules, Foreign Direct Product Rule (FDPR), de minimis thresholds, 10 General Prohibitions, SNAP-R license applications, voluntary self-disclosure, civil/criminal penalties, Export Compliance Program (ECP) design, and EAR vs ITAR jurisdiction determination. Use for any dual-use export control, CCL classification, or BIS compliance question.
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。
lawve-ai/awesome-legal-skills☆ 8662026年10月3日 更新
Require the learner to explain a concept in their own words before the AI evaluates or extends it. Ensures the AI works from the learner's understanding rather than providing an explanation from scratch.
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。
GarethManning/education-agent-skills☆ 8632026年8月29日 更新
When you want to draft, update, convert, or export a slide deck for a React/Next.js slide system (${SLIDE_DECK_REPO:-$HOME/code/your-slide-deck-site}/src/app/slides/). Writes TypeScript Slide[] arrays using your primitives (Eyebrow, Heading, Accent, Body, BulletList, Divider, TwoCol, GradientText), 12 cycling brand gradients, optional sections for "where am I" context, and speaker notes. Inspired by zarazhangrui/frontend-slides — "show, don't tell" for narrative (presents 3 angles, you pick) plus density modes (speaker-led vs reading-first). Four modes — new (draft from brief), update (modify existing, with overflow guards), ppt (convert legacy PPTX → React deck), export (Playwright snapshot existing React deck to standalone HTML, PDF, or Vercel URL — keeps brand). Triggers on "/slide-deck," "/slides new," "/slides export," "/slides update," "/slides ppt," "draft a deck," "deck for [topic]," "talk on [topic]," "keynote on [topic]," "internal deck for [audience]," "convert this pptx," "export this deck."
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。
coreyhaines31/makerskills☆ 8622026年10月9日 更新
Expert blueprint for idle/clicker games including big number handling (mantissa + exponent system), exponential growth curves (cost_growth_factor 1.15x), generator systems (auto-producers), offline progress calculation, prestige systems (reset for permanent multipliers), number formatting (K/M/B suffixes, scientific notation). Use for incremental games, idle games, or cookie clicker derivatives. Trigger keywords: idle_game, big_number, exponential_growth, generator_system, offline_progress, prestige_system, number_formatting.
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。
thedivergentai/Game-Dev-Agentic-Skills☆ 8542026年10月14日 更新
Godot Expert Auditor: Aurelius. Exhaustive never-list enforcement and architectural slap-down for Godot 4.7 projects. Use when auditing signal decay, ObjectDB orphans, typed Array/Dictionary slop, material.duplicate batch breaks, export case-sensitivity, Expression.execute risks, or sector never-lists. Keywords: auditor, Aurelius, never-list, signal decay, ObjectDB orphans, typed Array, export case-sensitivity, instance uniforms, PackedScene.get_state.
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。
thedivergentai/Game-Dev-Agentic-Skills☆ 8542026年10月14日 更新
Expert blueprint for idle/clicker games including big number handling (mantissa + exponent system), exponential growth curves (cost_growth_factor 1.15x), generator systems (auto-producers), offline progress calculation, prestige systems (reset for permanent multipliers), number formatting (K/M/B suffixes, scientific notation). Use for incremental games, idle games, or cookie clicker derivatives. Trigger keywords: idle_game, big_number, exponential_growth, generator_system, offline_progress, prestige_system, number_formatting.
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。
thedivergentai/Game-Design-Agentic-Skills☆ 8502026年10月13日 更新
Godot Expert Auditor: Aurelius. Exhaustive never-list enforcement and architectural slap-down for Godot 4.7 projects. Use when auditing signal decay, ObjectDB orphans, typed Array/Dictionary slop, material.duplicate batch breaks, export case-sensitivity, Expression.execute risks, or sector never-lists. Keywords: auditor, Aurelius, never-list, signal decay, ObjectDB orphans, typed Array, export case-sensitivity, instance uniforms, PackedScene.get_state.
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。
thedivergentai/Game-Design-Agentic-Skills☆ 8502026年10月13日 更新
Generates data export/import infrastructure for JSON, CSV, PDF formats with GDPR data portability, share sheet integration, and file import. Use when user wants data export functionality, CSV/JSON/PDF export, GDPR compliance data portability, import from files, or share sheet for 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。
rshankras/claude-code-apple-skills☆ 8022026年7月24日 更新
We propose an Asymmetric Within-Sample Transformation (AWST) to regularize RNA-seq read counts and reduce the effect of noise on the classification of samples. AWST comprises two main steps: standardization and smoothing. These steps transform gene expression data to reduce the noise of the lowly expressed features, which suffer from background effects and low signal-to-noise ratio, and the influence of the highly expressed features, which may be the result of amplification bias and other experi
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。
bioMate-AI/biomate-bioconductor-kb☆ 7972026年6月21日 更新
Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of st
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。
bioMate-AI/biomate-bioconductor-kb☆ 7972026年6月21日 更新
This package provides a client for the Bioconductor ExperimentHub web resource. ExperimentHub provides a central location where curated data from experiments, publications or training courses can be accessed. Each resource has associated me
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。
bioMate-AI/biomate-bioconductor-kb☆ 7972026年6月21日 更新