2,339 件 ・ 関連度順
概要と使いどころ
Build custom data visualizations with D3. Use when the user needs SVG or DOM-based charts, rich annotation, domain-native contextual backgrounds, data joins, custom scales or interactions, scroll-driven SVG scene states, or precise control over browser visualization behavior.
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 new frontend applications, dashboards, games, creative websites, hero sections, and visually driven UI from scratch, or when the user explicitly asks for a redesign/restyle/modernization. Builds from clean, airy, high-taste, readable image-generated concept design with section-specific references, faithful implementation, and browser 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。
Use when you have a task and must decide WHO does it — yourself, a spawned subagent, or another agent in the topology that already holds the context. The rule: how much would a blank slate have to read in to do this correctly? A lot → route to a context-holding agent; a little → subagent; unsure → a real agent or yourself. NOT the mechanics of fanning out (that's dispatching-parallel-agents / subagent-driven-development) — this is the who/whether decision, and the failure mode that makes teams abandon subagents.
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 any feature or bugfix, before writing implementation 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。
Generative Engine Optimization (GEO) specialist — the technical, on-page publishing work that makes a given page or site discoverable, understandable, trustworthy, quotable, and fresh for AI answer engines (Google AI Overviews, ChatGPT Search, Bing Copilot, Perplexity). Use when asked to 'optimize this page/site for GEO', 'optimize for AI search / answer engines', 'get my page cited by ChatGPT/Perplexity', 'improve AI visibility/citability', 'write an llms.txt', 'add citation-ready structure or schema for AI answers', 'otimizar para busca com IA', or to audit/create/improve a codebase for generative search. Do NOT use for AI-driven SEO content strategy or programmatic pages at scale (use ai-seo), classic keyword/SERP ranking (use seo), accessibility (use web-accessibility), or multi-area site audits (use web-quality-audit).
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。
Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build, then an independent Verifier. Use when the user says "tlc-spec-lean", "plan feature", "specify feature", "write the checks", "build this plan", or "verify work". Do NOT use for standalone design documents unattached to a feature, architecture decomposition analysis, or work that already has a task list or checklist to execute.
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。
Specialist in designing and implementing scalable modular monolith architectures using NestJS with DDD, Clean Architecture, and CQRS patterns. Use when building modular monolith backends, designing bounded contexts, creating domain modules, implementing event-driven module communication, or when user mentions "modular monolith", "bounded contexts", "module boundaries", "DDD", "CQRS", "clean architecture NestJS", or "monolith to microservices". Do NOT use for simple CRUD APIs, frontend work, general NestJS questions without architectural context, or stack-agnostic evolutionary modular monolith design (use evolutionary-modular-architecture).
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。
Feature planning and implementation with 4 adaptive phases (Specify, Design, Tasks, Execute). Auto-sizes depth by complexity. Writes testable requirements in EARS notation, atomic tasks, atomic Conventional Commits, and requirement traceability. Ships deterministic Python validation scripts so structural gates are enforced by code, not memory. Features an independent Verifier (author != verifier, evidence-or-zero), a discrimination sensor, a decision log (STATE.md), a test-coverage matrix, and a self-improving lessons layer. Stack-agnostic and tool-agnostic. Use when (1) planning features, (2) implementing with verification and atomic commits, (3) validating an implementation against a spec. Triggers on "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "record decision", "pause work", "resume work". Do NOT use for pure architecture decomposition analysis or standalone technical design documents.
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。
write the voice-over, demo script first, voiceover instead of PRD, voiceover-first development, align on the demo, script the demo, ship a feature demo-first. The whole demo-driven journey — approve the narration BEFORE any code, then build on a fresh worktree until the demo holds and open the PR with the proof on it. Use when a feature request arrives, or when the user runs /voiceover.
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。
Launch and control standalone Chrome in a Daytona sandbox via CDP. Use for web sign-in, OAuth, Den Web setup, browser-only flows, or when the app should not be driven through Electron CDP.
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 an article, case study, brand narrative, product journey, or long-form story into a cinematic scroll-driven landing page using one of three renderers: scrubbed video, a real-time Three.js world, or semantic HTML/SVG data and typography. Use when the user asks for a scroll world, fly-through landing page, article-to-website transformation, animated planet, data scrollytelling, video-scrubbed page, connected visual journey, or story-led alternative to ordinary stacked sections.
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 any ordered process into a data-driven vertical or horizontal scroll story with a base line, progress fill, active step states, responsive collapse, semantic fallback, and reduced-motion behavior. Use for onboarding, checkout, roadmaps, recipes, case studies, service processes, histories, or narratives where progress through the sequence should become visible while scrolling.
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 architecture procedurally in Three.js and film it assembling — a small geometry vocabulary that builds pagodas, castles, domes and spires from parameters instead of mesh files, hip roofs with flying eaves driven by a single profile function, and a clipping-plane build animation where everything below a rising line is finished work and scaffolding stands above it. Use for construction studies, architectural title sequences, procedural landmarks, or any hero object that should build itself rather than fade in.
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。
Build falling leaves that read as leaves, with each one tumbling on its own axis so it presents a face, thins to an edge, and opens out again, and with its sideways slip driven by that same tumble. Covers the 2-D canvas build and the instanced-3-D variant, where leaves are recycled from, density-versus-count maths, depth layering, colour under a tone-mapped composite, reduced motion, and visibility pausing. Use for autumn maple, sakura petals, blossom, ash, snowfall shapes, or any drifting foliage where a generic particle field reads as confetti.
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。
Build scene-by-scene chapters that advance left to right on one fixed stage while the user scrolls vertically, with native scroll as the only input. One pure function turns scrollY into scene, dwell and move, so forward, reverse, scrollbar drags, fast skips and reload at depth all land on the right frame. Covers dwell versus transition budgets, a burn-wipe or pan between scenes, chapter index and progress UI, glide-to-scene links that skip intermediate scenes, keyboard and reduced-motion behaviour. Use for horizontal scrollytelling, multi-scene product tours, "scroll down to travel sideways", chapter carousels driven by the wheel, or any piece where a wheel-jacked slider keeps breaking on touch, keys, refresh or back.
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 cinematic scroll-driven landing pages with Lenis smooth scrolling, GSAP ScrollTrigger, scroll-linked progression, staggered text reveals, sticky card stacks, parallax backgrounds, scroll-scrubbed transitions, footer reveals, and immersive preloaders. Use when analyzing or building premium editorial scroll experiences, sticky project stacks, kinetic typography, or section-by-section storytelling.
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 a gooey blob system using SVG filters where multiple shapes merge into a single fluid form. Use overlapping circles combined with a Gaussian blur and color matrix filter to produce a continuous, organic mass. The forms should visually fuse and separate based on proximity. Focus on filter-driven merging (blur + threshold effect), soft organic boundaries with no hard edges, multiple independent shapes behaving as one system, and smooth continuous motion that feels fluid and cohesive.
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 you need design-first, spec-driven, skimmable prompts for UI generation. Covers prompt structure, constraints, variations, typography/spacing rules, and iteration workflow for consistent UI outputs.
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。
Add the Shaders WebGPU mouse effect used for the Tidal Commons hero: a white twinkling halftone cursor trail driven by ChromaFlow, masked through a DotGrid, finished with chromatic ripples and film grain, and protected by static, touch, accessibility, SSR, and performance fallbacks. Use when a user asks for this shader mouse effect, a halftone cursor trail, an interactive WebGPU hero/contact background, or a reusable cursor-following shader layer in React, Next.js, Vue, Svelte, Solid, or plain web projects.
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。
Build rich, scroll-controlled real-time Three.js experiences as one persistent 3D world whose camera, lighting, atmosphere, materials, objects, DOM story, and interactions evolve across authored chapters. Use for 3D scrollytelling, scroll-driven WebGL worlds, camera journeys, interactive portfolios, product stories, exhibitions, explainers, game or film microsites, spatial narratives, and multi-scene websites where native scroll should travel through one continuous place. Not limited to landing pages.
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。
Build or refactor reusable, data-driven enemy archetype and moveset systems for Three.js action games. Use for enemy content schemas, model and rig conventions, combat move timing and contact contracts, runtime state boundaries, placeholder fallbacks, deterministic fixtures, or production playthrough validation.
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, trade, and settle permissionless prediction markets on Solana. Use when building prediction market infrastructure, creating social media markets (Twitter/YouTube/DeFiLlama), setting up custom oracle resolution, P2P betting, or autonomous agent-driven forecasting. Supports V2 AMM, P2P (V3), and custom oracle markets with any SPL token collateral (including Token-2022).
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。
Autonomous improvement loop: scan codebase metrics, scaffold experiment files, run agent-driven iterations until metric improves
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。
Collects every tweet in an X (Twitter) conversation thread given a conversation id (root tweet id) — the focal tweet plus all replies, sub-replies, and quote chains — and returns normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, in_reply_to mapping, and cursor for pagination. Use when user mentions Twitter conversation, X conversation thread, conversation_id, thread scraper, scrape Twitter replies, all replies to a tweet, replies under a tweet, sub-replies, nested replies, thread harvester, get replies of a tweet, scrape comments on Twitter, scrape comments on X, full thread extraction, conversation export, conversation tree, reply chain, thread dump, X tweet thread, twitter thread scrape, comment scraping twitter, comment scraping x, focal tweet plus context, root tweet plus replies. Also applies to sentiment analysis on a single viral tweet, controversy mapping, harvesting community Q&A threads, capturing AMA threads, recovering long-running discussions, and any paginated bulk reply collection driven by a conversation id.
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。