「eal」の検索結果

Use only when the user asks to produce a finished multi-scene narrator-led video and explicitly requests a faceless channel, YouTube automation, narrated explainer/story/education, documentary, storybook or myth retelling, or kids song video. Topic alone is never enough: a generic video of/about something, including a historical topic, uses ordinary video generation. Do not use for planning or ideas, single clips, silent animation, image-to-video, footage edits, ads, product demos, or UGC. This workflow requires a consistent non-photoreal style, reusable assets, narrator voiceover, and burned subtitles.

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 WebGL-accelerated data visualizations with Three.js, raw WebGL, deck.gl, luma.gl, PixiJS, Sigma.js, Plotly WebGL traces, ECharts GL, CesiumJS, Babylon.js, or related GPU libraries. Use when the visualization needs true spatial structure, dense 2D or 3D GPU rendering, particle or flow animation, volumetric views, or interactive exploration that adds real analytical value.

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 implement parallax scrolling and scrollytelling data visualizations. Use when the user asks for parallax scrolling, scrollytelling, scroll-driven timelines, sticky graphics, Scrollama, ScrollTrigger, ScrollTimeline, view timelines, rich-media timelines, moviescrollers, scroll-scrubbed charts, staged narrative reveals, or interactive visual stories where scrolling changes a data visualization or media scene.

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 AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

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 dashboards and live visualization systems. Use when the user needs monitoring views, streaming charts, coordinated interactions, downsampling, or performance-aware operational visualization.

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。

Define a Proof of Life probe to test a risky hypothesis cheaply. Use when you need harsh truth before building real product.

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。

Select the right Proof of Life (PoL) probe based on hypothesis, risk, and resources. Use this to match the validation method to the real learning goal, not tooling comfort.

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。

Audits agent config, instruction drift, hooks or MCP, and AI maintainability. Use when Claude, Codex, or Pi setup looks wrong. Not for application bugs or PR review.

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。

Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Use when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do NOT use for general maintainer lists, non-security ownership questions, or threat modeling (use security-threat-model).

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。

When the user wants to define GTM metrics, build a metrics dashboard, measure pipeline efficiency, or track AI product performance. Also use when the user mentions 'GTM metrics,' 'revenue latency,' 'pipeline metrics,' 'TTFV,' 'time-to-first-value,' 'data health,' 'attribution,' 'conversion rate,' 'CAC,' 'LTV,' 'NRR,' 'GTM dashboard,' 'magic number,' 'pipeline velocity,' or 'funnel metrics.' This skill covers GTM measurement from metric selection through dashboard design, including AI-specific cost metrics, attribution models, and weekly review cadences. Do NOT use for technical implementation, code review, or software 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。

When the user wants to sell through social media, optimize LinkedIn for sales, build DM sequences, or convert content engagement into pipeline. Also use when the user mentions 'social selling,' 'LinkedIn selling,' 'LinkedIn DMs,' 'social prospecting,' 'LinkedIn Sales Navigator,' 'DM sequences,' 'LinkedIn outreach,' 'social pipeline,' or 'LinkedIn optimization.' This skill covers social selling strategy from profile optimization through DM-to-deal conversion. Do NOT use for technical implementation, code review, or software 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。

Inspect Sentry issues, summarize production errors, and pull health data via the Sentry API (read-only). Use when user says "check Sentry", "what errors in production?", "summarize Sentry issues", "recent crashes", or "production error report". Requires SENTRY_AUTH_TOKEN. Do NOT use for setting up Sentry SDK, configuring alerts, or non-Sentry error monitoring.

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。

Guides design and implementation of evolutionary modular-monolith platforms with DDD (strategic + tactical), flat-by-aggregate organization, an Anti-Corruption Layer for vendor independence, a transactional outbox for events, smart resilience (backoff with jitter, circuit breakers, idempotency), and a polished architecture HTML document with elegant SVG diagrams. Use when designing a platform or backend, defining bounded contexts, organizing modules and folders, choosing monolith vs microservices, decoupling from an external service (ERP, storage, AI), making calls resilient, adding real-time push, picking a 2026 TypeScript stack (Nx, NestJS, React), or producing an architecture document or diagram. Also triggers on 'modular monolith', 'bounded contexts', 'flat-by-aggregate', 'ports and adapters', 'architecture diagram'. Do NOT use for simple CRUD, NestJS-only deep implementation (use nestjs-modular-monolith), or pure domain-model review (use tactical-ddd).

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。

Analyzes coupling between modules using the three-dimensional model (strength, distance, volatility) from "Balancing Coupling in Software Design". Use when asking "are these modules too coupled?", "show me dependencies", "analyze integration quality", "which modules should I decouple?", "coupling report", or evaluating architectural health. Do NOT use for domain boundary analysis (use domain-analysis) or component sizing (use component-identification-sizing).

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 senior-operator mode for AI agents that resolve tasks end to end without babysitting and never create new problems. The agent verifies every claim against real evidence (web search dated to the current month and year, the codebase, and available tools, MCPs, and CLIs); it never guesses, never fakes confidence, and never claims something is done without proof. It stays silent and keeps working, interrupting the user only on three stops, namely a destructive or irreversible action, a dead-end with no evidence after exhausting sources, or genuine ambiguity that changes the outcome. Output is short, literal, and human. Use when the user says "not-your-babysitter", "nanny mode", "work autonomously", "stop babysitting", or "no hand-holding", or wants an agent that solves problems on its own, especially hands-on engineering and operational tasks. Do not use when the user explicitly wants a tutorial, a verbose walkthrough, or open-ended brainstorming.

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。

Agent-first screenshots — an agent drives the real app via CDP and produces clean, defect-free product screenshots (newsletters, landing pages, social, decks, PR). Dual-channel verification (DOM + pixels + vision) in a capture loop. Use for any "take/redo screenshots of the app" 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。

create a fraimz, make fraimz, prove it works, frame proof, PR proof, validate experience, e2e evidence, fraimz.html. The full fraimz loop — frame the claim, drive the real app via CDP, validate/repair, output fraimz.html. Use whenever a task ends with "please create a fraimz" or any change needs end-to-end proof.

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 or revise music, sound effects and their mix in the active iPolloWork video, using authorized sources, real editable tracks and measured event cues.

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 a realistic Linear cycle plan from current priorities, dependencies, estimates, carryover, and team capacity without silently rescheduling 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。

Scan any agent skill for security risks before you install or use it. Powered by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). 100% local static analysis — no file contents or credentials leave your device. Compatible with CodeBuddy, Cursor, Windsurf, Claude Code, OpenClaw and more. Triggers on: `这个 skill 安全吗`, `skill 安全扫描`, `检查 skill 安全`, `audit skill`, `scan skill`, `check skill safety`, `analyze skill`, `inspect skill`, `verify skill`, `skill security`, `skill supply chain`. Do NOT trigger for general agent usage, full system health checks, project debugging, or normal development.

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 cursor-following fluid WebGPU distortion over an existing image with the Shaders library's ImageTexture and CursorRipples components. Use when a hero, gallery, or media panel needs a water-ripple mouse effect; when replacing a drifting CSS spotlight or flashlight reveal; or when a prompt says to borrow only the shader interaction from a Shaders.com reference while preserving the current brand, image, copy, and layout.

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。

Show the user real screenshots of the work as it progresses, without being asked. Capture the start, the key moment and the result of every visual change, send them as files with captions as soon as each is ready, and look at every image before sending it. Use on any task with a visible result (UI, pages, games, 3D, charts, motion), when the user says "show me", "screenshots", "keep giving me screenshots" or "where are the screenshots?", and before any report that claims a visual change works.

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 skeuomorphic web UI surfaces with layered gradients, stacked inner and outer shadows, reflective gradient borders, micro texture, and embossed text or icon details. Use when asked for pressed, carved, tactile, realistic, soft-plastic, soft-metal, or premium physical interface styling.

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。