「story」の検索結果

An inspired interpretation of HP's design language — a white-paper enterprise-consumer system anchored by HP Electric Blue (`#024ad8`) as the lone signal CTA, near-black ink (`#1a1a1a`) for headlines, geometric Forma-DJR sans throughout, and angular blue-chevron decorations that nod to the HP wordmark's slashes. Cards round at 8–16px, photos sit in soft 16px frames, and dark navy slabs anchor the customer-story and "how can we help" closing bands.

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。

Maxim Design System Intelligence — token architecture (primitive→semantic→component), component library governance, CSS variable systems, Tailwind integration, design-to-code handoff, Storybook, Figma token export. Activate for design system creation, token audits, component specs, dark mode systems, brand-to-token sync. Powered by Maxim behavioral science + Atomic Design + TOGAF governance.

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。

Import Figma content into a HyperFrames composition — rendered assets, brand tokens, components, storyboard sections → reconstructed motion (frames read as states, not slides) (REST/CLI), Figma Motion animations (MCP), and shaders (MCP source / native export). Use when the user pastes a figma.com link or asks to bring a Figma design, frame, logo, brand, or animation into a video/composition.

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 and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.

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 rich agent answers and any file, folder, URL, or export into a polished single-file HTML page. Auto-picks a default route plus 17 concrete design systems (teaching, dashboard, atlas, timeline-story, document, …).

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。

Bootstrap a Claude-assisted on-call for this channel/repo: discover the available connectors, mine incident history into draft triage playbooks, interview the human for policy, validate against held-out incidents, and install the scheduled routines. Use when the user wants to "set up on-call", "bootstrap the on-call kit", "onboard this channel", or has just installed the oncall-kit plugin. Five gated phases — never run more than one phase per turn, and never activate anything before Phase 4 sign-off.

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。

Map the big picture around a topic or software repository by identifying its boundaries, layers, actors, components, relationships, flows, history, fault lines, and open questions, then explain how the pieces fit together and where to look next. Use when a user asks to understand a whole field, domain, technology, ecosystem, industry, codebase, architecture, unfamiliar repo, or phrases such as "give me the big picture", "map the landscape", "how does this all fit together?", "help me get oriented", or "what am I missing?"

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。

Identify at-risk customer accounts by analyzing usage patterns, engagement signals, and support history to generate churn risk scores and intervention recommendations. Use when the user requests churn analysis or provides relevant inputs for this workflow.

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。

Think and work like an expert Mammalogist. Use when a task calls for Mammalogist judgment. Reasons from mammalian life history and detectability-limited sampling through ASM MDD taxonomy, Sherman/camera-trap/SCR survey design, occupancy and SECR models, bat acoustic validation, and museum voucher discipline while treating trap heterogeneity, camera autocorrelation, closure violation, and WNS decontamination gaps as first-class failure modes.

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。

Think and work like an expert Earthquake Engineer. Use when a task calls for Earthquake Engineer judgment. Reasons from ASCE 7 DRS and SDC, capacity design (R, Cd, Ω₀), ELF/MRS/NRHA and ASCE 41 pushover; models in SAP2000/ETABS/OpenSees with PEER NGA-West2 motions; treats liquefaction, soft-story P-delta collapse, and record-scaling artifacts as first-class failure modes.

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。

Think and work like an expert Additive Manufacturing Engineer. Use when a task calls for Additive Manufacturing Engineer judgment. Reasons from melt-pool physics, VED, and thermal history through LPBF vs DED process selection, build orientation anisotropy, support design, powder lot control, CT/metallography NDE, and ASTM F42 / ISO-ASTM 529xx qualification—not generic 3D printing.

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。

Append-only gap closure and the cadence engine for research theses. Evaluates artifact CURRENT state (never git history, never task checkboxes) against current pins and wrong_if falsifiers, then appends a Convergence section to tasks.md re-proposing the gaps. A clean run leaves tasks.md byte-identical. Deterministic gaps (stale, invalidated) are uncapped; judgment-class gaps are capped per spec 046 Q40.

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。

Earnings sentiment analysis, analyst estimates vs guidance, earnings surprise history, consensus sentiment, earnings revision trends, analyst rating changes, earnings beat miss track record, guidance accuracy, whisper numbers, pre-announcement sentiment

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。

Direct, build and render premium cinematic motion design from code — launch films, product and feature videos, looping feature animations for landing pages and social, logo stings and reveals, UI walkthroughs, app demos, kinetic type, teasers, trailers, intros and promo clips. Use this whenever the user wants any video, animation, motion graphic or animated demo made with Remotion, HyperFrames, HTML/GSAP or React, or asks to storyboard, time, score, render, polish or critique one — even if they only say "make a video about X", "animate this feature" or "we need a launch clip". It supplies concept and copy discipline, type and colour taste that defers to a supplied brand, a beat-locked timeline that drives both picture and a synthesized soundtrack, choreography and transition craft, real product UI in motion, film-grade finishing (true motion blur, no banding, BT.709, sync-checked mux) and a measured self-critique loop on contact sheets and renders.

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。

Produce and operate Amazon Nova Reel video-generation jobs through Amazon Bedrock. Use for Nova Reel text-to-video, image-conditioned animation, automated or manual multi-shot storyboards, async S3 delivery, cost and approval gates, production continuity, output custody, and AWS-specific safety, privacy, IAM, and provenance decisions.

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 production workflow for creating Manim-based explainer animations. Use when an agent must plan, code, render, QA, or hand off precise math, science, data, diagram, algorithm, or concept animations with Manim, including storyboard, scene architecture, formulas, coordinate systems, voiceover timing, accessibility, reproducibility, provenance, and delivery decisions.

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, troubleshoot, and hand off provider-independent in-camera VFX and LED volume virtual-production work, with Unreal Engine/nDisplay/Live Link awareness. Use for ICVFX suitability, LED stage geometry, frustums, tracking, lens calibration, sync, render nodes, color, lighting/reflections, artifact mitigation, rehearsal, live-composite fallback, monitoring, records, QA, and handoff. Do not use for ordinary offline post compositing, generic storyboards, or full game production.

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 motion graphics direction for AI agents producing title sequences, lower thirds, explainer graphics, product UI overlays, social ads, kinetic typography, diagrams, data callouts, brand films, and video post. Use when planning, prompting, storyboarding, specifying, implementing, reviewing, or QAing motion graphics across live footage, generated video, UI capture, data visualization, brand systems, typography, accessibility, claim integrity, runtime handoff, and iteration.

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。

Direct cinematic shots and coverage for AI-assisted content production. Use when an agent must translate story intent into framing, shot size, lens and perspective, camera position, movement, blocking, screen direction, lighting-aware coverage, continuity, shot specifications, or diagnose why generated or filmed shots do not cut together.

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 reference media analysis for generated-media production. Use when an agent must analyze reference images, videos, audio, style boards, product shots, brand assets, mood boards, storyboards, performances, prior cuts, or client examples and translate them into safe, non-copying direction, prompts, QA criteria, provenance records, and handoff notes for image, video, audio, avatar, or post-production agents.

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 explainer video production for AI agents creating educational, product, concept, nonprofit/public-service, onboarding, training, animated, mixed-media, and short social explainers. Use when an agent must turn a topic, brief, research corpus, product, process, policy, dataset, or complex idea into a factual, accessible, narrated, captioned, storyboarded, generated-media-ready explainer video with claim review, localization, pacing, variants, and 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。

Provider-independent editing and montage direction for AI agents producing generated videos, ads, trailers, social clips, explainers, product videos, documentary-style pieces, and music- or beat-driven cuts. Use when planning, revising, QAing, or handing off an edit: story structure, shot selection, continuity, montage theory, rhythm and pacing, J/L cuts, match cuts, cutaways, transitions, beat sync, platform timing, source/generated asset management, revision workflow, and composition handoff.

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 personalized triathlon, marathon, and ultra-endurance training plans. Use when athletes ask for training plans, workout schedules, race preparation, or coaching advice. Can sync with Strava to analyze training history, or work from manually provided fitness data. Generates periodized plans with sport-specific workouts, zones, and race-day strategies.

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 60–90 second, collage-style HyperFrames explainer from a hiding-in-plain-sight topic or supplied documents and links. Use for requests such as 'make a plain-sight explainer', 'Vox-style history of X', 'why is X everywhere?', or 'turn this document into an explainer'. Covers topic or source routing, research, script, static design approval, voiceover timing, motion continuity, build, and numeric quality gates.

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。