「custom」の検索結果

Provider-independent production workflow for recutting long talking-head, podcast, interview, webinar, panel, lecture, livestream, founder call, or customer-call footage into short clips, highlight reels, trailers, audiograms, captioned vertical videos, and social cutdowns. Use when an agent must ingest source recordings, transcribe and diarize speakers, select quotes without misrepresentation, preserve context, handle consent/rights/disclosures, clean jump cuts and audio, add captions, graphics, lower thirds, b-roll, platform variants, synthetic-media boundaries, review packets, delivery specs, and recut 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。

Capture high-quality screenshots of any public URL at custom resolutions. Supports desktop and mobile viewports, full-page captures, and specific element targeting. Ideal for visual monitoring, design research, and content archival.

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。

Research local markets by combining Google Maps reviews, Xiaohongshu local content, Weibo discussions, and web search. Covers customer sentiment by location, local competition analysis, neighborhood trends, and location-specific brand perception.

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 sentiment in any text — reviews, social posts, feedback, or articles. Returns sentiment polarity (positive, negative, neutral), confidence score, and key phrases driving the sentiment. Useful for brand monitoring, customer feedback analysis, and content evaluation.

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。

Research and collect social proof — testimonials, case studies, user reviews, social mentions, and community endorsements across platforms. Useful for marketing teams building trust content, landing pages, and sales collateral from authentic customer voices.

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。

Search discussions, track communities, analyze posts, and discover trends on Reddit through SandBase. Use when asked for Reddit research, community analysis, trending topics, discussion monitoring, content discovery, or audience insight beyond customer-focused research.

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。

Extract and analyze product reviews from e-commerce and review sites. Aggregates ratings, identifies common themes in positive and negative feedback, and surfaces actionable product insights from customer voices across platforms.

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。

Aggregate and analyze product and business reviews from Google Maps, Amazon, Akta, and Xiaohongshu. Cross-platform review intelligence including rating patterns, common themes, competitive comparison, and customer satisfaction trends.

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。

Research products across Amazon, Google Shopping, and Xiaohongshu to understand pricing, reviews, market positioning, and consumer sentiment. Covers competitive product analysis, pricing benchmarks, feature comparison, and customer satisfaction signals.

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 customer reviews for local businesses on Google Maps. Covers review extraction, sentiment patterns, rating distribution, common complaints, and competitor review comparison for local business intelligence and reputation management.

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。

Triage and prioritize a support ticket or customer issue. Use when a new ticket comes in and needs categorization, assigning P1-P4 priority, deciding which team should handle it, or checking whether it's a duplicate or known issue before routing.

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。

Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP 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。

Remove sequencing adapters from FASTQ files using Cutadapt and Trimmomatic. Supports single-end and paired-end reads, Illumina TruSeq, Nextera, and custom adapter sequences. Use when FastQC shows adapter contamination or before alignment of short reads.

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。

Reviewer role. Opens rendered HTML, inspects every slide visually, fixes problems in custom.css or slides.html and rebuilds through build-html.sh. Use whenever the user says "review", "QA", "check slides", "inspect", "audit", "proofread", or wants feedback on a rendered 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。

Extract structured company lists from directories with Firecrawl. Use for scraping YC, Crunchbase, Product Hunt, G2, startup directories, category directories, or custom company databases into JSON, CSV, CRM-ready lists, or research tables.

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 pre-meeting lead intelligence briefs with Firecrawl. Use when the user needs company research, person research, recent news, talking points, pain points, or outreach preparation before a sales call, partnership meeting, investor conversation, or customer interview.

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 SDK for Python (the `ai` package). Use for Python model calls (LLMs, image, video, speech, embedding, transcription, reranking, or evaluation), agents, model interaction tests, tool calling, subagents, approvals, durable execution, telemetry, AI SDK UI backends, and custom providers.

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 the user needs a professional marketer's operating mindset for any marketing, growth, or client-acquisition task — finding first customers, writing an ad or landing page, designing ad creatives and visuals (how the eye works: background, scene, hero, movement), evaluating an idea, deciding whether to do X to get Y, positioning or launching a B2B or SaaS product, running cold outreach, setting up ads, or writing copy — not a tactical template.

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。

CesiumJS primitives and geometry - Primitive, GeometryInstance, Appearance, BufferPrimitive collections, GeoJsonPrimitive, Billboard/Label/PointPrimitive collections, built-in geometry shapes, ground primitives, classification. Use when rendering performance-critical static or vector geometry, loading GeoJSON without entities, creating custom shapes, batching draw calls, or using low-level collections.

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。

CesiumJS terrain, globe, and environment - TerrainProvider, Globe, sampleTerrain, atmosphere, sky, fog, lighting, shadows, panoramas. Use when configuring terrain providers, querying terrain heights, customizing atmosphere or sky rendering, adding panoramas, or adjusting scene lighting and shadows.

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。

CesiumJS camera control - Camera, flyTo, lookAt, setView, ScreenSpaceCameraController, composable Controller camera controllers (1.144), CameraEventAggregator, flight animation. Use when positioning the camera, creating flyTo animations, constraining user navigation, adding custom or asset-inspection camera controllers, tracking entities, or converting between screen and world coordinates.

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 beautiful, distinctive HTML/CSS/JS control panels for MATLAB uihtml components. 8 built-in styles (Clean, Material, Cosmic Dark, Neumorphic Dark, Dashboard Light, Midnight Gradient, Minimal Mono, Warm Dark) plus custom aesthetics. Produces production-grade UI with sliders, buttons, toggles, and panels. Use when building visually polished MATLAB app UIs with uihtml.

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。

The moi workspace — the web UI the user chats from, extended with agent-authored applets (widgets, views) plus theme & config. Read this FIRST when a message carries a hidden moi-context envelope or the user uses moi vocab such as workspace, applet, widget, view, scratchpad, dashboard, or a `moi` command, or asks to build, edit, customize, or theme the workspace UI or its 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。

Test application performance with k6 load/stress/soak/spike scripts and k6 scenarios, Lighthouse CI for Web Vitals, and performance budgets as CI gates. Covers load profiles, custom metrics, bottleneck identification, and Core Web Vitals (LCP, INP, CLS). Use when: "performance test," "load test," "stress test," "soak test," "spike test," "k6," "k6 scenarios," "Lighthouse," "Web Vitals," "Core Web Vitals," "performance budget." Not for: scheduled production probes — use synthetic-monitoring; pixel-diff regressions — use visual-testing; designing tests from prod telemetry — use observability-driven-testing. Related: ci-cd-integration, qa-metrics, release-readiness.

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。