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概要と使いどころ
Qianfan Deep Research Agent for complex research tasks. Combines information retrieval, multi-source analysis, content synthesis, and report generation. Use when user needs in-depth research, analysis reports, or comprehensive investigation on complex 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。
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Use this skill whenever the user mentions changelogs, release notes, version updates, "what changed", product updates, app store descriptions, or needs to summarize recent development work for non-technical audiences.
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。
Baidu Baike encyclopedia search skill. Provides authoritative, real-time, structured Chinese encyclopedia knowledge. Use when user needs factual information about concepts, people, places, or 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。
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
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。
Automate Gmail tasks via Rube MCP (Composio): send/reply, search, labels, drafts, attachments. Always search tools first for current schemas.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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 this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
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。
Baidu Maps skill for location search, nearby place search, geocoding, route planning, and weather queries. Use when user needs map services, location information, or navigation within China.
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。
DiDi ride-hailing service skill. Supports taxi booking, price estimation, route planning (driving/transit/walking/cycling), order management, driver location tracking, and scheduled rides. Use when user expresses any transportation need including ride-hailing, route queries, or commuting.
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。
Douyin (TikTok China) content toolkit for video script writing, short video optimization, BGM recommendations, caption generation, trending topic analysis, and video download/info extraction workflows.
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。
Baidu E-commerce skill for cross-platform price comparison, review analysis, and purchase knowledge. Complete workflow from product discovery to purchase decision. Use when user wants to compare prices, read reviews, or make purchase 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。
Für Vorkasse Abschlag Sicherheit: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: vorkasse-abschlag-wartung-maintenance-website.
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。
Für Wartung Maintenance: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
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。
Für Konzernklausel: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: agb-konzernklausel-datenaustausch-haftung.
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。
Leverage OpenAI Codex/GPT models for autonomous code implementation, code review, and plan review. Triggers: "codex", "use gpt", "gpt-5", "let openai", "full-auto", "adversarial review", "second opinion review", "用codex", "让gpt实现", "对抗式审查", "让codex审查计划", "第二意见". Use this skill whenever the user wants to delegate coding tasks to OpenAI models, run code or plan reviews via codex, get a second-opinion review from a different model, or execute tasks in a sandboxed environment.
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。
Assess physical and transition climate risk for a site, product, or portfolio with scenario-based structure. Use when asked to run a climate risk assessment, evaluate physical or transition risk, prepare TCFD/ESRS-style climate risk analysis, or assess how climate scenarios affect an asset or business. Produces a hazard-exposure-vulnerability matrix across 2030/2040/2050 horizons and labelled scenarios, with financial-impact ranges, confidence levels, and adaptation options.
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 this skill when conditioning, loading, preparing, or labeling signal data for analysis or ML training. Covers: cleaning a single signal (fill gaps, remove drift, deoutlier, denoise, resample/align a time base) BEFORE analysis; building a `signalDatastore` pipeline; creating a `labeledSignalSet` for Signal Labeler; deriving labels (filename, folder, in-file, ROI, time-frequency ROI); stratified train/val/test splits; framing long signals; parallel processing; and shaping datastore output for `trainnet`. Triggers include "clean up this signal", "remove drift / detrend", "fill gaps", "remove spikes / outliers", "denoise", "resample to a uniform rate", "align channels", "labels from filenames", "stratified split", "prepare for Signal Labeler", and function names like `fillgaps`, `fillmissing`, `detrend`, `filloutliers`, `smoothdata`, `resample`, `synchronize`, `signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`.
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。
Configure, simulate, debug, and analyze radarDataGenerator within radarScenario. Use for: interactively building radar detection scenarios from datasheets or performance requirements; diagnosing missed detections and configuration errors; interpreting sensor spherical, body, and scenario-frame outputs; deriving ReferenceRange from hardware specs via link budget; scan mode configuration (mechanical, electronic/AESA, hybrid); and validating simulation results against analytical predictions.
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 creating or revising finished video thumbnails or cover images with Scenario: game trailers, boss reveals, patch updates, devlogs, or community videos needing readable composition, exact headline text and consistent characters. Not for title ideas or critique alone, in-video title cards, or a generic image without a thumbnail deliverable.
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 creating a ChatGPT pet or Codex pet with Scenario: hatching an animated companion from a text idea, a character, mascot or brand cue, or reference photos and art; making the 1536x2288 v2 pet sprite sheet with nine animation states and sixteen look directions, the 1536x1872 v1 sheet ChatGPT web uploads, a pixel-perfect pixel-art pet, an animated GIF of the pet, or a Codex pet.json package.
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 making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants. Also for revising one variant or resuming a partially completed batch. Not for a new commercial from a still image, ordinary single-clip grading, or automatic Cartesian combinations.
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 one image must be composed from several reference pictures through the Scenario MCP server, each lending one thing: the character from one, the place, pose, style, light, palette, material, outfit, or layout from others. Also when a reference leaks into the result (its object, colors, or face showing where it should not) or a reference's role is ignored. Keywords: multi-reference, reference roles, combine references, style reference, pose reference, give each picture a job.
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 an agent drives Unity 6.3 (6000.3) on a Mac for any task: batch mode and -executeMethod jobs, a running editor (the user's GUI editor or a headless one), the Unity CLI and com.unity.pipeline, MCP servers, the Test Framework, command-line builds; when a batch run fails silently, 'Scripts have compiler errors', a capture comes back black or pink, or a result must be proven with numbers and a frame; or when a Unity brief must go to the right scenario-unity-* 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。
Use when building 3D levels and worlds in Godot 4.7: third-person or FPS controller, player stuck on stairs, spring arm camera clipping, blockout with CSG, GridMap and MeshLibrary, terrain (heightmap, HeightMapShape3D, Terrain3D regions, textures, painting), scattering trees with MultiMesh, streaming a big world, procedural meshes with SurfaceTool, Jolt physics settings, importing GLB or glTF from Blender or AI generators (Scenario, Tripo, Meshy, Hitem3D), import scripts, name suffixes, model facing, collision generation, LODs.
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。