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概要と使いどころ
Generate publication-quality figures and tables from experiment results. Use when user says "画图", "作图", "generate figures", "paper figures", or needs plots for a paper.
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 and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.
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。
Autonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
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 publication-quality AI illustrations for academic papers using Gemini image generation. Creates architecture diagrams, method illustrations with Claude-supervised iterative refinement loop. Use when user says "生成图表", "画架构图", "AI绘图", "paper illustration", "generate diagram", or needs visual figures for papers.
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 Docugenerate tasks via Rube MCP (Composio). 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。
Generate and manage Software Bill of Materials (SBOMs) for the OpenShell project. Covers SBOM generation with Syft, license resolution via public registries, and CSV export for compliance review. Trigger keywords - SBOM, sbom, bill of materials, license audit, license resolution, generate sbom, sbom csv, dependency license, supply chain, license scan.
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 original images, artwork, product visuals, diagrams, or other raster assets with the desktop's configured image provider. Use whenever the user asks to create or generate an image.
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。
Runs the Autoware autonomous-driving stack against CARLA on UE 5.8 over CARLA's native ROS 2 interface — no bridge process. Reports the DDS contract (rt/vehicle/status/* out, rt/control/command/* in), the Autoware-only sensor blueprints, generates the lanelet2 + point-cloud map artifacts Autoware needs instead of an .xodr, and drives the two shipped modes (classical NDT stack, or the camera-only VAD end-to-end model). Use when the user asks to "run Autoware on CARLA", "connect an AV stack", "drive the ego from Autoware", "generate a lanelet2 map", or asks which topics CARLA exchanges with Autoware.
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。
Gets a custom map into CARLA on UE 5.8 — the four distinct routes and which one to pick — via Util/Tools/Import.py for FBX+OpenDRIVE assets into a source build, CARLA_MAPS_TO_COOK to ship a map inside a package, or client.generate_opendrive_world() for an OpenDRIVE-only map at runtime with no build at all. Covers where imported assets land, why an imported map cannot be loaded from a package by name, and the four capabilities the UE4 skill has that ue58 lacks — standalone asset packages, their installer, semantic-material tagging, and a pedestrian navmesh that is generated but silently skipped. Use when the user asks to "import a map", "add a custom map", "load my .xodr", "package my own town", or "create a standalone map 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 building Next.js 14+ applications with App Router, server components, or server actions. Invoke to configure route handlers, implement middleware, set up API routes, add streaming SSR, write generateMetadata for SEO, scaffold loading.tsx/error.tsx boundaries, or deploy to Vercel. Triggers on: Next.js, Next.js 14, App Router, RSC, use server, Server Components, Server Actions, React Server Components, generateMetadata, loading.tsx, Next.js deployment, Vercel, Next.js performance.
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。
Required before calling image_generate. Create and edit images from a prompt — generate an image, make a picture / logo / illustration / icon / banner / poster / thumbnail / hero image / mockup / product shot / social graphic, or edit / restyle / combine existing images from reference images. Uses OpenAI gpt-image-2 through the Hive image service, billed to the user's Hive credits like an LLM call (no API key needed). Teaches the exact call shape, the quality/cost tradeoff (quality="low" is the default and cheapest), reference-image editing, how to show the result to the user with attach_file, and the failure modes (out of credits, model unavailable, moderation).
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 an immutable patch artifact's program impact, regression risk, and auto-merge eligibility. Use for generated patch files, provider pull-request diffs, or commit ranges when reviewers need evidence about affected runtime paths, contracts, tests, and recoverability. This skill is read-only and does not generate, edit, apply, push, or merge the patch.
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 and generates llms.txt files -- the emerging standard for helping AI systems understand website structure and content. Can validate existing llms.txt files or generate new ones from scratch by crawling the site.
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。
Auto-generate a professional, client-ready GEO service proposal from audit data. Creates a full proposal in markdown and PDF including executive summary, findings, recommended service packages (Basic/Standard/Premium), pricing, timeline, and terms. Use when user says "proposal", "proposta", "offerta", "preventivo", "generate proposal", or after completing a GEO audit for a prospect.
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。
Image expert. ALWAYS invoke this skill when you need to read, analyze, describe, or generate images. Use for screenshots, photos, charts, diagrams, AI-generated images, or any visual content.
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 candidate fixes for verified security findings. Consumes TRIAGE.json (preferred), VULN-FINDINGS.json, INCIDENTS.json, or a vuln-pipeline results directory. Pipeline input is delegated to the execution-verified `vuln-pipeline patch` ladder; static-analysis input gets a per-finding patch subagent + independent reviewer and is written as inert diffs for human review. Writes PATCHES/bug_NN/{patch.diff,patch_result.json}, PATCHES.md, and PATCHES.json. Use when asked to "fix the findings", "patch these vulns", "generate fixes", or "close the loop on triage".
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。
Generates Claude Code skills from the Trail of Bits Testing Handbook (appsec.guide), analyzing handbook pages and emitting SKILL.md files with the structure each skill type requires. Use when creating or refreshing a skill from handbook content, or when the user names the testing handbook or appsec.guide. Not for answering security testing questions — the generated skills cover those.
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 image-based alternatives, remixes, or new design directions from a Product Design brief. Use when the user asks for design variants, visual exploration, remixes, or image-generated approaches from provided context.
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 update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, create individual components with proper variant sets and variable bindings, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. Also use when the user asks to create or generate any component in Figma — even a single one — since components require proper variable foundations, variant states, and design token bindings to be production-quality. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded 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。
Assess an immutable patch artifact's program impact, regression risk, and auto-merge eligibility. Use for generated patch files, provider pull-request diffs, or commit ranges when reviewers need evidence about affected runtime paths, contracts, tests, and recoverability. This skill is read-only and does not generate, edit, apply, push, or merge the patch.
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。
Bulk-create Canva designs from tabular data using a brand template with autofill fields, producing one design per row. Use when users say "bulk create designs from this CSV", "generate one design per row", "create a design for each product", "batch generate from a template", or "autofill a template from a spreadsheet". Accepts any tabular data source — uploaded files, pasted tables, JSON, or URLs.
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。
Choose, lay out, critique, and explain data visualizations. Use when the user asks what visualization fits a dataset or goal, how a chart, dashboard, operational workspace, UML-like diagram, or software architecture diagram should be composed or interacted with, asks for visual page design, a layout mockup, generated large-screen and mobile concept images, or to be shown what a visualization could look like, when domain-native contextual surfaces or graphical backgrounds may help, when scrollytelling or parallax might be appropriate, wants a critique of an existing visualization, or needs guidance grounded in trusted visualization theory and practice. For advanced visual design or page-layout prompts where composition affects understanding, Codex must generate and show both large-screen and mobile portrait image concepts before implementation or text-only design handoff, plus mobile landscape when needed.
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 visual assets from text prompts: PNG images (Gemini / xAI Grok, or local Qwen-Image when installed), GLB 3D models (Tripo CLI), rigged characters, retargeted animations, and frame-by-frame animated sprites, plus background removal. Use whenever a game needs generated art.
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 Excalidraw diagrams from natural language descriptions. Outputs .excalidraw JSON files openable in Excalidraw. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", "generate an Excalidraw file", "draw an ER diagram", "create a sequence diagram", or "make a class diagram". Supports flowcharts, relationship diagrams, mind maps, architecture, DFD, swimlane, class, sequence, and ER diagrams. Can use icon libraries (AWS, GCP, etc.) when set up. Do NOT use for code architecture analysis (use the architecture skills), Mermaid diagram rendering (use mermaid-studio), or non-visual documentation (use docs-writer).
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。