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概要と使いどころ
Draft a reply, a follow-up, or a new email in Superhuman in the user's own voice — read the whole thread first, reuse an existing draft instead of adding a second one, keep the right people on the thread, and leave sending to the user unless they asked for it. Use when the user says reply to, answer, follow up with, draft an email to, or send, or when a triage turned up threads that need a response.
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。
Critique and improve the visual design of an existing UI component with concrete implementation guidance. Use when the user asks to redesign, restyle, reimagine, polish, or improve a component, screen, or interface, especially in React and Tailwind codebases.
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。
Cooks and packages a shippable CARLA server from a UE 5.8 ue58-dev checkout via the CMake `package` targets (shipping/development/debug/test), scoping the cook with CARLA_MAPS_TO_COOK, and inspects an existing package for the failures a green build hides — stale pak/ucas mismatch, missing staged OpenDrive/TM road data, missing post-process profiles, and Town15's uncookable content. Use when the user asks to "package CARLA UE5", "cook a map", "build a shipping server", "make a distributable CARLA", or a package builds but renders black / has no maps.
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。
Creates and edits CARLA Leaderboard route files — placing waypoints and scenario trigger points interactively from the spectator camera (route_creator, scenario_creator), visualising an existing route in the simulator (route_displayer), summarising it as a table (route_summarizer), capturing the current weather in route format (weather_creator), sorting scenarios by route position (scenario_orderer) and converting 1.0-format routes to 2.x (route_bridge). Use when the user asks to "make a new route", "add a scenario to a route", "visualise/debug a route", "see what's in this route file", or "convert old leaderboard routes".
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。
Reads a CARLA Leaderboard results.json — per-route driving score, route completion, infraction penalty and the infraction lists — explains how the score was computed for that leaderboard version, and rescores an existing result under the other version's rules (2.0 multiplicative vs 2.1 additive) without re-running anything. Also diffs two runs and merges sharded result files. Use when the user asks "what did I score", "why is my score low", "did my agent pass", "why don't my scores match the leaderboard", or hands over a results.json.
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。
Installs the CARLA Autonomous Driving Leaderboard (leaderboard.carla.org) at a chosen version — 1.0, 2.0 or 2.1 — together with the exact scenario_runner branch and CARLA build each one requires, then wires the four-root PYTHONPATH and verifies the whole stack imports. Detects which version an existing checkout is by reading its code, not its branch name. Use when the user asks to "install the leaderboard", "set up the CARLA challenge", "evaluate my driving agent", "reproduce my leaderboard score", or names a leaderboard version.
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 researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing 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。
Use when generating subtitles with KrillinAI CLI from a YouTube link, Bilibili/local video, or existing media, including platform caption download, Whisper fallback, translation, bilingual SRT, and short vertical subtitle output.
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。
Typeset professional documents with Kami templates: resumes, one-pagers, white papers, letters, portfolios, and slide decks. Use when asked to 做 PDF / 排版 / 简历 / 一页纸 / PPT / slides, or to create a Kami landing page. Not for auditing or restyling an existing product 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。
Use when implementing infrastructure as code with Terraform across AWS, Azure, or GCP. Invoke for module development (create reusable modules, manage module versioning), state management (migrate backends, import existing resources, resolve state conflicts), provider configuration, multi-environment workflows, and infrastructure testing.
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。
Reverse-engineering specialist that extracts specifications from existing codebases. Use when working with legacy or undocumented systems, inherited projects, or old codebases with no documentation. Invoke to map code dependencies, generate API documentation from source, identify undocumented business logic, figure out what code does, or create architecture documentation from implementation. Trigger phrases: reverse engineer, old codebase, no docs, no documentation, figure out how this works, inherited project, legacy analysis, code archaeology, undocumented features.
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 designing new high-level system architecture, reviewing existing designs, or making architectural decisions. Invoke to create architecture diagrams, write Architecture Decision Records (ADRs), evaluate technology trade-offs, design component interactions, and plan for scalability. Use for system design, architecture review, microservices structuring, ADR authoring, scalability planning, and infrastructure pattern selection — distinct from code-level design patterns or database-only design tasks.
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。
Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot learning, creating system prompts with personas and guardrails, building JSON/function-calling schemas, or developing prompt evaluation frameworks to measure and improve model 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。
Guide for modifying an already-installed workspace capability — adding or editing its MCP servers, skills, integrations, or agent guidance. Use when the user wants to customize, change, or extend an existing capability.
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。
Ensure a usable SageMaker execution role exists before deploying or training. Use this skill whenever about to create a SageMaker endpoint, model, training job, or any resource that requires an execution role. Use it especially when the user has not provided a role ARN explicitly, when scripts are about to call `iam:CreateRole`, or when an AccessDenied error mentions an IAM action. Never blindly call `iam:CreateRole` — always check for existing roles first. This skill prevents the most common SageMaker deployment failure: trying to create IAM resources from an SSO principal that has no IAM write permissions.
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。
Read existing Codex Security Cloud findings, reports, recorded assignment and verification, and scan status from the connected account. Use for Cloud read requests and finding links, not local scans or requests to change Cloud 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。
Define, review, or update SECURITY.md guidance for a repository or component. Use when the user wants to clarify what Codex Security should review, what is out of scope, which security properties must hold, or whether existing guidance still matches the code.
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。
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。
Read the input and ticket, choose the mode, run preflight, and check for existing delivery.
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。
Draft or refresh Omnigent package release notes for the next version using the existing GitHub Actions preview, merged PR material, and release-note composer. Use when preparing release highlights before a tag exists or reviewing a release-note draft; does not cut or publish a release.
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。
Review an existing fix PR using the audited repro and full diff, preserving branch and approval rules.
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 Resolve mode, recover its input, check the workspace, and discover existing fixes.
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。
Detect Python agent frameworks from code imports and map them to Omnigent executor types. Load when the user has existing agent code to integrate.
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。