7,253 件 ・ 関連度順
概要と使いどころ
Explains test failures and provides actionable debugging guidance. Use when tests fail (unit, integration, E2E), builds fail, or code throws errors. Analyzes error messages, stack traces, and test output to identify root causes and suggest concrete fixes. Handles pytest, jest, junit, mocha, vitest, selenium, cypress, playwright, and other testing frameworks across Python, JavaScript/TypeScript, Java, Go, and other languages.
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。
Selectively instruments code to capture runtime data for debugging failures and bugs. Use when investigating crashes, exceptions, unexpected behavior, test failures, or performance issues. Analyzes stack traces and error messages to identify suspicious code regions, then adds targeted logging, tracing, and assertions to capture variable values, execution paths, timing, and conditional branches. Supports Python, JavaScript/TypeScript, Java, and C/C++.
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。
Optimize test suites using mutation testing to maximize mutation kill rate with minimal tests. Use when you need to reduce test suite size while maintaining quality, identify redundant tests, improve mutation coverage, or validate test effectiveness. The skill analyzes test coverage, execution intervals, and redundancy using mutation operators, selects or generates a minimal subset of tests that maximizes mutation kill rate, and outputs an optimized test suite with detailed reports showing killed and surviving mutants. Supports multiple programming languages and mutation testing frameworks.
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 vague or partially formed AI, computer-science, data-driven, and engineering-method research directions into evidence-grounded, falsifiable, paper-ready Research Idea Briefs through heuristic questioning, staged confirmation, literature positioning, novelty attack, and method-figure planning. Use when the user needs to clarify a research idea, formalize inputs/outputs/objectives/constraints, frame background and motivation, select 3-5 anchor papers, identify a defensible gap, derive 2-3 contributions, stress-test novelty, or design an input-to-output method framework and core-paper figure. Also trigger on requests such as 明确科研 idea、启发式梳理 idea、互动追问科研问题、梳理论文创新点、定义研究任务、找对标论文、把研究方向变成论文方案、画方法框架图. Do not use as the primary workflow for running experiments, exhaustive systematic reviews, drafting full manuscript sections, or polishing finished prose.
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。
Add, inspect, repair, or validate CodeDrobe Core adapters for Chromium/Electron AI desktop applications. Use when supporting a new app, updating Codex or WorkBuddy compatibility after an app release, discovering installation paths or CDP targets, selecting stable DOM landmarks, adding renderer profiles or transactional host settings, recording lastVerified versions, or writing adapter and real-renderer tests.
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 charts: select type, extract data, render 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。
Streams change data capture from PostgreSQL into Redpanda or Kafka using Redpanda Connect's postgres_cdc input, which reads the WAL through logical replication (pgoutput). Use when configuring postgres_cdc (formerly pg_stream), setting up wal_level=logical, replication slots, and publications, enabling an initial snapshot before streaming, or troubleshooting slot growth and WAL accumulation. Also covers Redpanda Enterprise destination features such as Iceberg Topics, Tiered Storage, and server-side Schema ID Validation, since postgres_cdc itself requires a Redpanda Enterprise license.
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 wants to automate capture of marketing screenshots for a SwiftUI iOS app across multiple locales, devices, or appearances. Covers full-screen shots, isolated element renders (carousel cards, widgets), and reproducible output naming. Triggers on marketing screenshots, locale screenshots, widget renders, App Store assets, fastlane-alternative, simctl screenshots.
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 Guizang-style social card image sets, Live Photo motion cards, material-first Live Photo puzzle layouts, triple Live Photo collages, long-video-to-Live-Photo treatments, and WeChat official account cover pairs from articles, scripts, screenshots, product notes, subtitles, photos, or user-supplied videos. Use when the user asks for 小红书图文, Rednote/Xiaohongshu images, social cards, carousel images, 3:4 covers, Live Photo, 实况照片, 单视频实况拼图, 二宫格实况拼图, 三连实况拼图, 四宫格实况拼图, 微信公众号封面, WeChat 21:9 + 1:1 covers, Swiss Style, or magazine-style social images.
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。
Miro presents itself as the AI-powered visual workspace through a confident, almost playful brand voice — anchored by its signature canary yellow ({colors.brand-yellow}) wordmark over white canvas, broken open by colorful pastel feature tints (rose, teal, coral, orange, mint) that echo the actual sticky-note color palette used on the live whiteboard. Black-pill primary buttons dominate marketing, real Miro-board mockups serve as feature illustrations, and a 4-tier pricing grid leads into a dense comparison table. Roobert PRO carries display headlines; the system supports homepage, pricing, AI Workflows product page, agile vertical, and customer stories surfaces.
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 asks for an HTML-first visual design deliverable or design judgment: interactive prototype, slide deck, motion demo, infographic, dashboard, landing page, whitepaper, changelog, business card, social cover, brand system, design critique, multi-variant exploration, or export to MP4, GIF, PPTX, PDF, or SVG. It is optimized to make AI agents do the routing, template selection, verification, and export prep so humans spend less time prompt-engineering. Do not use for production web apps, SEO sites, backend systems, or pure copy edits.
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 or improve a presentation for an academic context — conference papers, seminar talks, thesis defenses, grant briefings, lab meetings, invited lectures, or any presentation where the audience will evaluate reasoning and evidence. Triggers include: 'conference talk', 'seminar slides', 'thesis defense', 'research presentation', 'academic deck', 'academic presentation'. Also triggers when the user asks to 'make slides' in combination with academic content (e.g., 'make slides for my paper on X', 'create a presentation for my dissertation defense', 'build a deck for my grant proposal'). This skill governs CONTENT and STRUCTURE decisions. For the technical work of creating or editing the .pptx file itself, also read the pptx SKILL.md.
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。
Redpanda's Agentic Data Plane: governance infrastructure for building, running, and governing AI agents and MCP servers, plus a proxying AI Gateway for LLM providers, operated via `rpk ai` and the ADP API. Use when creating or managing AI agents (managed or self-managed) via `rpk ai agent` or `AgentRegistryService`; configuring MCP servers (remote or managed catalog, code mode, auth); setting up LLM providers or querying models via `rpk ai llm`/`rpk ai model` or the AI Gateway proxy; or configuring budgets, guardrails, or Cedar access-control policies through the governance APIs. Also covers reading agent transcripts and spending insights, and wiring OAuth clients or providers to the aigw Authorization Server. For the separate rpk cloud mcp control-plane MCP server, see `/redpanda:rpk-cloud`.
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。
GitLab CLI for managing issues, merge requests, CI/CD pipelines, and repositories. Use when: (1) Creating, reviewing, or merging MRs, (2) Managing GitLab issues, (3) Monitoring or triggering CI/CD pipelines, (4) Working with self-hosted GitLab instances, (5) Automating GitLab workflows from the command line. Requires GITLAB_TOKEN (recommend minimal scopes). The `glab api` command enables arbitrary API calls - use read-only tokens when possible.
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。
Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.
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 a step-by-step construction plan from a one-line objective, where each step is self-contained and executable by a fresh agent in a new session.
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。
Trigger this skill when building applications with Gemma or for general knowledge inquiries related to Gemma models (e.g. prompt structure, capabilities). Covers model selection, development workflows, and deployment best practices.
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。
Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
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。
MiniMax presents itself as a premium AI infrastructure brand through a striking duality — bold black-pill CTAs and stark white canvas for marketing, paired with vibrant gradient product cards (orange-red, magenta-pink, purple, blue) that turn each model release into a distinctive visual identity. The system uses DM Sans across all surfaces, employs an oversized 80px hero display, anchors major actions in deep near-black pills, and layers content density via a 3-column documentation grid with sidebar nav, prose body, and TOC. Coverage spans the marketing homepage, model showcase pages, developer documentation, and platform pricing surfaces.
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。
Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines
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。
Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.
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。
Ultracite multi-provider linting/formatting (Biome, ESLint, Oxlint). Use for v6/v7 setup, provider selection, Git hooks, MCP integration, AI hooks, migrations, or encountering configuration, type-aware linting, monorepo errors.
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。
Designs effective KPI dashboards with proper metric selection, visual hierarchy, and data visualization best practices. Use when building executive dashboards, creating analytics views, or presenting business metrics.
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。