Drive and script tldraw offline canvases with an agent.
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。
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概要と使いどころ
Drive and script tldraw offline canvases with an agent.
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。
Drive Blender via the catalog blender MCP, with bpy recipes.
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。
TDD: enforce RED-GREEN-REFACTOR, tests before 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。
Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.
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 driving two monitors on Windows with cua-driver.
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。
Drive the user's desktop in the background — clicking, typing, scrolling, dragging — without stealing the cursor, keyboard focus, or switching virtual desktops / Spaces. Cross-platform: macOS, Windows, Linux. Works with any tool-capable model. Load this skill whenever the `computer_use` tool is available.
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。
Artificial intelligence-driven transformative applications in disease ... — In cancer diagnostics, AI systems have achieved breakthrough performances
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 architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
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。
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.
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。
Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.
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 MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.
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 and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow.
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。
xUnit testing patterns and data-driven test guidance. Use when writing or reviewing .NET unit 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。
Spec-driven development lifecycle — EARS requirements, technical design docs, implementation tracking, and contribution guidelines. Use when planning features, defining requirements, or managing project lifecycle.
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。
Drive the Codex in-app browser (open, navigate, click, type, screenshot, read page state) through the app's own node_repl runtime. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to use the in-app browser, open or navigate a page in it, test a local app in a browser, or click, type, or take a screenshot in the Codex browser panel.
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。
DDD v3 — bounded contexts, aggregates, value objects, domain events, Ubiquitous Language, strategic design
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。
Elite IT Management Advisor specializing in data-driven strategy, executive communication, and human-centric leadership for the 2026 digital era.
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。
Measurement-driven model router for Claude Code. Routes Haiku/Sonnet/Opus per task class, logs every routed task with real $ numbers, and A/B tests cheaper tiers before you trust the savings.
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。
This is the core skill for the deep research and writing tool—combining AI-driven deep research with well-formatted written outputs. Every document produced is backed by comprehensive literature search and verified citations through the research-lookup 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。
Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.
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。
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration 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。
Alternative Slowbar coffee intelligence — scientific analysis from seed to cup using First Principle + System Thinking. Covers: varieties, terroir, cultivation, disease diagnosis, processing, roasting physics/chemistry, extraction science, brewing, business strategy, storytelling. ALWAYS trigger for coffee-related questions requiring scientific depth. DO NOT trigger for simple recipes or general food questions. Style: science-driven, farmer-first, quality-obsessed.
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。
Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.
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。