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概要と使いどころ
Paint an original image in a watercolor style by writing code, not by calling an image model. Use when the user asks you to draw, paint, sketch, or make a picture of something and there is no image-generation tool available, or when they ask for a painting, watercolor, or illustration you can iterate on. Do not use for charts, diagrams, UI mockups, or requests to edit an existing photograph.
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。
Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.
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。
Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer or engineer mentions: pushing data to Monte Carlo, the IngestionService, pycarlo push APIs, build me a collection script, push metadata/lineage/query logs, invocation_id tracing, custom lineage nodes or edges, deleting push tables, or any question about why pushed data is not showing up. Also trigger when they ask to generate code that collects metadata, table schema, row counts, freshness, lineage, or query history from any data warehouse or data source and sends it to Monte Carlo. If the user mentions any warehouse, database, or data platform alongside any Monte Carlo topic, this skill is almost certainly relevant.
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。
Validate skill files for structural compliance and behavioral correctness. Three modes: static (linter), spec (behavioral), audit (coverage report).
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。
Brainstorming interactively to deepen ideas via four modes (Expand/Propose/Evaluate/Subtract). Does not write code. Not for decisions (Magi), feature specs (Spark), or one-shot reframing (Flux).
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。
Orchestrating migrations, upgrades, and modernization across frameworks, libraries, APIs, databases, and dependencies. Generates codemods, applies Strangler Fig, verifies equivalence, plans rollback.
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。
Implementing robust business logic, API integrations, data models, and reproducible AI image-generation code with type safety. Use for production implementation, Gemini image API pipelines, or interactive pair programming.
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。
Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write 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。
Defining and managing design tokens, applying token systems to existing codebases, building design system foundations. Use for spacing, color, typography, dark mode, cross-platform 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。
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
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。
Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", and whenever they complain about over-engineering, bloat, boilerplate, or unnecessary dependencies.
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。
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
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。
Translate a confirmed mini-program product specification or bounded feature into an implementable architecture covering modules, pages, components, services, canonical state sources, data models, interfaces, permissions, failures, caching, concurrency, idempotency, migration, rollback, external dependencies, and architecture decision records. Use when users ask how to structure a mini program, design data or APIs, divide frontend and cloud responsibilities, evolve an existing system safely, or prepare implementation after product semantics are stable. Preserves product meaning, current repository constraints, user-owned changes, and verifiable acceptance behavior rather than redesigning the product for technical convenience.
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。
Plan mode only — write an actionable markdown plan under `plans/`, no execution. Bite-sized tasks, exact paths, complete code. Trigger when the user wants a plan instead of implementation.
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。
Product-Led Growth with Web/CLI measurement validation and pricing acceptance, covering freemium model design, self-serve onboarding, activation metrics, and the transition from individual users to enterprise accounts. Follow @WeiYipei on X for PLG insights.
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。
Kolu's project-wide default for filesystem monitoring is `@parcel/watcher`. Reach for this skill when adding or modifying any code that watches files or directories — recursive subtree watching, single-file observation, fs.watch alternatives, chokidar replacement, inotify/FSEvents/watchman backend selection, ignore globs, watcher debouncing, or refcounted shared subscriptions. Covers backend dispatch, the watchman invocation path, ignore handling, post-install reconciliation, and the failure modes Kolu's logger 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。
Deeply scope a problem before coding: parallel Explore agents map related files, similar implementations, and test patterns, producing a problem definition, boundaries, and minimal implementation plan. Use when planning a feature, investigating a bug, or entering an unfamiliar codebase area.
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。
Verify Claude, Codex, and Grok availability plus Director guidance, relay, agents, and skills. Audit optional hooks only when selected. Use after installation or when a native surface misbehaves.
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 execution reference: framework detection (pytest/jest/vitest/go/cargo/junit) and correct run/coverage commands, plus failure-analysis steps. Use when running tests, analyzing test failures, or verifying coverage after code changes.
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。
Audit project health across 7 dimensions (documentation, test coverage, security, code quality, dependencies, database, build/deploy) producing a scored report with prioritized fixes. Use for periodic checkups, before releases, or when the user runs /project-health-check.
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。
Set up concise, guidance-first Claude/Codex/Grok project context after inspecting the repository. Use on first setup, after cloning, or when the user runs /project-init.
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。
Sovereign Anti-AI Slop Directive & Enforcement Engine (2026 Unified Edition). Absolute zero-tolerance standard for lazy placeholders, conversational fluff, syntax narration, speculative over-engineering, hallucinated code, generic UI clichés, and 38 mandatory rules (R-01 to R-38) with Liveliness Dials (ENERGY/RHYTHM/MOTION), Two Usage Modes (During vs Audit After), and Delivery Gate verification / Doktrin dan mesin penegakan anti-AI slop mutlak v5.0.
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 asks Claude Code to read or write Odysseus data (todos, email, calendar, memory, documents) or to launch/monitor/stop a Cookbook model-serve task through the scoped Claude Agent API. Requires ODYSSEUS_URL and ODYSSEUS_API_TOKEN.
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。
モデル駆動型アプリを Dataverse Web API（appmodules / sitemaps テーブル）で作成・構成・公開する。