「xp」の検索結果

Use when lighting or rendering a PlayCanvas scene, covering lights, ambient and environment lighting, sky, shadows, tone mapping, exposure, fog, and post-processing.

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 a PlayCanvas StandardMaterial needs custom shading its properties cannot express, such as stylized looks or vertex displacement, before writing a ShaderMaterial.

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。

Agent-agnostic long-term project memory through `.memory-bank/` + RULES (TDD/SOLID/Clean Architecture/FSD/Mobile) + dev-toolkit commands. Use when working in a project with a `.memory-bank/` directory or when the user explicitly asks for memory-bank workflow, code rules, or dev-toolkit commands (`/mb`, plan, spec, verify, done; «память проекта», «контекст проекта», «план», «продолжай по плану»).

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 use AI agents to work with Penpot design files via the Penpot MCP Server. Triggers include: using Penpot through an AI agent, design files, design systems, design tokens, Penpot MCP, design-to-code, generating UI from design, auditing a design system, creating components/variants, renaming layers, exporting assets from Penpot, adding flows, interactions, animations, overlays, or prototyping in Penpot, or prompting an AI agent to read/modify a Penpot file. Also triggers when the user wants to set up Penpot MCP, connect any MCP-compatible AI agent or IDE to Penpot, or produce production-ready HTML/CSS/React from a Penpot design. Use this skill for Penpot-agent workflows — design, code, audit, prototyping, or setup.

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 when the user wants a Chinese adult-oriented turn-based text GalGame GM with harem formation, freeform narrative roleplay, natural-escalation yellow-fiction text adventure, multi-character relationship drama, story memory, or novel export. Trigger on requests for 后宫养成, 后宫, 养成, 多女主, 多男后宫, 黄色爽文, 自然流YY文字游戏, 成人向文字冒险, 回合制文字冒险, GalGame, 后宫互动, 逐步升温剧情, 暧昧开局, 自定义身份卡, 文档记忆, 小说导出, 女性向剧情, or any Chinese freeform narrative game where the user wants adult consenting characters, gradual escalation, strong character routes, and long-running continuity.

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。

DECIDE-phase doctrine for an Arbor research run: when to merge, prune, combine, or finalize; how the held-out merge gate works; and the rule that the final report uses TEST scores. Load before deciding what to do with completed experiments.

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。

Intake for an autonomous research run (Arbor). Use when the user wants to optimize a metric in a repo over many isolated experiments — 'optimize this benchmark', 'improve the model F1 overnight', 'beat the leaderboard'. Discovers the repo/eval/splits, measures the baseline, confirms a Research Contract, then emits a ready-to-send /auto-research command. Does NOT start the run itself.

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。

You MUST use this before any creative work — creating features, building components, drafting documents, designing workflows, or modifying behavior. Explores your human partner's intent, requirements, and design before any implementation begins.

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 at extremes (1000x bigger/smaller, instant/year-long) to expose fundamental truths hidden at normal scales

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。

Writing, exploit: shape raw material into an article, paragraph by paragraph.

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。

Writing, exploit; assemble raw material into a journey of beats, grounding each term before a beat leans on it.

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 encountering any bug, test failure, or unexpected behavior, before proposing 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。

Writing, explore: mine raw fragments, no structure yet.

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。

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before 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。

Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.

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 exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.

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 how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains.

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 a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

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 explicitly asks for a desktop or system screenshot (full screen, specific app or window, or a pixel region), or when tool-specific capture capabilities are unavailable and an OS-level capture is 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。

Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel

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。

Core knowledge for migrating integrations from other platforms (Boomi, Cyclr) to Prismatic Code Native Integrations. Provides the standard integration schema, schema-to-spec mapping, confidence scoring, and migration-aware code generation patterns. Use when the user says "migrate", "convert from Boomi/Cyclr", "parse this export".

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。

Delegate implementation (or, when explicitly requested, research) to GPT-6.1 Sol (high reasoning; xhigh on request) via Codex CLI. Claude plans, orchestrates, and reviews; Sol writes 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。

Expert prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reliability, efficiency, and measurable outcomes.

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。

Design agent system prompts with explicit behavior rules and cognitive control. This skill should be used when users need to define agent instructions, create intent-to-tool mappings, establish confirmation policies, or prevent hallucinated actions in AI agents.

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。