「prompt」の検索結果

Silently restructures the user's natural-language prompt into the format the model CURRENTLY running this skill handles best, then answers. On activation it identifies which model family is executing it (Claude, GPT, Gemini, Llama, DeepSeek, Mistral, Qwen, Grok, Perplexity, Kimi, GLM, Command, Nova, or Phi) and loads that one model's official strategy — so the optimization always matches the model that actually runs it. Activate with /prompt-refine. Use when users want better answers without learning prompt engineering.

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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。

Create well-structured prompts for AI agents using proven architecture patterns. Use when users ask to write agent prompts, system prompts, or agent instructions, or want to improve existing prompts that aren't working.

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。

Transforms vague UI/feature requests into structured, optimized prompts with design system awareness. Use when generating prompts for UI implementation, feature specification, or design-to-code translation. Triggers on tasks requiring prompt refinement, UI specification, or design system integration.

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Guides selection of identity, reasoning, and output approaches for Claude prompts based on task characteristics. Trigger on: "help me choose an approach," "which approach fits this task," "recommend a prompt pattern," "compare reasoning methods," "map this task to the right approach," "what combination of approaches," "which identity fits," "which reasoning method." Also trigger on symptom-phrased: "my prompt feels generic," "I don't know which approach to use," "my output lacks domain depth." Covers decision-tree logic across 8 identity approaches, 18 reasoning variants, and 10 output formats. After selection, use the relevant catalog skill if available to retrieve full templates. Activate whenever approach-selection across multiple categories is the primary decision. Do NOT use when the user already names a specific approach to retrieve (use the relevant catalog skill directly if available) or for evaluating existing prompts (use rootnode-prompt-validation if 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。

Diagnoses and fixes Claude behavioral issues in system prompts and Projects using tested countermeasure templates. Use when "Claude is too verbose," "keeps hedging," "agrees with everything," "claims it did something it didn't," "won't use a tool," "fix Claude's output," "tune Claude's behavior," "Claude ignores my preferences," "adds unsolicited disclaimers," "uses too many lists." Covers ten tendencies: agreeableness (output-content + persistent-preference), hedging, verbosity, list overuse, fabricated precision, over-exploration, tool miscalibration (over- and under-triggering), LaTeX defaulting, editorial drift, self-referential fabrication. Also use when auditing a system prompt for behavioral calibration or recalibrating a pre-4.7 prompt, and when users describe recurring output problems without naming a tendency. Do NOT use for scoring a prompt's overall quality — use rootnode-prompt-validation if 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。

Tested reasoning approaches for Claude prompts — 18 variants across 6 categories (Analytical, Strategic, Creative, Technical, Research, Comparative). Use when the user wants a specific reasoning template — retrieving, reviewing, customizing, or combining reasoning instructions for a prompt. Trigger on: "give me the Root Cause Diagnosis approach," "show me the reasoning template for," "I need the Evidence Synthesis method," "show me analytical reasoning options," "combine reasoning approaches for," "show me all reasoning variants." Also use when a prompt produces shallow output and the fix is a reasoning upgrade. Provides 18 tested approaches for analytical, strategic, creative, technical, research, and comparison tasks. If the user is unsure which reasoning method fits, use rootnode-block-selection first if available. Do NOT use for evaluating existing prompts — use rootnode-prompt-validation if available. Do NOT use for project-level audits — use rootnode-project-audit if 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。

Director-level AI art prompt creation for Eastern beauty series, including Eastern fantasy / gu feng Chinese beauty character art, classical Eastern beauty, realistic and modern Eastern beauty, Cosplay展会摄影 / official convention cosplay photography with AAA game character campaign and Vogue editorial quality, 古风闺蜜 / AncientFemaleCompanionship two-person ancient Chinese female companionship photography, 东方美学图鉴 / 小红书图鉴 cover and content systems for 四大美人、四大才女、十二花神、东方神女、敦煌飞天、朝代服饰、东方器物、东方神话, 甜系纯欲生活写真 / SweetHomeGirl lifestyle portraits built around realism, feminine charm, romantic feeling, story moment, and natural attraction, new-Chinese-style fashion editorials, magazine portraits, worldbuilding, mythic role design, costume/styling systems, cinematic composition, lighting, negative prompts, and model-specific prompt variants. Use when the user asks for 东方美人, 东方审美, 东方美学图鉴, 小红书图鉴, 图鉴封面, 图鉴正文, 四大美人, 四大才女, 十二花神, 东方神女, 敦煌飞天, 朝代服饰, 东方器物, 东方神话, Cosplay展会摄影, coser, Coser, 漫展摄影, 展会摄影, ChinaJoy, Bilibili World, Tokyo Game Show, 游戏展台, 官方展会摄影, AAA游戏角色Cosplay, 古风闺蜜, AncientFemaleCompanionship, Ancient Female Companionship, 闺阁夜话, 姐妹古风写真, 古代闺阁生活, 灯下梳发, 共读, 夏夜纳凉, 守夜, 江南同行, 湖亭共伞, 山寺同行, 灯会夜游, 柔美, 妩媚, 成熟, 优雅, 高贵, 清冷, 温婉, 英气, 神性, 慵懒, 东方幻想, 古风美女, 古典东方美人, 宋韵, 唐宫, 江南, 洛神, 青瓷, 昆曲, 国风人物, 汉服女子, 写实东方美人, 现代东方审美, 新中式, 东方高级感, SweetHomeGirl, 甜系纯欲生活写真, 甜系纯欲, 甜美女友感, 真实女生, 自然抓拍, 故事感, 女友视角, lifestyle girlfriend portrait, 仙侠/武侠/宫廷/江南/敦煌风 AI 绘画提示词, image prompt optimization, style word expansion, character series concepts, or prompt packs for Midjourney, Stable Diffusion, ComfyUI, DALL-E, Gemini, Seedream, or other image generation tools.

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 well-structured prompts for AI agents using proven architecture patterns. Use when users ask to write agent prompts, system prompts, or agent instructions, or want to improve existing prompts that aren't working.

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。

Systematically extract hidden system prompts, core directives, and invisible context intentionally concealed within Large Language Model (LLM) applications. This skill utilizes targeted linguistic engineering and boundary manipulation to bypass prompt opacity.

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。

Transform vague inputs into precision-optimized AI prompts for Claude, ChatGPT, Gemini, or other LLMs. Use when user mentions "optimize prompt", "improve prompt", "lyra", "prompt engineering", or needs help crafting effective AI prompts.

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。

Adapt and convert AI prompts between different models and platforms. Translates between Midjourney, Flux, Leonardo AI, DALL-E, Sora, Imagen, Stable Diffusion, Adobe Firefly, Ideogram, and more. Handles syntax differences, parameter mapping, and model-specific optimizations. Use when user says "adapt prompt", "convert prompt", "translate prompt", "port to flux", "midjourney to dall-e", or "change model".

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System Prompt 工程 — 基於 Claude Code 914 行系統提示詞的逆向分析。Use when: 撰寫 system prompt、設計 prompt 動態組裝、最佳化 prompt cache 效率、撰寫安全指令。

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。

GEODE prompt-writing standards. Use when creating or editing runtime prompts, system prompts, tool/developer instructions, model-facing identity text, prompt templates, or scaffold rules that affect model behavior; especially when avoiding identity assertions such as "You are ...".

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Explicit-only local skill. Invoke with $nsfw-prompt. Compile adult NSFW image prompts for online generators (Grok Imagine first) and local stacks (Flux, Pony, Illustrious, SDXL, Z-Image); Chinese briefing, English prompts.

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Use when designing production-LLM prompts — few-shot, chain-of-thought, system prompts, templates, self-verification — distinct from prompt-optimizer and refine-prompt.

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。

Estratégias de cache para prompts de LLM incluindo cache de prompt da Anthropic, cache de resposta e CAG (Cache Augmented Generation) Use quando: prompt caching, cache prompt, response cache, cag, cache augmented.

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。

Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation) Use when: prompt caching, cache prompt, response cache, cag, cache augmented.

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 向けテキスト指示（skill / slash command / task プロンプト / コード生成プロンプト）を、バイアスを排した実行者に動かしてもらい、両面（実行者の自己申告 + 指示側メトリクス）で評価して反復改善する手法。改善が頭打ちになるまで回す。Use when user says 'プロンプトを改善して', 'スキルをチューニング', 'empirical-prompt-tuning', or after creating/heavily revising a skill or prompt.

Expert prompt engineer specializing in advanced prompting techniques, LLM optimization, and AI system design. Masters chain-of-thought, constitutional AI, and production prompt strategies. Use when building AI features, improving agent performance, or crafting system prompts.

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。

Compares old vs new prompts across test cases with diff summaries, stability metrics, breakage analysis, and fix suggestions. Use for "prompt testing", "A/B testing prompts", "prompt versioning", or "quality regression".

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。

Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.

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。

Wires Promptfoo and DeepTeam into CI/CD for automated, repeatable red-teaming of LLM apps against OWASP LLM Top 10, OWASP Agentic, and MITRE ATLAS presets, failing the build when jailbreak or injection vulnerabilities regress. Use for continuous adversarial testing in CI/CD, a merge-blocking security gate, or comparing model/prompt versions for compliance reporting.

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。