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概要と使いどころ
Especialista em Langfuse - plataforma de observabilidade LLM de código aberto. Cobre rastreamento, gerenciamento de prompts, avaliação, datasets e integração com LangChain, LlamaIndex e OpenAI. Essencial para depuração, monitoramento e melhoria de aplicações LLM em produção. Use quando: langfuse, observabilidade llm, rastreamento llm, gerenciamento de prompts, avaliação llm.
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。
[Utilities] Use when the user invokes, lists, saves, updates, or deletes a PROJECT-SPECIFIC saved prompt — a named, reusable procedure stored with the project rather than in the portable framework. `/custom-prompt list` prints every defined prompt with its description; `/custom-prompt <free-text request>` matches the request to the closest saved prompt and executes it only after a confirmation gate; `/custom-prompt save|update|delete ...` maintains the registry — save never stores raw wording, it drafts the best version of the prompt and confirms the name, description, inferred goal, and steps with the user first. Triggers: custom prompt, custom prompts, list custom prompts, save this prompt, save this prompt task, update this prompt, my saved prompt, project prompt, playbook, recipe, runbook.
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。
Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.
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。
DEPRECATED: This skill has been replaced by `mcp-app-builder`. Check if `mcp-app-builder` is available in the skills folder. If not, install it: `npx skills install mcp-use/mcp-use --skill mcp-app-builder` Use `mcp-app-builder` instead of this skill. Build Model Context Protocol (MCP) servers with mcp-use framework. Use when creating MCP servers, defining tools/resources/prompts, working with mcp-use, bootstrapping MCP projects, or when user mentions MCP development, tools, resources, or 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。
Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)
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。
GitHub Issue群からClaude Code並列開発用の実行プロンプト集（docs/prompts/xxx.md）を自動生成するスキル。 「開発計画を作成して」「実行プロンプトを生成して」「dev-planを作って」「プロンプト集を作って」 「並列開発の計画を立てて」などのリクエストで発動。 Issue番号リストを受け取り、依存関係のWave構造を対話で決定し、 /gtr-workflow → 実装 → /e2e-test → /pull-request の一連の指示を各Issueごとに生成する。
Expert guide for crafting high-quality video prompts for Ozor.ai, the AI video generation platform. Use this skill whenever the user mentions Ozor, wants to create a launch video, product demo, feature announcement, explainer video, social ad, release notes video, investor update, tutorial, or any marketing video. Also trigger when the user asks for help writing video prompts, improving video output, structuring video scenes, choosing video formats, or wants best practices for AI video creation. Trigger on phrases like 'make a video', 'create a launch video', 'video for my product', 'Ozor prompt', 'video best practices', 'explainer video', 'product demo video', 'social clip', 'announcement video', or any request involving short-form video content for products and marketing.
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 Nano Banana Pro prompts for blog and YouTube thumbnail images. Use when user mentions "サムネイル作成", "サムネ", "YouTube用画像", or "ブログ画像".
Generates high-quality image prompts for AI image generators (Midjourney, DALL-E, Stable Diffusion). Use when user mentions "イラスト作成", "画像プロンプト", "プロンプト生成", or "画像生成".
Generates Nano Banana Pro prompts for profile icons and SNS images. Use when user mentions "プロフィール画像", "アイコン作成", "SNS用画像", or "ヘッダー画像".
Generates Nano Banana Pro prompts for original character designs. Use when user mentions "キャラクター作成", "キャラデザ", or "オリキャラ".
Generates Nano Banana Pro prompts for technical explanation infographics. Use when user mentions "図解作成", "テック図解", or "AI解説図".
Generates Nano Banana Pro prompts for 4-panel engineer humor comics. Use when user mentions "漫画作成", "エンジニア漫画", "4コマ", or "あるある".
Use after changing prompts, skills, the compiler, or editorial policies — or when the user asks to measure edit quality, run regression evals, check agreement with approved edits, or says '評価して', '一致率を測って', 'eval を回して'. Compares agent output against human-approved golden projects.
Write effective prompts for LLMs — structure, few-shot examples, chain-of-thought, system prompts, and output parsing.
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。
Claude API (platform.claude.com) のプロンプトエンジニアリング・評価リファレンス。 prompt engineering, XML タグ, few-shot, system prompts, モデル別プロンプティング（Fable 5 / Opus 5 / Sonnet 5）。 evals, grading（LLM-graded 等）, jailbreak・prompt leak 対策, hallucination 低減, classification, ticket routing 等ユースケース実装。
Design a self-improvement loop for a shipped product's AI agents — production traces feed evals, evals feed improvement proposals (prompts, playbooks, retrieval configs), and a human approval gate promotes changes with rollback. Technique-agnostic: chooses per project between ACE-style evolving playbooks, GEPA/MIPROv2 offline optimization, or simple eval-driven iteration via references/techniques.md. Load when the user asks to make my product's agents self-improving, learn from production traces, add a learning loop, evolve prompts or playbooks safely, promote agent improvements, or GEPA-style optimization. NOT harness-evolution (that improves the coding agent), NOT experimentation (product A/B tests), NOT agent-run-retro (dev-phase manual retros — this skill is the production-scale continuation).
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 AI art prompt engineer for Midjourney and Stable Diffusion. Generates high-quality prompts including unified batch illustrations, marketing designs, interactive compositions, and structured framework prompts with translations.
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。
INVOKE THIS SKILL when optimizing, improving, or debugging LLM prompts using production trace data, evaluations, and annotations. Covers extracting prompts from spans, gathering performance signal, and running a data-driven optimization loop using the ax CLI.
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, test, inspect, install, and deploy MCP servers with FastMCP in Python. Use when creating a new MCP server, wrapping an API or database as MCP tools, exposing resources or prompts, or preparing a FastMCP server for Claude Code, Cursor, or HTTP deployment.
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。
Skill for system-prompts tasks.
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。
Creates reusable prompt templates with strict output contracts, style rules, few-shot examples, and do/don't guidelines. Provides system/user prompt files, variable placeholders, output formatting instructions, and quality criteria. Use when building "prompt templates", "LLM prompts", "AI system prompts", or "prompt engineering".
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 building CLI tools, implementing argument parsing, or adding interactive prompts. Invoke for CLI design, argument parsing, interactive prompts, progress indicators, shell completions.
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。