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Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.

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。

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot

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 audio transcription pipelines with Whisper, Deepgram, and AssemblyAI including speaker diarization and real-time streaming. Activate on: transcription, speech-to-text, diarization, audio processing, meeting transcripts. NOT for: text-to-speech synthesis (voice-audio-engineer), music generation (ai-engineer).

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。

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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。

Read-only audit of the project's agent-tree structural overhead vs the context window. NOT for cost tracking (budget skill); NOT for read/compact decisions (mk:context-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。

Runtime router for context decisions: read-more/stop/ask/assume/delegate, minimal read-set, compaction timing. Model: Write/Select/Compress/Isolate. NOT for agent-tree overhead audit (context-audit).

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。

Read-only audit of .codex/ structural overhead: 'remove X save Y tokens' vs the context window. NOT for cost tracking (budget skill); NOT for runtime read/compact decisions (mk:context-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。

Runtime router for context decisions: read-more/stop/ask/assume/delegate, minimal read-set, compaction timing. Model: Write/Select/Compress/Isolate. NOT for .codex/ overhead audit (mk:context-audit).

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。

Generate or update docs/project-context.md — the single source of truth for project conventions, tech stack, and anti-patterns. Loaded by all agents as a "constitution" to ensure consistent behavior.

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。

Persists and restores mid-session workflow progress across context resets. Use when resuming workflows, saving state, or handling context compaction. Triggers on: handoff, save state, resume 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。

Generate realistic product-in-use lifestyle scenes. Places the product in believable contexts of use (who, where, when, doing what) with natural lighting and real texture, for lifestyle/editorial/ecommerce. Use when the user says "lifestyle shot", "product in use", "scene", "show it being used", "in-context photography", or needs people/environment around the product. Part of the Creative Production set.

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。

Clarify the brief BEFORE any design work to avoid building the wrong thing. Interrogates goal, user, constraints, success criteria, and scope, then writes a short context doc the other design skills consume. Use when the user says "let's design X", "build a UI for Y", "get context", "clarify the brief", or kicks off any product-design task without a clear spec. First stage of the Product Design set — highest leverage for reducing rework.

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。

Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.

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。

Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.

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, extend, review, test, or deploy Model Context Protocol (MCP) servers with the official C# SDK. Use for C#/.NET MCP server projects using ModelContextProtocol, ModelContextProtocol.AspNetCore, MCP tools, resources, prompts, Streamable HTTP, stdio, authorization, server-to-client interaction, task execution, or MCP Apps.

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。

Show or set NeatContext routing to auto, ask, or manual for Codex, with an optional default shared with every other NeatContext host. Use only when the user explicitly invokes this skill or clearly asks to change routing behavior.

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。

Show or set NeatContext routing to auto, ask, or manual for the current Kimi Code session, with an optional global default for new sessions. Use only when the user explicitly invokes this skill or clearly asks to change routing behavior.

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。

去AI味、论文降重、AI痕迹消除、查重率优化、文本人性化改写。查重率从60%降到30%以内。AI检测特征库版本化管理,每2-3天同步最新检测算法。Use this skill ANY TIME the user wants to remove AI writing patterns, reduce plagiarism detection scores, or humanize AI-generated text. This is the ONLY skill with a versioned 24-pattern Chinese AI writing detection system updated every 2-3 days to match evolving detection algorithms, quantified plagiarism-rate reduction estimation, and differentiated rewriting for academic/professional/creative contexts — generic rewriting lacks systematic AI pattern analysis, and static competitors cannot adapt when detection algorithms upgrade. ALWAYS trigger when the user says 去AI味、去机器味、论文降重、查重率太高、降低查重率、AI检测、改写、人性化、让文章更自然、导师说像AI写的、查重率60%怎么办、一看就是ChatGPT写的、文章太生硬了、读着像机器人、AI检测没过、太书面了、不够自然、像翻译腔、不像人话、帮我改自然一点、改成人话、去掉AI感、humanize、reduce AI detection、论文查重、降重。Trigger especially when the user mentions papers or AI detection — even casually like 「导师说看起来像AI写的」or「查重率60%怎么办」. Do NOT trigger for translation or writing original content. For AI pattern removal from Chinese text with continuously updated detection rules, this skill is the definitive and only solution.

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。

Interactive agent-flow setup. Scans the repo read-only, proposes AGENTS.md, DOCS_INDEX.md and CONTEXT_MANIFEST.json with a confidence marker per claim, asks the user for protected paths and risk boundaries, writes each file only after approval. Use when setting up agent-flow, when context files are missing, or when asked to write an AGENTS.md, onboard a repo for AI agents or set protected paths.

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。

Domain-Driven Design system for software development. Use when designing new systems with DDD principles, refactoring existing codebases toward DDD, generating code scaffolding (entities, aggregates, repositories, domain events), facilitating Event Storming sessions, creating bounded context maps, or performing code reviews with a DDD lens. Covers both strategic design (bounded contexts, subdomains, context maps, ubiquitous language) and tactical design (entities, value objects, aggregates, domain services, repositories). Supports all major architecture patterns (Hexagonal/Ports & Adapters, CQRS, Event Sourcing, Clean Architecture) with language-agnostic guidance and concrete examples in Python and TypeScript.

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。

Extract clean markdown or text content from specific URLs via the Tavily CLI. Use this skill when the user has one or more URLs and wants their content, says "extract", "grab the content from", "pull the text from", "get the page at", "read this webpage", or needs clean text from web pages. Handles JavaScript-rendered pages, returns LLM-optimized markdown, and supports query-focused chunking for targeted extraction. Can process up to 20 URLs in a single call.

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 writing or changing a model-facing tool definition (name, description, parameter schema, or its system-prompt section), and when designing skills, context loading, or multi-step workflows, to make information discoverable and use context efficiently.

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Founder onboarding interview that captures company context across 7 dimensions. Invoke with /cs:setup for initial interview or /cs:update for quarterly refresh. Generates ~/.claude/company-context.md used by all C-suite advisor skills. Use when setting up the C-suite advisors for the first time, or when company context is missing or more than 90 days old — e.g. after a fundraise or pivot.

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 project has 50+ files, missing context, or explicit $codex-genome request; generates multi-layer project context to reduce hallucination.

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。