3,809 件 ・ 関連度順
概要と使いどころ
Produce a token-bounded, citation-ready context slice from an existing Obsidian vault for a downstream agent or task. Use for "/wiki-context-pack", "use my vault as context", "context slice for X", "pack the wiki for my agent", or "bounded context for Y".
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。
[omh] Context window or token budget at risk: plan compact context, token/cost budgets, summarization checkpoints, and overflow recovery before long agent work. Use when the user says: context-budget-review, context budget review, context budget, token budget review, token budget, prompt budget, prompt caching, prompt cache.
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。
Builds resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like lambda durable functions, durable execution, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, reliable serverless applications, context.step, context.wait, context.invoke, context.runInChildContext, withDurableExecution, DurableContext, UnrecoverableInvocationError, durable-execution-sdk, qualified ARN invocation, and durable handler replay.
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。
When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' or wants to avoid repeating foundational information across marketing tasks. Creates `.agents/product-marketing-context.md` that other marketing skills reference.
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。
Foundation skill that captures and stores core brand context — identity, audience, positioning, values, and voice. Use when the user says "set brand context", "save my brand info", "store brand details", "brand profile", "create brand context file", "update brand context", or when starting any brand project for the first time. Every other brand skill reads this file first. Always run this before beginning any brand work if the context file doesn't exist 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。
Dung khi bat dau lam viec voi mot san pham hoac khach hang moi — skill nay tao FILE CONTEXT ma hon 60 skill khac se doc, gom san pham, khach hang, dinh vi, proof, objection, brand voice va KPI. Chay mot lan, dung lai mai ve sau. Kich hoat khi user nhac 'tao context', 'setup product marketing context', 'bat dau du an moi', 'AI chua hieu san pham cua toi', 'khai bao thong tin san pham'. Khong dung cho — context cho thuong hieu CA NHAN thi dung skill 22-personal-brand-context; nghien cuu insight sau thi dung skill 09-insight-khach-hang.
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。
Dung khi bat dau xay thuong hieu CA NHAN cho mot con nguoi cu the — founder, coach, creator: skill nay tao file .agents/personal-brand-context.md gom dinh vi ca nhan, niche, story arc, content pillar, chan dung nguoi theo doi, brand voice, visual identity va kho anh reference. Chay MOT LAN truoc moi skill personal brand 23-28. Kich hoat khi user nhac 'thuong hieu ca nhan', 'personal brand', 'ho so ca nhan', 'founder context', 'coach context', 'creator context', 'muon xay hinh anh ca nhan', 'bat dau lam personal brand'. Khong dung cho — thuong hieu DOANH NGHIEP hoac san pham thi dung skill product-marketing-context; dinh vi cong ty tren thi truong thi dung skill 58-positioning.
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 starting work on a new product, client, or market — this skill creates the file `.agents/product-marketing-context-global.md` that 60+ other global skills read before they write anything: product, ICP, positioning, proof, objections, brand voice, pricing, and KPIs, with a region variant for US, EU, SEA, or LATAM. Run once, reuse forever. Trigger on 'set up marketing context', 'new client setup', 'onboard a new product', 'the AI does not know my product', 'US marketing context', 'EU GDPR setup', 'SEA market context', 'LATAM setup'. Also use when the user complains every answer comes back generic because nothing about the business was ever provided. Not for — a personal brand belonging to a founder, coach, or creator, see `22-personal-brand-context-global`; deep persona and JTBD research, see `09-customer-insight-global`; the period plan itself, see `00-marketing-plan-global`.
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。
Coder-agent working-file budget discipline: keep the editable working set (files you /add into writable context) under ~25k tokens, separate "read" from "edit", delegate breadth to a read-only repo-map, and drop files once edited. Use when an LLM coder-agent edits multiple files, when the working set must stay focused, or when the model starts editing the wrong file / missing targets because too much context dilutes attention. Search keywords: context window full, agent edits wrong file, too much context, /add /drop files, working file budget, context dilution, lost in the middle.
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。
Report how much of the session's context window remains. Use when the user asks "how much context is left", "check the context level", "how full is the context window", or "is context running low".
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。
Manage per-feature living documents that capture decisions, constraints, and reasoning across AI sessions during active development. Scoped to feature-level work — design, implementation, bugfix, refactor — not for codebase-wide assessments or product-wide specifications (those define their own document lifecycles). Handles creating new context documents, loading existing ones, and enriching them with new decisions. Use when starting a new feature, resuming work, making technical decisions, resolving questions, or when context needs to persist across sessions. Use this skill whenever the user mentions 'load context', 'update context', 'context doc', 'decisions', 'continue where we left off', 'what did we decide', or 'capture this decision'.
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。
Install a per-turn canary signal (e.g. starting every reply with the user's name and a turn counter) so silent context degradation becomes visible the moment it happens, and run a recovery protocol when the canary trips. Use when the user mentions a "canary", "context canary", or "canary check", asks to detect context rot / compaction / drift, says "you stopped using my name" or "did you lose context", asks "how degraded is your context", or wants an early-warning system for long agent sessions.
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。
Deep Context Builder Skill (Ultra-Granular Pure Context Mode) workflow skill. Use this skill when the user needs Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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-PLC Stage 1 Collection。GoalとModeからExecution Contextを確立し、Context Store、intent.yaml、context.yaml、backlog.yamlを生成する。
Specialized agentic and context engineering prompt methodology for Claude. Use when designing AI agents — system prompts, tool definitions, context window architectures, failure mode planning, multi-agent coordination, agent evaluation. Trigger on: "design an agent," "build a system prompt for an agent," "architect an agent's context," "design tool definitions," "agent system prompt," "context window architecture," "tool interface design," "evaluate agent behavior," "multi-agent coordination," "context engineering for agents," "ACI design." Provides 12 tested approaches for agent architecture (designing agents, not using them). Do NOT use for evaluating or scoring individual non-agent prompts (use rootnode-prompt-validation if available). Do NOT use for general software architecture that hosts agents (use standard technical reasoning for that).
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。
プロダクトの基盤情報（課題仮説・ソリューション・市場スコープ・原体験・ビジネスモデル・競合・差別化）を ユーザーとの対話で掘り下げ、構造化されたドキュメント（product-context.md）として整理するスキル。 「自分のプロダクトって結局何なの？」を一緒に整理する壁打ち相手として機能する。 ペルソナ作成、LP設計、機能優先順位、マーケティング戦略など、 プロダクトの方向性に関わるあらゆる意思決定の「前提情報」を1ファイルにまとめる。 コードベースがあれば自動で読み取れる部分は埋め、残りをユーザーにヒアリングする。 Use when: 「プロダクトを整理したい」「ターゲット整理」「コンテキスト作成」 「ペルソナの前に」「誰向けのプロダクトか整理」「プロダクト情報まとめ」 「product context」「プロダクト定義」「プロダクトの前提」 「product discovery」「誰向け」と言われた時。 新しいプロジェクトの立ち上げ時や、方向性を見直したい時にも使う。 ペルソナ作成スキルを使う前に、まずこのスキルでプロダクトの前提を整理すべき。 Triggers: "product discovery", "product context", "プロダクト整理", "ターゲット整理", "コンテキスト作成", "プロダクト定義", "プロダクトの前提", "ペルソナの前に", "誰向け", "プロダクト情報まとめ", "プロダクトって何", "何を作ってるか整理", "どんな需要があるか"
Compress any conversation into a portable JSON context graph for handoff to a new chat or LLM. Trigger on: "compress this chat", "save context", "new chat", "hand off", "transfer context", "too many tokens", "start fresh", "export conversation", "context graph", "continue in new session". Also trigger proactively when the user mentions starting over in a long session.
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 `.claude/` structural overhead. Reports prioritized "remove X save Y tokens" recommendations against the model context window. NOT for monetary cost tracking — that's /mk:budget. NOT for transcript size monitoring — long-session continuity defers to Claude Code native compaction. NOT for runtime context decisions (what to read, when to compact) — see mk:context-engineering. Use when planning to add context capacity, diagnosing perceived slowdowns, or auditing health.
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。
How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).
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。
Save durable decisions, findings, plans, and implementation knowledge from the visible pi conversation into a new or existing NeatContext context. Use only when the user explicitly asks to preserve the current conversation as reusable context, or runs /neatcontext-save.
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 a fresh NeatContext context from a user-defined behavioral profile and an existing local knowledge folder. Use only when the user explicitly asks to create a new context, or runs /neatcontext-create — not to save the current conversation.
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。
Export a NeatContext context saved from a conversation into a self-contained bundle folder that can be shared or moved to another machine. Use only when the user explicitly invokes this skill or asks to export a NeatContext context.
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。
Import a self-contained NeatContext context bundle shared by another person, or reconcile a newer copy of a context already on this machine, leaving the source bundle unchanged. Use only when the user explicitly invokes this skill or asks to import a NeatContext bundle.
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。
Estenda janelas de contexto de modelos transformer usando RoPE, YaRN, ALiBi e técnicas de interpolação de posição. Use ao processar documentos longos (32k-128k+ tokens), estender modelos pré-treinados além dos limites de contexto originais ou implementar codificações posicionais eficientes. Cobre embeddings rotativos, vieses de atenção, métodos de interpolação e estratégias de extrapolação para LLMs.
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。