「knowledge」の検索結果

Purge the context-mode knowledge base. Permanently deletes all indexed content and resets session stats. This is destructive and cannot be undone. Trigger: /context-mode:ctx-purge

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。

Index a local file or directory into context-mode's persistent FTS5 knowledge base so future ctx_search calls can retrieve focused snippets without rereading raw files. Trigger: /context-mode:ctx-index

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。

Search context-mode's persistent FTS5 knowledge base for previously indexed local project content, documentation, or session memory. Trigger: /context-mode:ctx-search

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 how much context window context-mode saved this session. Displays token consumption, context savings ratio, and per-tool breakdown. Read-only — shows stats only, no reset capability. To wipe the knowledge base entirely, use ctx_purge instead. Trigger: /context-mode:ctx-stats

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 an insight, decision, or learning to agentmemory's long-term storage with searchable concept tags. Use when the user says "remember this", "save this", "note that", "don't forget", or wants to preserve knowledge for future 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。

Analyze indexed codebases via graph database (neug) and vector index (zvec). Covers call graphs, dependencies, dead code, hotspots, module coupling, architecture reports, semantic search, impact analysis, bug root cause from GitHub issues, class diagrams (UML), and PR review (risk scoring, conflict detection, auto-merge candidates, labeling). Also covers creating, inspecting, and repairing a CodeScope index. Use for: code structure, who calls what, why something changed, similar functions, module boundaries, bug tracing, class relationships, PR risk/conflicts, or any question benefiting from a code knowledge graph. Applies when a `.codegraph` index exists in the workspace, or when the user wants to create one.

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。

Explicitly save important knowledge to auto-memory with timestamp and context. Use when a discovery is too important to rely on auto-capture.

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。

Board meeting preparation for the adversarial scenario, not the friendly one. Forces numbers-cold mastery, anticipates hard questions, builds a narrative that acknowledges weakness without losing the room. Use when preparing for a board meeting, an investor update, fundraising presentation, or any high-stakes adversarial review where every number must live in your head not just on a slide.

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 running, diagnosing, or designing internal business operations — process documentation, vendor SLAs, capacity planning, internal comms, SOP/runbook authoring, procurement spend. Triggers on "BizOps review", "where's the bottleneck", "vendor health", "internal SOP", "all-hands deck", "spend categorization", "capacity for Q3", "process mapping". Forks context to route to one of six BizOps sub-skills (process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizer) and returns a digest. Distinct from business-growth (external sales motion) and c-level-advisor (strategic, not operational).

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 to deeply read a book, article, PDF, or document set; extract claims and evidence; build a knowledge map; or learn through Feynman explanation and recall. Covers quick, deep, map, Feynman, and whole-book reading modes.

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, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict 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。

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.

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。

Capture conversations and decisions into structured Notion pages; use when turning chats/notes into wiki entries, how-tos, decisions, or FAQs with proper linking.

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。

Knowledge comic creator supporting multiple art styles and tones. Creates original educational comics with detailed panel layouts and batch-capable image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".

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。

Author the architecture blueprint before code is written. Validates decisions against the pinned engine, flags knowledge gaps.

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。

Sweep configured feedback sources (Slack, GitHub Issues; email experimental) for new items: acknowledge at source, analyze recordings, verify fixes merged to main, and emit an `lfg`-ready plan. First run sets up sources; supports mode:non-interactive for scheduled runs.

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, editing, validating, testing, or debugging an n8n workflow through the n8n-mcp MCP server — designing a flow, configuring a node, writing an expression or Code node, wiring credentials, or fixing one that misbehaves. The entry-point skill for the n8n-mcp-skills pack: it routes you to the right specialist skill, gives working knowledge of every n8n-mcp tool from turn one, and states the rules that keep workflows from breaking in production. Always consult it first on any n8n, workflow, node, or automation task — even a quick one-off, and even when the user names no skill — because n8n's surface drifts between versions and the specialist skills prevent silent failures.

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。

Query the pre-built code-review-graph knowledge graph (Tree-sitter, whole monorepo) instead of walking call chains with Grep+Read – 2-6x cheaper, and it catches dynamic dispatch that grep misses. Use for ANY task that spans multiple files, even when the user never mentions a graph or asks for it - fixing or tracing a bug ("fix this bug", "why does X happen", "trace this"), exploring unfamiliar code ("how does X work", "who calls X", "what imports Y", "where is X used or handled"), planning or doing a refactor ("rename X", "is it safe to change or remove X", "what would break", "blast radius", "find dead code"), or reviewing changes ("review this PR", "review this branch or diff"). When you are about to Grep for a symbol's callers, callees, or importers, use this skill.

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。

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

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。

Fresh-session security questionnaire response for {{projectName}}. Parses a new inbound questionnaire from {{questionnaire_label}} in Gmail, matches each question to our vetted knowledge base of approved answers and policies, drafts responses in the vendor's own format (SIG, CAIQ, or a custom spreadsheet), flags anything it can't answer confidently, and posts the completed draft to {{security_channel}} — holding it for security to review before it goes back to the prospect.

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 web research with mandatory URL verification, confidence-tagged output, and four depth modes (quick to deep investigation). USE WHEN research, do research, quick research, extensive research, deep investigation, find information, investigate, extract alpha, analyze content, retrieve content, AI trends, enhance content, extract knowledge, web scraping, YouTube extraction, map landscape, competitive analysis, find it, find this, find this product, identify this, what is this, what's that thing, track down, locate, help me find, I can't find X online, can't find it online, source this — never substitute raw WebSearch/WebFetch for a multi-source find/identify/investigate request. NOT FOR people/company/entity deep background, academic papers (use ArXiv), JSON entity extraction, or content-adaptive wisdom extraction (use ExtractWisdom).

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 the public daemon profile — a digital representation of what you're working on. DaemonAggregator reads LifeOS sources (TELOS, KNOWLEDGE, PROJECTS, MEMORY/WORK, identity) → daemon-data.json. SecurityFilter strips names/paths/credentials via deterministic patterns (NOT LLM). Workflows: UpdateDaemon, ReadDaemon, PreviewDaemon, DeployDaemon. USE WHEN daemon, update daemon, daemon profile, deploy daemon, preview daemon, read daemon, public profile, digital presence. NOT FOR LifeOS system management.

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。

FLOW framework integration: evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO 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。

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

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。