628 件 ・ 関連度順
概要と使いどころ
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
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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。
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.
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Operate a LangBot instance through its built-in MCP (Model Context Protocol) server. Use when an AI agent needs to manage LangBot — list/create/update/delete bots, agents, pipelines, models, knowledge bases, MCP servers, and skills — over MCP instead of raw HTTP. Covers the /mcp endpoint, API-key auth (web-UI lbk_ keys and the config.yaml global key), the tool surface, and client configuration. Triggers on "langbot mcp", "manage langbot via mcp", "langbot /mcp", "langbot mcp server".
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。
Test LangBot WebUI and core product flows with an automated browser and backend logs. Use when validating the configured LangBot frontend, pipeline Debug Chat, model provider setup and test buttons, bot and knowledge-base UI flows, or troubleshooting failed LangBot end-to-end tests.
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。
Master index for the web3 smart contract security knowledge base. Use this to navigate the skill chain. Read files in order — each ends with NEXT.
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。
Persistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships across the entire research lifecycle. Inspired by Karpathy's LLM Wiki pattern. Use when user says "知识库", "research wiki", "add paper", "wiki query", "查知识库", or wants to build/query a persistent field map.
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。
Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, related work, a survey, or a landscape summary.
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。
Answer an explicitly vault-scoped question from an Obsidian wiki without changing it. Use when the user selects the vault as the evidence source: query the wiki, query quick, query deep, explain from the wiki, summarize the vault, find in wiki, search the wiki, or based on the wiki. Do not route ordinary general-knowledge questions here.
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Search and contribute to the shared AI-modding knowledge base, where field notes record how specific games were modded, decompiled or reverse-engineered (exact versions, route, engine facts, verification, gotchas). Use before starting work on a game ("has anyone modded X?"), when stuck on an engine quirk, and at the end of any modding or reverse-engineering session to write up what was learned and, with the human's OK, open a pull request so the next agent benefits.
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。
使用 Yuxi 知识库进行检索、打开文档、文档内定位和查看思维导图。当用户需要基于已配置知识库回答问题、核验资料或引用文档内容时使用此技能。
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 connected Notion pages and databases, verify the relevant sources, and produce concise answers that preserve links and uncertainty.
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。
This skill helps users automatically extract YouTube video transcripts and metadata via the BrowserAct API. The Agent should proactively apply this skill when users express needs like extracting full transcript from a specific YouTube video, getting subtitles and metadata for video content analysis, gathering video titles and likes counts, summarizing YouTube videos without watching them, collecting channel details from a video URL, tracking transcript automation for specific videos, scraping YouTube subtitles for internal knowledge bases, fetching full video content for AI summarization pipelines, downloading structured transcripts from YouTube links, analyzing video text content for media research, monitoring video publisher information and channel links, or building datasets from YouTube video transcripts.
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 this as the main Claude Scholar skill for a vault-first, project-scoped Obsidian research knowledge base rooted at Research/{project-slug}/. It owns bootstrap, routing, daily logging, hub/plan/index maintenance, registry updates, lifecycle actions, and lint orchestration.
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Use this skill for Obsidian-native formatting and derived artifacts such as Markdown formatting, wikilinks, registry tables, canvas files, optional Bases, CLI operations, and link repair. This skill does not decide knowledge routing.
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Use this skill when the user wants to detach, archive, purge, or otherwise change the lifecycle state of an Obsidian project knowledge base.
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Use this skill when generating higher-level synthesis notes such as literature reviews, comparison matrices, project summaries, or other cross-note summaries inside the project knowledge base.
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This skill should be used when the user asks to start a new research project, import an existing code-plus-Markdown repository into Obsidian, or bind the current repository to a compact research knowledge base for future syncing.
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。
This skill should be used when the user asks to maintain an Obsidian knowledge base for a research project, import an existing research repository into Obsidian, keep project memory or daily notes synchronized, summarize project context into durable notes, or update experiments, results, papers, writing, and plans in an Obsidian vault without requiring MCP.
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。
Write a blameless incident postmortem under postmortems/ following the Google SRE shape — evidence-based timeline, trigger vs root cause vs symptom, contributing factors, what went well, and owned+dated+verifiable action items. Read when asked to write a postmortem, do an incident review, run a root cause analysis, write up the outage, retro on the outage, or when the user says we had an incident and wants it documented. Do NOT read to frame a proposal (use frame-a-proposal), write a spec (use write-a-spec), record a decision (use record-a-decision), or review a design (use review-a-design) — a postmortem documents an incident that already happened, it does not propose, specify, decide, or critique future work.
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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
Auto-detect work context (Dev vs Knowledge) — use to tailor workflows based on current task type
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。
Initializes a hierarchical AGENTS.md knowledge base for a project. Use when a repo needs its structure, commands, and conventions documented for agents.
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 Acontext, Login & Init Acontext Project, Add Skill Memory to Agent.
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。