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Keep project decisions, debugging notes, and session discoveries in a lasting Markdown wiki. Organize pages with tags and categories, connect related notes with links, and retrieve information through keyword searches.
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Organize Confluence team wikis and project documentation with clear page hierarchies, labels, and templates. Use macros, built-in content tools, to assemble indexes and reports, with REST API guidance for creating and updating pages.
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Build a lasting research knowledge base linking papers, ideas, experiments, and claims. Keep failed approaches and unresolved gaps available for future work, generate compact summaries, and check records for missing connections or conflicting evidence.
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Add Mermaid diagrams to generated wiki pages to explain request flows, state changes, data relationships, and branching logic. Keep diagrams aligned with inspected source code and repair syntax problems in diagrams degraded during earlier runs.
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Set up a new Obsidian vault, a folder for linked notes, or adopt an existing one. Select the working vault and route requests to the appropriate skills for importing sources, answering questions, saving results, or maintenance.
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Turn conversations and notes into structured Notion pages, including wiki entries, how-to guides, FAQs, and decision logs. Capture context and sources, connect related pages, and maintain owners and status as information changes.
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Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.
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When you want to capture into, compile, query, lint, or connect your personal Second Brain. Wraps the Karpathy LLM Wiki schema (Obsidian or any markdown vault) — raw/ (unprocessed sources), wiki/ (AI-compiled interlinked topic pages), outputs/ (generated artifacts). Tool-agnostic in design but defaults to a vault at ${SECOND_BRAIN_VAULT:-$HOME/Documents/SecondBrain}/. Six modes — capture (drop something into raw/), compile (process unprocessed raw files into wiki pages, update INDEX.md), query (answer a question from the wiki, save to outputs/), lint (orphans / contradictions / stale / unprocessed raw / topic gaps), connect (suggest new wikilinks between pages), search (quick lookup). Triggers on "/second-brain," "/sb," "capture this," "save this to my brain," "compile the wiki," "process raw notes," "query my wiki," "ask my brain," "lint the wiki," "find connections," "search my notes." Complements deep-research (external corpus) — this is the internal corpus.
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Build and maintain a structured LLM-generated wiki for any codebase. Use when the user asks to analyze/understand/document a codebase, build a code wiki, create project documentation from source, or update an existing .llm-wiki. Triggers on phrases like "build wiki", "analyze this codebase", "document this project", "update wiki", "llm-wiki", or when entering an unfamiliar project that has no .llm-wiki yet.
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Fast PARALLEL wiki lookup engine over wiki/techniques + wiki/payloads + wiki/tools + wiki/cheatsheets for a surface/service/vuln-class. Two modes - quick (one qmd search, cheap, fire constantly) and deep (4 parallel subagents, one per area, merged ready-to-use arsenal card, cached). This is the fast path arsenal that `arsenal` delegates to; the hunt-* skills each inline their own qmd_query and can hand off here for a parallel lookup. Use for "what do I use against <surface>", "arsenal for <X>", "deep/full arsenal", "tool + payload + technique + cheatsheet for <X>", "fast wiki lookup", "parallel wiki search", any "how do I attack/exploit <service|vuln-class>" where you want the documented tooling + payloads before hand-rolling.
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Incremental LLM-friendly wiki generator for Obsidian note vaults. Use when: (1) Building wiki from notes, (2) Ingesting notes to wiki, (3) Obsidian LLM wiki, (4) Incremental knowledge base management. Triggers: 'build wiki from notes', 'ingest notes to wiki', 'Obsidian LLM wiki', 'incremental knowledge base'.
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Build and maintain a GitNexus code index, a searchable map of code relationships. Use CLI commands to refresh or remove indexes, check their status, list indexed projects, and generate repository documentation with an LLM.
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Manage Lark knowledge spaces, their members, and the hierarchy of document entries. Create spaces and entries, browse their structure, and move or copy entries to organize where team documents and shortcuts are located.
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Read, summarize, create, and edit 飞书 Docx and Wiki document content. Revise wording, reorganize sections, insert local images or attachments, and retrieve document media, with additional support for document history and mind notes.
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Answer questions using a selected Obsidian vault, a collection of linked notes, without changing its files. Choose a search depth and receive answers with page references, clearly identified uncertainty, conflicting evidence, and any missing information.
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Retrieve 飞书 cloud documents as Markdown using a document URL or token. Handle embedded images, files, and whiteboards through a separate download tool, and identify the underlying content type before reading wiki links.
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[omh] Scattered knowledge needing a wiki: wiki construction blueprints and retained knowledge capture with destination-aware external knowledge connection guidance. Use when the user says: wiki, project wiki, build a wiki, start a wiki, organize my notes, external knowledge store, knowledge base, Obsidian.
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Query pro-workflow wikis via SQLite FTS5 BM25 retrieval. Returns top-K passages with citations. Use when answering a question that any of the user's wikis already covers, when the user says "what does the wiki say about X", "ask wiki", "search wikis", or before drafting a new wiki page (to avoid duplication).
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Build and maintain a persistent, LLM-maintained markdown wiki following Andrej Karpathy's LLM Wiki pattern — the agent incrementally compiles raw sources into an interlinked knowledge base instead of re-deriving answers from scratch. Use this whenever the user wants to ingest a source (an article, paper, transcript, chapter, meeting notes), file knowledge or conversation findings into the wiki, query the accumulated knowledge base, lint or health-check the wiki, or mentions "the wiki", "knowledge base", "ingest this", "file this", "what do we know about X", or accumulating notes on a topic over time — even if they don't say "LLM Wiki" explicitly.
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Use to run the second-brain loop — turn captures in raw/ into clean, cross-linked knowledge in wiki/, and to answer questions from past thinking. Trigger on "/wiki", "process my raw notes", "update the wiki", "add this to my brain/wiki", "what did I think about X", "what do my notes say about X". Follows references/sops/wiki-translate.md. Enforces the admission policy: no PHI, no live financials, no secrets in the committed wiki.
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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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Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.
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Helps an AI assistant work with the Miraheze wiki farm — writing wiki requests that get approved, navigating ManageWiki, doing common how-to tasks (templates, skins, permissions, custom domains, backups), writing regex for MediaWiki search-and-replace, AND writing actual article and page content for Miraheze-hosted wikis. Miraheze does NOT ban generative AI; AI-written content is permitted (subject to per-wiki rules). MADE BY SQERSTERS
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Organize Notion workspaces with clear page structures, connected databases, and reusable templates. Build team wikis and task views, reduce duplicated content, and use the Notion API to automate page creation, database queries, and content updates.
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