获取一个URL并将其内容提炼到Obsidian知识库中。如果从项目目录内调用，页面将直接保存到该项目的文件夹中（如有必要，会在知识库中创建该项目）；否则保存到misc/文件夹，并随时间积累项目关联性。
ar9av/ingest-url 是一个专为AI代理（如Claude Code、Cursor或Codex）设计的技能，用于从给定的URL抓取内容，并将其提炼为格式化的笔记，存入Obsidian知识库。该技能在Obsidian中按项目组织笔记：如果用户在特定项目目录中工作，页面会直接存入该项目的文件夹；若不在项目目录中，则默认存入“misc/”文件夹，并随时间累积项目关联性，从而自动归类。用户可以通过自然语言指令（如“/ingest-url <url>”、“add this URL to the wiki”、“ingest this link”）或粘贴URL时附带“save this”来触发。此技能适用于Obsidian用户，帮助高效保存和整理来自网页的信息，是知识管理工作流的理想补充。
npx skills add https://github.com/ar9av/obsidian-wiki/tree/main/skills/ingest-urlInstalled? Explore more 写作与编辑 skills: steipete/notion, langchain-ai/langchain, bytedance/podcast-generation · View all 6 →
获取一个URL并将其内容提炼到Obsidian知识库中。如果从项目目录内调用，页面将直接保存到该项目的文件夹中（如有必要，会在知识库中创建该项目）；否则保存到misc/文件夹，并随时间积累项目关联性。当用户说出“/ingest-url ”、“add this URL to the wiki”、“ingest this link”、“save this page”，或者粘贴URL并说“add this”或“save this to my wiki”时，请使用此技能。
This repo contains 20 individual skills — each has its own dedicated page.
Ingest Claude Code conversation history into the Obsidian wiki. Use this skill when the user wants to mine their past Claude conversations for knowledge, import their ~/.claude folder, extract insights from previous coding sessions, or says things like "process my Claude history", "add my conversations to the wiki", "what have I discussed with Claude before". Also triggers when the user mentions their .claude folder, Claude projects, session data, past conversation logs, local-agent-mode sessions, or audit logs.
Ingest Codex CLI conversation history into the Obsidian wiki. Use this skill when the user wants to mine their past Codex sessions for knowledge, import their ~/.codex folder, extract insights from previous coding sessions, or says things like "process my Codex history", "add my Codex conversations to the wiki", or "what have I discussed in Codex before". Also triggers when the user mentions .codex sessions, rollout files, session_index.jsonl, or Codex transcript logs.
Ingest GitHub Copilot CLI session history into an Obsidian wiki as distilled knowledge pages. Use this skill when the user wants to capture their Copilot CLI sessions into a personal wiki — extracting architecture decisions, debug notes, and patterns into searchable Obsidian pages. Triggers on phrases like "ingest my copilot sessions into obsidian", "add my copilot history to my wiki", "pull my copilot session history into the vault", "capture what I've learned from copilot into obsidian", "just the new sessions since last time", or "mine patterns across my copilot sessions". Also triggers when the user mentions session-store.db, ~/.copilot/session-state, or VS Code copilot-chat transcripts in the context of building a wiki or knowledge base. Does NOT trigger for general copilot usage questions, searching sessions, or backing up history.
Scan the Obsidian wiki and automatically discover missing cross-references between pages. Use this skill when the user says "link my pages", "find missing links", "cross-reference", "connect my wiki", "add wikilinks", "what pages should be linked", or after any large ingestion to ensure new pages are woven into the existing knowledge graph. Also trigger when the user mentions "orphan pages" in the context of wanting to connect them, or says things like "my wiki feels disconnected" or "pages aren't linked well". This is a write-heavy skill — it actually modifies pages to add links, unlike wiki-lint which just reports issues.
Run the daily wiki maintenance cycle: check all source freshness, update the index, and regenerate hot.md. Use this skill when the user says "/daily-update", "run the daily update", "update everything", "morning sync", "refresh the wiki index", or when triggered by the launchd cron at 9 AM. Also use to set up or verify the cron + terminal notification infrastructure for the first time ("set up the daily cron", "install the terminal notification", "how do I get the morning reminder?").
Ingest any raw text data, conversation logs, chat exports, or unstructured documents into the Obsidian wiki. Use this skill when the user wants to process data that isn't standard documents or Claude history — things like ChatGPT exports, Slack threads, Discord logs, meeting transcripts, journal entries, CSV data, browser bookmarks, email archives, or any raw text dump. Triggers on "ingest this data", "process these logs", "add this export to the wiki", "import my chat history from X". This is the catch-all for any text source not covered by the more specific ingest skills.
Color-code the Obsidian graph view by rewriting `.obsidian/graph.json` colorGroups. Use this skill when the user says "color my graph", "color code obsidian", "colorize the graph", "color the graph by tag", "color by category", "highlight visibility in graph", "make the graph colorful", "distinguish tags in graph", or wants nodes in Obsidian's graph view tinted by tag, folder, or visibility. Generates a `colorGroups` array from the vault's actual tags/categories and merges it into the existing graph.json without clobbering other graph settings. Always backs up first.
Ingest Hermes agent history into the Obsidian wiki. Use this skill when the user wants to mine their past Hermes sessions for knowledge, import their ~/.hermes folder, extract insights from previous Hermes conversations, or says things like "process my Hermes history", "add my Hermes memories to the wiki", "ingest ~/.hermes", or "what have I worked on in Hermes". Also triggers when the user mentions Hermes memories, Hermes sessions, ~/.hermes/memories, or Hermes skill logs.
Validate whether an implementation matches its stated goal. Use this skill when a skill or agent wants a second opinion on its own output, when the user says "check this implementation", "validate what you did", "is this correct?", "review the output", or "did you do this right?". Also spawned automatically as a subagent by other skills (memory-bridge, daily-update) to self-check their outputs before presenting to the user. Returns a structured pass/warn/fail verdict with specific actionable issues.
The foundational knowledge distillation pattern for building and maintaining an AI-powered Obsidian wiki. Based on Andrej Karpathy's LLM Wiki architecture. Use this skill whenever the user wants to understand the wiki pattern, set up a new knowledge base, or needs guidance on the three-layer architecture (raw sources → wiki → schema). Also use when discussing knowledge management strategy, wiki structure decisions, or how to organize distilled knowledge. This is the "theory" skill — other skills handle specific operations (ingesting, querying, linting).
Browse and compare wiki knowledge by which AI tool originally produced it. Use this skill when the user says "/memory-bridge", "browse codex memory", "what did codex know about X", "show me claude knowledge", "cross-tool memory", "what does hermes know that claude doesn't", "show me knowledge from <tool>", "compare my AI tool memories", or wants to explore knowledge gaps between tools. Works from any project. Diff mode ("what's different", "unique to codex", "gaps between tools") is the killer feature — it surfaces blind spots between tools that the user may not know exist.
Automates ingestion of documents into the Obsidian wiki (obsidian-wiki) using the wiki-ingest pipeline. Handles deduplication via manifest, frontmatter, and cross-links; triggers on user request within the obsidian-wiki project context.
Ingest OpenClaw agent history into the Obsidian wiki. Use this skill when the user wants to mine their past OpenClaw sessions for knowledge, import their ~/.openclaw folder, extract insights from previous OpenClaw conversations, or says things like "process my OpenClaw history", "add my OpenClaw sessions to the wiki", "ingest ~/.openclaw", or "what have I worked on in OpenClaw". Also triggers when the user mentions OpenClaw session logs, MEMORY.md, daily notes, or ~/.openclaw/workspace.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Enforce consistent tagging across the Obsidian wiki using a controlled vocabulary. Use this skill when the user says "fix my tags", "normalize tags", "clean up tags", "tag audit", "what tags should I use", "tag taxonomy", or whenever you're creating or updating wiki pages and need to choose the right tags. Also trigger when the user asks about tag conventions, wants to add a new tag to the taxonomy, or says "my tags are a mess". Always consult this skill's taxonomy file before assigning tags to any wiki page.
Query-driven targeted ingest from a specific AI agent's raw history. Use this skill when the user invokes /wiki-claude, /wiki-codex, /wiki-hermes, /wiki-openclaw, /wiki-copilot, /wiki-pi — with or without a search topic. Different from wiki-history-ingest (which bulk-ingests everything new): this skill finds sessions about a SPECIFIC TOPIC in a specific agent's history and ingests just those, then returns a synthesized answer immediately usable in the current session. Primary use case: you're working in agent A and want to pull in how you solved X in agent B's history. Cross-referencing, not archiving. Also trigger on: "what did I work on in codex about X", "search my claude sessions for Y", "pull in hermes knowledge about Z", "find that conversation where I did X in codex".
Save the current conversation as a permanent, structured wiki note. Use this skill when the user says "save this", "/wiki-capture", "capture this", "file this conversation", "preserve this", "add this to my wiki", or wants to turn what was just discussed into lasting knowledge. The skill classifies the content, rewrites it as declarative knowledge (not a chat transcript), and places it in the correct vault category. Also supports a fast QUICK MODE (`/wiki-capture --quick`, "quick capture", "capture this finding", "save this bug fix", "save this gotcha", "drop this to raw", "quick save to wiki") that drops findings to the `_raw/` staging area in under 60 seconds with no manifest or index writes — used by the session-end Stop hook to auto-preserve findings.
Create dynamic, queryable dashboard views of the Obsidian vault using Obsidian Bases or Dataview. Use this skill when the user says "create a dashboard", "vault dashboard", "show all X as a table", "dynamic view", "query my vault", "build a content index", "show me all concepts/entities/projects", or wants a structured, auto-updating view of their wiki content. Bases is native to Obsidian 1.8+ (no plugin needed). Dataview requires the community plugin.
Generate a periodic knowledge digest — a human-readable newsletter-style summary of what was learned, updated, and connected in your wiki over a specified period (day/week/month). Use when the user says "what did I learn this week", "give me a digest", "weekly summary", "knowledge report", "what's new in my wiki", "/wiki-digest [period]", "summarize my recent learning", or wants a readable overview of recent wiki activity. Distinct from wiki-status (which reports ingestion delta of sources) — wiki-digest summarizes *knowledge*, not sources.
Export the Obsidian wiki's knowledge graph to structured formats for use in external tools. Use this skill when the user says "export wiki", "export graph", "export to JSON", "export to Gephi", "export to Neo4j", "graphml", "visualize wiki", "knowledge graph export", "export to OKF", "OKF bundle", "open knowledge format", "export as markdown bundle", or wants to use their wiki data in another tool. Outputs graph.json, graph.graphml, cypher.txt (Neo4j), and graph.html (interactive browser visualization) into a wiki-export/ directory at the vault root, plus an optional OKF (Open Knowledge Format) markdown bundle under wiki-export/okf/.
Notion CLI/API for pages, Markdown content, data sources, files, comments, search, Workers, and raw API calls.
The agent engineering platform.
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors