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  "item": {
    "slug": "note-processor",
    "name": "Note Processor",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/johstracke/note-processor",
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    "packageFormat": "ZIP package",
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      "SKILL.md",
      "scripts/note_processor.py"
    ],
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      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
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          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
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          "label": "Upgrade existing",
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        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
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    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
      }
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Note Processor",
        "body": "Analyze and summarize research notes to extract insights quickly."
      },
      {
        "title": "Quick Start",
        "body": "note_processor.py summarize <topic>\nnote_processor.py keywords <topic>\nnote_processor.py extract <topic> <keyword>\nnote_processor.py list\n\nExamples:\n\n# Get a summary of a research topic\nnote_processor.py summarize income-experiments\n\n# Extract top keywords from notes\nnote_processor.py keywords security-incident\n\n# Search for specific information\nnote_processor.py extract income-experiments skill\n\n# List all research topics with stats\nnote_processor.py list"
      },
      {
        "title": "Features",
        "body": "Summaries - Overview of topic with statistics, tags, key points\nKeywords - Extract most common words (filters stop words)\nSearch - Find notes containing specific keywords\nList - See all research topics with basic stats\nIntegration - Works with research-assistant's database format"
      },
      {
        "title": "After Research Sessions",
        "body": "# Summarize what you learned\nnote_processor.py summarize new-research-topic\n\n# Extract key themes\nnote_processor.py keywords new-research-topic"
      },
      {
        "title": "Before Writing Reports",
        "body": "# Find specific information\nnote_processor.py extract income-experiments monetization\n\n# Get overview for introductions\nnote_processor.py summarize income-experiments"
      },
      {
        "title": "Reviewing Progress",
        "body": "# See all topics and their sizes\nnote_processor.py list\n\n# Check what you've been working on\nnote_processor.py keywords income-experiments"
      },
      {
        "title": "summarize <topic>",
        "body": "Shows:\n\nNote count and word count\nCreation and last update dates\nTop 5 tags\nKey points (sentences with important words)\n3 most recent notes\n\nOutput example:\n\n📊 Summary: income-experiments\n------------------------------------------------------------\nNotes: 4\nWords: 63\nCreated: 2026-02-07\nLast update: 2026-02-07\n\n🏷️  Top Tags:\n   content: 2\n   automation: 2\n   experiment: 2\n\n💡 Key Points:\n   1. First experiment: create and publish skills...\n   2. Second experiment: content automation pipeline..."
      },
      {
        "title": "keywords <topic>",
        "body": "Shows:\n\nTotal unique keywords\nTop 20 keywords with frequency\nFilters common stop words (that, this, with, from, etc.)\n\nOutput example:\n\n🔤 Keywords: income-experiments\n------------------------------------------------------------\nTotal unique keywords: 38\n\nTop 20 Keywords:\n  1. experiment           ( 4x)\n  2. skill                ( 3x)\n  3. clawhub              ( 2x)\n  4. content              ( 2x)"
      },
      {
        "title": "extract <topic> <keyword>",
        "body": "Shows:\n\nAll notes containing the keyword\nKeyword highlighted in uppercase\nTimestamps and tags\nPreview of matched content\n\nOutput example:\n\n🔍 Search Results: 'skill' in income-experiments\n------------------------------------------------------------\nFound 4 match(es)\n\n1. [2026-02-07 19:09:51]\n   Tags: ideas, autonomous\n   First experiment: create and publish **SKILL**s to ClawHub..."
      },
      {
        "title": "list",
        "body": "Shows:\n\nAll research topics\nNote count and word count\nLast update date\nPreview of most recent note\n\nOutput example:\n\n📚 Research Topics (5)\n------------------------------------------------------------\n\nincome-experiments\n   Notes: 4 | Words: 63 | Updated: 2026-02-07\n   Latest: Experiment 2 STARTING: Content automation...\n\nsecurity-incident\n   Notes: 1 | Words: 45 | Updated: 2026-02-07\n   Latest: Day 1: Security vulnerability found..."
      },
      {
        "title": "Integration with research-assistant",
        "body": "note-processor works with the same database as research-assistant (research_db.json)."
      },
      {
        "title": "Typical Workflow",
        "body": "# 1. Add research notes\nresearch_organizer.py add \"new-topic\" \"Research finding here\" \"tag1\" \"tag2\"\n\n# 2. Add more notes over time\nresearch_organizer.py add \"new-topic\" \"Another finding\" \"tag3\"\n\n# 3. Summarize when done\nnote_processor.py summarize new-topic\n\n# 4. Find specific information\nnote_processor.py extract new-topic keyword\n\n# 5. See all topics\nnote_processor.py list"
      },
      {
        "title": "Using Both Together",
        "body": "# Research phase\nresearch_organizer.py add \"experiment\" \"Test result 1\" \"testing\"\nresearch_organizer.py add \"experiment\" \"Test result 2\" \"testing\"\nresearch_organizer.py add \"experiment\" \"Conclusion: worked!\" \"results\"\n\n# Analysis phase\nnote_processor.py summarize experiment\nnote_processor.py keywords experiment\n\n# Writing phase\nnote_processor.py extract experiment conclusion\n# Now write report based on extracted notes"
      },
      {
        "title": "Key Point Detection",
        "body": "The summarize command detects key points by finding sentences with important words:\n\nimportant, key, critical, essential\nmust, should, note, remember\nwarning, priority, critical\n\nThis helps surface actionable insights from your research."
      },
      {
        "title": "Keyword Extraction",
        "body": "The keywords command:\n\nFilters words shorter than 4 characters\nRemoves common stop words\nCounts frequency across all notes\nShows top 20 keywords\n\nStop words filtered:\nthat, this, with, from, have, been, will, what, when, where, which, their, there, would, could, should, about, these, those, other, into, through"
      },
      {
        "title": "Before Writing a Report",
        "body": "# Get overview\nnote_processor.py summarize research-topic\n\n# Find specific data points\nnote_processor.py extract research-topic metrics\n\n# Extract themes\nnote_processor.py keywords research-topic"
      },
      {
        "title": "Reviewing Research Progress",
        "body": "# See what you've been working on\nnote_processor.py list\n\n# Check a specific topic's progress\nnote_processor.py summarize current-project\n\n# Find patterns\nnote_processor.py keywords current-project"
      },
      {
        "title": "Finding Specific Information",
        "body": "# Search across a topic\nnote_processor.py extract income-experiments monetization\n\n# Find references to specific tools\nnote_processor.py extract security-incident path-validation\n\n# Locate conclusions\nnote_processor.py extract experiment conclusion"
      },
      {
        "title": "Best Practices",
        "body": "Use summaries - Get overview before diving into details\nSearch first - Use extract before reading all notes\nCheck keywords - Find themes you might have missed\nList regularly - Review all topics to see gaps\nTag consistently - Makes keywords more meaningful"
      },
      {
        "title": "Data Location",
        "body": "Database: ~/.openclaw/workspace/research_db.json\nFormat: Compatible with research-assistant skill"
      },
      {
        "title": "Limitations",
        "body": "Simple keyword extraction - Frequency-based, not semantic\nNo NLP - Basic text processing (no ML/AI)\nStop word list - English-focused, customize for other languages\nKey point detection - Pattern-based, not understanding-based"
      },
      {
        "title": "For Better Keywords",
        "body": "Use consistent terminology in your notes\nAvoid abbreviations or synonyms for the same concept\nTag notes with important terms\nReview keywords to see if important terms appear"
      },
      {
        "title": "For Better Summaries",
        "body": "Write complete sentences in notes\nInclude important words (key, critical, must, etc.)\nTag notes with themes\nRegularly summarize to track progress"
      },
      {
        "title": "For Better Search",
        "body": "Use specific keywords in extract\nSearch for related terms (synonyms)\nCheck tags in results\nUse summaries to find the right topic"
      },
      {
        "title": "\"Topic not found\"",
        "body": "Topic 'x' not found.\n\nSolution: Check topic name spelling. Use note_processor.py list to see all topics."
      },
      {
        "title": "\"No matches found\"",
        "body": "No matches for 'keyword' in topic 'x'\n\nSolution: Try different keywords, check spelling, use note_processor.py keywords to find related terms."
      },
      {
        "title": "Poor keyword results",
        "body": "Top Keywords are mostly common words\n\nSolution:\n\nUse more specific terms in your notes\nTag notes with important terms\nThe stop word filter can be customized in the code"
      },
      {
        "title": "Project Review",
        "body": "# What have I been working on?\nnote_processor.py list\n\n# Tell me about this project\nnote_processor.py summarize project-x\n\n# What are the main themes?\nnote_processor.py keywords project-x"
      },
      {
        "title": "Writing Documentation",
        "body": "# Find specific details\nnote_processor.py extract security-incident vulnerability\n\n# Get overview for introduction\nnote_processor.py summarize security-incident\n\n# What's important?\nnote_processor.py keywords security-incident"
      },
      {
        "title": "Preparing a Report",
        "body": "# Find all relevant information\nnote_processor.py extract income-experiments monetization\n\n# Get summary\nnote_processor.py summarize income-experiments\n\n# Extract key points\nnote_processor.py summarize income-experiments\n# Key points are in the output"
      },
      {
        "title": "With research-assistant",
        "body": "research-assistant: add notes\nnote-processor: analyze notes\nUse together: add → analyze → write report"
      },
      {
        "title": "With task-runner",
        "body": "# Add task to summarize research\ntask_runner.py add \"Summarize experiment results\" \"documentation\"\n\n# When complete\nnote_processor.py summarize experiment\n\n# Mark done\ntask_runner.py complete 1"
      },
      {
        "title": "With file skills",
        "body": "# Extract research notes\nnote_processor.py extract research-topic important\n\n# Export for sharing\nresearch_organizer.py export research-topic ~/shared/summary.md\n\n# Or export summary output to file\nnote_processor.py summarize research-topic > ~/shared/summary.txt"
      },
      {
        "title": "Zero-Cost Advantage",
        "body": "This skill requires:\n\n✅ Python 3 (included)\n✅ No API keys\n✅ No external dependencies\n✅ No paid services\n✅ Works with research-assistant (free)\n\nPerfect for autonomous research workflows with no additional costs."
      }
    ],
    "body": "Note Processor\n\nAnalyze and summarize research notes to extract insights quickly.\n\nQuick Start\nnote_processor.py summarize <topic>\nnote_processor.py keywords <topic>\nnote_processor.py extract <topic> <keyword>\nnote_processor.py list\n\n\nExamples:\n\n# Get a summary of a research topic\nnote_processor.py summarize income-experiments\n\n# Extract top keywords from notes\nnote_processor.py keywords security-incident\n\n# Search for specific information\nnote_processor.py extract income-experiments skill\n\n# List all research topics with stats\nnote_processor.py list\n\nFeatures\nSummaries - Overview of topic with statistics, tags, key points\nKeywords - Extract most common words (filters stop words)\nSearch - Find notes containing specific keywords\nList - See all research topics with basic stats\nIntegration - Works with research-assistant's database format\nWhen to Use\nAfter Research Sessions\n# Summarize what you learned\nnote_processor.py summarize new-research-topic\n\n# Extract key themes\nnote_processor.py keywords new-research-topic\n\nBefore Writing Reports\n# Find specific information\nnote_processor.py extract income-experiments monetization\n\n# Get overview for introductions\nnote_processor.py summarize income-experiments\n\nReviewing Progress\n# See all topics and their sizes\nnote_processor.py list\n\n# Check what you've been working on\nnote_processor.py keywords income-experiments\n\nCommand Details\nsummarize <topic>\n\nShows:\n\nNote count and word count\nCreation and last update dates\nTop 5 tags\nKey points (sentences with important words)\n3 most recent notes\n\nOutput example:\n\n📊 Summary: income-experiments\n------------------------------------------------------------\nNotes: 4\nWords: 63\nCreated: 2026-02-07\nLast update: 2026-02-07\n\n🏷️  Top Tags:\n   content: 2\n   automation: 2\n   experiment: 2\n\n💡 Key Points:\n   1. First experiment: create and publish skills...\n   2. Second experiment: content automation pipeline...\n\nkeywords <topic>\n\nShows:\n\nTotal unique keywords\nTop 20 keywords with frequency\nFilters common stop words (that, this, with, from, etc.)\n\nOutput example:\n\n🔤 Keywords: income-experiments\n------------------------------------------------------------\nTotal unique keywords: 38\n\nTop 20 Keywords:\n  1. experiment           ( 4x)\n  2. skill                ( 3x)\n  3. clawhub              ( 2x)\n  4. content              ( 2x)\n\nextract <topic> <keyword>\n\nShows:\n\nAll notes containing the keyword\nKeyword highlighted in uppercase\nTimestamps and tags\nPreview of matched content\n\nOutput example:\n\n🔍 Search Results: 'skill' in income-experiments\n------------------------------------------------------------\nFound 4 match(es)\n\n1. [2026-02-07 19:09:51]\n   Tags: ideas, autonomous\n   First experiment: create and publish **SKILL**s to ClawHub...\n\nlist\n\nShows:\n\nAll research topics\nNote count and word count\nLast update date\nPreview of most recent note\n\nOutput example:\n\n📚 Research Topics (5)\n------------------------------------------------------------\n\nincome-experiments\n   Notes: 4 | Words: 63 | Updated: 2026-02-07\n   Latest: Experiment 2 STARTING: Content automation...\n\nsecurity-incident\n   Notes: 1 | Words: 45 | Updated: 2026-02-07\n   Latest: Day 1: Security vulnerability found...\n\nIntegration with research-assistant\n\nnote-processor works with the same database as research-assistant (research_db.json).\n\nTypical Workflow\n# 1. Add research notes\nresearch_organizer.py add \"new-topic\" \"Research finding here\" \"tag1\" \"tag2\"\n\n# 2. Add more notes over time\nresearch_organizer.py add \"new-topic\" \"Another finding\" \"tag3\"\n\n# 3. Summarize when done\nnote_processor.py summarize new-topic\n\n# 4. Find specific information\nnote_processor.py extract new-topic keyword\n\n# 5. See all topics\nnote_processor.py list\n\nUsing Both Together\n# Research phase\nresearch_organizer.py add \"experiment\" \"Test result 1\" \"testing\"\nresearch_organizer.py add \"experiment\" \"Test result 2\" \"testing\"\nresearch_organizer.py add \"experiment\" \"Conclusion: worked!\" \"results\"\n\n# Analysis phase\nnote_processor.py summarize experiment\nnote_processor.py keywords experiment\n\n# Writing phase\nnote_processor.py extract experiment conclusion\n# Now write report based on extracted notes\n\nKey Point Detection\n\nThe summarize command detects key points by finding sentences with important words:\n\nimportant, key, critical, essential\nmust, should, note, remember\nwarning, priority, critical\n\nThis helps surface actionable insights from your research.\n\nKeyword Extraction\n\nThe keywords command:\n\nFilters words shorter than 4 characters\nRemoves common stop words\nCounts frequency across all notes\nShows top 20 keywords\n\nStop words filtered: that, this, with, from, have, been, will, what, when, where, which, their, there, would, could, should, about, these, those, other, into, through\n\nUse Cases\nBefore Writing a Report\n# Get overview\nnote_processor.py summarize research-topic\n\n# Find specific data points\nnote_processor.py extract research-topic metrics\n\n# Extract themes\nnote_processor.py keywords research-topic\n\nReviewing Research Progress\n# See what you've been working on\nnote_processor.py list\n\n# Check a specific topic's progress\nnote_processor.py summarize current-project\n\n# Find patterns\nnote_processor.py keywords current-project\n\nFinding Specific Information\n# Search across a topic\nnote_processor.py extract income-experiments monetization\n\n# Find references to specific tools\nnote_processor.py extract security-incident path-validation\n\n# Locate conclusions\nnote_processor.py extract experiment conclusion\n\nBest Practices\nUse summaries - Get overview before diving into details\nSearch first - Use extract before reading all notes\nCheck keywords - Find themes you might have missed\nList regularly - Review all topics to see gaps\nTag consistently - Makes keywords more meaningful\nData Location\n\nDatabase: ~/.openclaw/workspace/research_db.json Format: Compatible with research-assistant skill\n\nLimitations\nSimple keyword extraction - Frequency-based, not semantic\nNo NLP - Basic text processing (no ML/AI)\nStop word list - English-focused, customize for other languages\nKey point detection - Pattern-based, not understanding-based\nTips\nFor Better Keywords\nUse consistent terminology in your notes\nAvoid abbreviations or synonyms for the same concept\nTag notes with important terms\nReview keywords to see if important terms appear\nFor Better Summaries\nWrite complete sentences in notes\nInclude important words (key, critical, must, etc.)\nTag notes with themes\nRegularly summarize to track progress\nFor Better Search\nUse specific keywords in extract\nSearch for related terms (synonyms)\nCheck tags in results\nUse summaries to find the right topic\nTroubleshooting\n\"Topic not found\"\nTopic 'x' not found.\n\n\nSolution: Check topic name spelling. Use note_processor.py list to see all topics.\n\n\"No matches found\"\nNo matches for 'keyword' in topic 'x'\n\n\nSolution: Try different keywords, check spelling, use note_processor.py keywords to find related terms.\n\nPoor keyword results\nTop Keywords are mostly common words\n\n\nSolution:\n\nUse more specific terms in your notes\nTag notes with important terms\nThe stop word filter can be customized in the code\nExamples by Use Case\nProject Review\n# What have I been working on?\nnote_processor.py list\n\n# Tell me about this project\nnote_processor.py summarize project-x\n\n# What are the main themes?\nnote_processor.py keywords project-x\n\nWriting Documentation\n# Find specific details\nnote_processor.py extract security-incident vulnerability\n\n# Get overview for introduction\nnote_processor.py summarize security-incident\n\n# What's important?\nnote_processor.py keywords security-incident\n\nPreparing a Report\n# Find all relevant information\nnote_processor.py extract income-experiments monetization\n\n# Get summary\nnote_processor.py summarize income-experiments\n\n# Extract key points\nnote_processor.py summarize income-experiments\n# Key points are in the output\n\nIntegration with Other Skills\nWith research-assistant\nresearch-assistant: add notes\nnote-processor: analyze notes\nUse together: add → analyze → write report\nWith task-runner\n# Add task to summarize research\ntask_runner.py add \"Summarize experiment results\" \"documentation\"\n\n# When complete\nnote_processor.py summarize experiment\n\n# Mark done\ntask_runner.py complete 1\n\nWith file skills\n# Extract research notes\nnote_processor.py extract research-topic important\n\n# Export for sharing\nresearch_organizer.py export research-topic ~/shared/summary.md\n\n# Or export summary output to file\nnote_processor.py summarize research-topic > ~/shared/summary.txt\n\nZero-Cost Advantage\n\nThis skill requires:\n\n✅ Python 3 (included)\n✅ No API keys\n✅ No external dependencies\n✅ No paid services\n✅ Works with research-assistant (free)\n\nPerfect for autonomous research workflows with no additional costs."
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    "owner": "johstracke",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
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