{
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  "item": {
    "slug": "pubmed-search-skill",
    "name": "PubMed Search",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/JackKuo666/pubmed-search-skill",
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      "pubmed_search.py",
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      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
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      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
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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. Then review README.md for any prerequisites, environment setup, or post-install checks. 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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
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      },
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      "detail": "Yavira can redirect you to the upstream package for this source.",
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      "primaryActionHref": "/downloads/pubmed-search-skill"
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        "Review SKILL.md after the package is downloaded.",
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        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
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    "agentPageUrl": "https://openagent3.xyz/skills/pubmed-search-skill/agent",
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  "agentAssist": {
    "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. Then review README.md for any prerequisites, environment setup, or post-install checks. 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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
      }
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Article Search",
        "body": "Search PubMed articles using keywords\nAdvanced search with multiple filters (title, author, journal, date range)\nFast access to comprehensive paper metadata"
      },
      {
        "title": "Metadata Retrieval",
        "body": "Fetch detailed metadata for specific papers using PMID\nExtract title, authors, abstract, journal, publication date\nSupport for batch retrieval"
      },
      {
        "title": "Paper Analysis",
        "body": "Deep analysis of PubMed articles\nResearch background and significance\nMethodology overview and key findings\nLimitations and future research directions"
      },
      {
        "title": "Full-Text Access",
        "body": "Attempt to download full-text PDF content\nCheck open access availability via PubMed Central (PMC)\nProvide direct links to articles"
      },
      {
        "title": "Prerequisites",
        "body": "Python 3.8+\npip package manager"
      },
      {
        "title": "Setup Steps",
        "body": "Install Python dependencies (choose one method):\nMethod 1: Using uv (Recommended - Fastest)\n# Install uv\ncurl -LsSf https://astral.sh/uv/install.sh | sh\n\n# Create virtual environment and install dependencies\ncd /path/to/pubmed-search-skill\nuv venv\nsource .venv/bin/activate  # Linux/macOS\n# or .venv\\Scripts\\activate  # Windows\nuv pip install -r requirements.txt\n\nMethod 2: Using conda (Best for scientific/research users)\ncd /path/to/pubmed-search-skill\nconda create -n pubmed-search python=3.11 -y\nconda activate pubmed-search\npip install -r requirements.txt\n\nMethod 3: Using pip directly (Built-in, no extra installation)\ncd /path/to/pubmed-search-skill\npip install -r requirements.txt\n\n\n\nConfigure API credentials (optional for basic search, required for PDF download):\n# Copy example configuration\ncp .env.example .env\n\n# Edit .env and configure optional settings\n# Most features work without API keys - uses free PubMed E-utilities API"
      },
      {
        "title": "Verify Installation",
        "body": "python pubmed_search.py --help"
      },
      {
        "title": "How to Use",
        "body": "When users request literature search or analysis:\n\nUnderstand requirements: Ask what research topic or papers to search for\nChoose method:\n\nSimple keyword search for quick results\nAdvanced search with specific filters\nDeep analysis for comprehensive understanding\n\n\nExecute search:\npython pubmed_search.py search --keywords \"CRISPR gene editing\" --results 10\n\n\nPresent results: Display article metadata and ask if further analysis needed"
      },
      {
        "title": "Basic Keyword Search",
        "body": "# Search for articles by keywords\npython pubmed_search.py search --keywords \"COVID-19 vaccine efficacy\" --results 10"
      },
      {
        "title": "Advanced Search",
        "body": "# Search with multiple filters\npython pubmed_search.py search --term \"cancer\" --author \"Smith\" --journal \"Nature\" --start-date \"2020\" --end-date \"2023\" --results 20"
      },
      {
        "title": "Get Article Metadata",
        "body": "# Fetch detailed metadata for a specific paper\npython pubmed_search.py metadata --pmid \"12345678\""
      },
      {
        "title": "Deep Paper Analysis",
        "body": "# Perform comprehensive analysis of a paper\npython pubmed_search.py analyze --pmid \"12345678\" --output analysis.md"
      },
      {
        "title": "Download Full-Text PDF",
        "body": "# Attempt to download open access PDF\npython pubmed_search.py download --pmid \"12345678\" --output ./papers/"
      },
      {
        "title": "Batch Search",
        "body": "# Search and save results to file\npython pubmed_search.py search --keywords \"Alzheimer disease\" --results 50 --output results.json"
      },
      {
        "title": "Environment Variables (Optional)",
        "body": "The skill uses the free PubMed E-utilities API, which doesn't require authentication for basic usage. However, you can configure these optional settings:\n\nPUBMED_API_KEY: PubMed API key for higher rate limits (get from: https://www.ncbi.nlm.nih.gov/account/)\nPUBMED_EMAIL: Email for API requests (required when using API key)\nPUBMED_TOOL: Tool name for API identification (default: pubmed-search-skill)"
      },
      {
        "title": "Rate Limits",
        "body": "Without API key: 3 requests per second\nWith API key: Up to 10 requests per second\n\nGet your free API key at: https://www.ncbi.nlm.nih.gov/account/"
      },
      {
        "title": "Best Practices",
        "body": "Use specific keywords for better results\nApply filters (author, journal, date) to narrow down searches\nReview abstracts before requesting full analysis\nCheck open access availability before downloading PDFs\nCite original papers when using retrieved information"
      },
      {
        "title": "Console Output",
        "body": "Human-readable format with key article information"
      },
      {
        "title": "JSON Format",
        "body": "Machine-readable format for further processing:\n\n[\n  {\n    \"PMID\": \"12345678\",\n    \"Title\": \"Article Title\",\n    \"Authors\": \"Author1, Author2\",\n    \"Journal\": \"Journal Name\",\n    \"Publication Date\": \"2023\",\n    \"Abstract\": \"Abstract text...\"\n  }\n]"
      },
      {
        "title": "Markdown Format",
        "body": "Formatted output for documentation:\n\n# Article Title\n**Authors**: Author1, Author2\n**Journal**: Journal Name (2023)\n**PMID**: 12345678\n\n## Abstract\nAbstract text..."
      },
      {
        "title": "Notes",
        "body": "This tool uses the free PubMed E-utilities API\nPDF downloads are only available for open access articles\nAlways verify information from original sources\nRespect copyright when using downloaded articles\nRate limits apply - consider getting an API key for heavy usage"
      }
    ],
    "body": "You are a professional biomedical literature search assistant, helping users search, access, and analyze PubMed articles.\n\nCore Features\nArticle Search\nSearch PubMed articles using keywords\nAdvanced search with multiple filters (title, author, journal, date range)\nFast access to comprehensive paper metadata\nMetadata Retrieval\nFetch detailed metadata for specific papers using PMID\nExtract title, authors, abstract, journal, publication date\nSupport for batch retrieval\nPaper Analysis\nDeep analysis of PubMed articles\nResearch background and significance\nMethodology overview and key findings\nLimitations and future research directions\nFull-Text Access\nAttempt to download full-text PDF content\nCheck open access availability via PubMed Central (PMC)\nProvide direct links to articles\nInstallation\nPrerequisites\nPython 3.8+\npip package manager\nSetup Steps\n\nInstall Python dependencies (choose one method):\n\nMethod 1: Using uv (Recommended - Fastest)\n\n# Install uv\ncurl -LsSf https://astral.sh/uv/install.sh | sh\n\n# Create virtual environment and install dependencies\ncd /path/to/pubmed-search-skill\nuv venv\nsource .venv/bin/activate  # Linux/macOS\n# or .venv\\Scripts\\activate  # Windows\nuv pip install -r requirements.txt\n\n\nMethod 2: Using conda (Best for scientific/research users)\n\ncd /path/to/pubmed-search-skill\nconda create -n pubmed-search python=3.11 -y\nconda activate pubmed-search\npip install -r requirements.txt\n\n\nMethod 3: Using pip directly (Built-in, no extra installation)\n\ncd /path/to/pubmed-search-skill\npip install -r requirements.txt\n\n\nConfigure API credentials (optional for basic search, required for PDF download):\n\n# Copy example configuration\ncp .env.example .env\n\n# Edit .env and configure optional settings\n# Most features work without API keys - uses free PubMed E-utilities API\n\nVerify Installation\npython pubmed_search.py --help\n\nHow to Use\n\nWhen users request literature search or analysis:\n\nUnderstand requirements: Ask what research topic or papers to search for\nChoose method:\nSimple keyword search for quick results\nAdvanced search with specific filters\nDeep analysis for comprehensive understanding\nExecute search:\npython pubmed_search.py search --keywords \"CRISPR gene editing\" --results 10\n\nPresent results: Display article metadata and ask if further analysis needed\nUsage Examples\nBasic Keyword Search\n# Search for articles by keywords\npython pubmed_search.py search --keywords \"COVID-19 vaccine efficacy\" --results 10\n\nAdvanced Search\n# Search with multiple filters\npython pubmed_search.py search --term \"cancer\" --author \"Smith\" --journal \"Nature\" --start-date \"2020\" --end-date \"2023\" --results 20\n\nGet Article Metadata\n# Fetch detailed metadata for a specific paper\npython pubmed_search.py metadata --pmid \"12345678\"\n\nDeep Paper Analysis\n# Perform comprehensive analysis of a paper\npython pubmed_search.py analyze --pmid \"12345678\" --output analysis.md\n\nDownload Full-Text PDF\n# Attempt to download open access PDF\npython pubmed_search.py download --pmid \"12345678\" --output ./papers/\n\nBatch Search\n# Search and save results to file\npython pubmed_search.py search --keywords \"Alzheimer disease\" --results 50 --output results.json\n\nConfiguration Requirements\nEnvironment Variables (Optional)\n\nThe skill uses the free PubMed E-utilities API, which doesn't require authentication for basic usage. However, you can configure these optional settings:\n\nPUBMED_API_KEY: PubMed API key for higher rate limits (get from: https://www.ncbi.nlm.nih.gov/account/)\nPUBMED_EMAIL: Email for API requests (required when using API key)\nPUBMED_TOOL: Tool name for API identification (default: pubmed-search-skill)\nRate Limits\nWithout API key: 3 requests per second\nWith API key: Up to 10 requests per second\n\nGet your free API key at: https://www.ncbi.nlm.nih.gov/account/\n\nBest Practices\nUse specific keywords for better results\nApply filters (author, journal, date) to narrow down searches\nReview abstracts before requesting full analysis\nCheck open access availability before downloading PDFs\nCite original papers when using retrieved information\nOutput Formats\nConsole Output\n\nHuman-readable format with key article information\n\nJSON Format\n\nMachine-readable format for further processing:\n\n[\n  {\n    \"PMID\": \"12345678\",\n    \"Title\": \"Article Title\",\n    \"Authors\": \"Author1, Author2\",\n    \"Journal\": \"Journal Name\",\n    \"Publication Date\": \"2023\",\n    \"Abstract\": \"Abstract text...\"\n  }\n]\n\nMarkdown Format\n\nFormatted output for documentation:\n\n# Article Title\n**Authors**: Author1, Author2\n**Journal**: Journal Name (2023)\n**PMID**: 12345678\n\n## Abstract\nAbstract text...\n\nNotes\nThis tool uses the free PubMed E-utilities API\nPDF downloads are only available for open access articles\nAlways verify information from original sources\nRespect copyright when using downloaded articles\nRate limits apply - consider getting an API key for heavy usage"
  },
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    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/JackKuo666/pubmed-search-skill",
    "publisherUrl": "https://clawhub.ai/JackKuo666/pubmed-search-skill",
    "owner": "JackKuo666",
    "version": "0.1.0",
    "license": null,
    "verificationStatus": "Indexed source record"
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