{ "schemaVersion": "1.0", "item": { "slug": "scholar-research", "name": "Scholar Research", "source": "tencent", "type": "skill", "category": "开发巄具", "sourceUrl": "https://clawhub.ai/jcheng67/scholar-research", "canonicalUrl": "https://clawhub.ai/jcheng67/scholar-research", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/scholar-research", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=scholar-research", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "README.md", "SKILL.md", "_meta.json", "config.json", "pyproject.toml", "references/apis.md" ], "primaryDoc": "SKILL.md", "quickSetup": [ "Download the package from Yavira.", "Extract the archive and review SKILL.md first.", "Import or place the package into your OpenClaw setup." ], "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. 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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." } ] }, "documentation": { "source": "clawhub", "primaryDoc": "SKILL.md", "sections": [ { "title": "Scholar Research Skill", "body": "Search and analyze academic papers from open access sources with credibility scoring and detailed summaries." }, { "title": "When to Use", "body": "User wants to find papers on a specific topic\nUser needs credibility assessment of papers\nUser wants summarized research with methodology\nUser wants to track field evolution over time\nUser needs figures/tables extracted from top papers" }, { "title": "Data Sources (Free/Open Access)", "body": "The skill searches across these sources:\n\narXiv - Pre-prints (Physics, Math, CS, q-bio, q-fin)\nPubMed/PMC - Biomedical & Life sciences\nDOAJ - Peer-reviewed OA journals (all disciplines)\nOpenAlex - 250M+ papers metadata\nCORE - Largest OA full-text aggregator\nSemantic Scholar - Limited free tier\nUnpaywall - Finds free versions of paywalled papers\nCrossRef - All DOI metadata\nbioRxiv - Biology pre-prints\nmedRxiv - Medicine pre-prints\nZenodo - EU research data/papers\nHAL - French OA repository\nJ-STAGE - Japanese OA repository\nSSRN - Economics, Law pre-prints" }, { "title": "User-Added Sources", "body": "Users can add custom sources via config:\n\n{\n \"custom_sources\": [\n {\"name\": \"My University\", \"url\": \"https://repo.my.edu\", \"api\": \"...\"}\n ]\n}" }, { "title": "Default Weights (Total: 100 + 40 bonus)", "body": "Paper Quality (100 points):\n\nFactorWeightDescriptioncitation_count15%Times cited by other paperspublication_recency10%Newer = more relevantauthor_reputation12%Combined h-index of authorsjournal_impact12%Impact factor, CiteScorepeer_review_status10%Peer-reviewed vs pre-printopen_access8%Free to read/downloadretraction_status10%Not retractedauthor_network8%Connected to established networkfunder_acknowledgment5%Clear funding sourcesreproducibility5%Code/data available\n\nBonus Points (up to +40):\n\nAuthor Trust: +20 max\nJournal Reputation: +20 max" }, { "title": "Customizing Weights", "body": "Users can modify weights in config:\n\n{\n \"scoring\": {\n \"citation_count\": 25,\n \"publication_recency\": 5\n }\n}\n\nOr use preset profiles: \"strict\", \"recent_only\", \"balanced\"" }, { "title": "Top Papers (default: 5, user-configurable)", "body": "[1] Paper Title (Year)\n Score: 95/100 | Citations: 234\n šŸ“„ PDF | šŸ“Š Figures | šŸ”¬ SI\n \n Summary: [One paragraph]\n \n Methodology: [Detailed breakdown]" }, { "title": "Field Timeline", "body": "šŸ“ˆ FIELD TIMELINE (N papers)\n\n2024: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 15 papers\n ā†’ Major: [Breakthrough 1]\n ā†’ Trend: [Trend 1]\n\n2023: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 12 papers\n ā†’ Major: [Breakthrough 2]" }, { "title": "Credibility Distribution", "body": "šŸ“Š Credibility Distribution\n\nScore 90-100: ā–ˆā–ˆ (5) ā˜… Top\nScore 70-89: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ (15)\nScore 50-69: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ (25)\nScore 30-49: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ (10)\nScore 0-29: ā–ˆā–ˆ (2)\n\n[ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–‘ā–‘ā–‘ā–‘ā–‘ā–‘ā–‘ā–‘ā–‘] Average: 58/100" }, { "title": "Workflow", "body": "Search: Query across all enabled sources\nFetch: Download metadata + PDFs\nScore: Calculate credibility scores\nSort: Rank by score + relevance\nPresent: Top N papers + timeline\nExtract: Figures from top-scored papers (optional)" }, { "title": "Usage Examples", "body": "Find papers on: machine learning\nFields: computer science, AI\nTop papers: 5\nExtract figures: true\n\nFind papers on: quantum computing\nFields: physics\nTop papers: 10\nExtract figures: false" }, { "title": "Dependencies", "body": "Python 3.8+\nrequests (API calls)\nbeautifulsoup4 (parsing)\npypdf2 (PDF extraction)\nopencv-python (figure detection)\ntransformers (summarization)\nmatplotlib (visualization)" }, { "title": "Configuration", "body": "See config.json for:\n\nAPI keys\nSource enable/disable\nScoring weights\nDisplay preferences\nCustom sources" }, { "title": "Notes", "body": "Always prioritize open access sources\nCite sources in responses\nWarn about pre-print limitations\nCheck retraction status when available\nRespect rate limits" } ], "body": "Scholar Research Skill\n\nSearch and analyze academic papers from open access sources with credibility scoring and detailed summaries.\n\nWhen to Use\nUser wants to find papers on a specific topic\nUser needs credibility assessment of papers\nUser wants summarized research with methodology\nUser wants to track field evolution over time\nUser needs figures/tables extracted from top papers\nData Sources (Free/Open Access)\n\nThe skill searches across these sources:\n\narXiv - Pre-prints (Physics, Math, CS, q-bio, q-fin)\nPubMed/PMC - Biomedical & Life sciences\nDOAJ - Peer-reviewed OA journals (all disciplines)\nOpenAlex - 250M+ papers metadata\nCORE - Largest OA full-text aggregator\nSemantic Scholar - Limited free tier\nUnpaywall - Finds free versions of paywalled papers\nCrossRef - All DOI metadata\nbioRxiv - Biology pre-prints\nmedRxiv - Medicine pre-prints\nZenodo - EU research data/papers\nHAL - French OA repository\nJ-STAGE - Japanese OA repository\nSSRN - Economics, Law pre-prints\nUser-Added Sources\n\nUsers can add custom sources via config:\n\n{\n \"custom_sources\": [\n {\"name\": \"My University\", \"url\": \"https://repo.my.edu\", \"api\": \"...\"}\n ]\n}\n\nScoring System\nDefault Weights (Total: 100 + 40 bonus)\n\nPaper Quality (100 points):\n\nFactor\tWeight\tDescription\ncitation_count\t15%\tTimes cited by other papers\npublication_recency\t10%\tNewer = more relevant\nauthor_reputation\t12%\tCombined h-index of authors\njournal_impact\t12%\tImpact factor, CiteScore\npeer_review_status\t10%\tPeer-reviewed vs pre-print\nopen_access\t8%\tFree to read/download\nretraction_status\t10%\tNot retracted\nauthor_network\t8%\tConnected to established network\nfunder_acknowledgment\t5%\tClear funding sources\nreproducibility\t5%\tCode/data available\n\nBonus Points (up to +40):\n\nAuthor Trust: +20 max\nJournal Reputation: +20 max\nCustomizing Weights\n\nUsers can modify weights in config:\n\n{\n \"scoring\": {\n \"citation_count\": 25,\n \"publication_recency\": 5\n }\n}\n\n\nOr use preset profiles: \"strict\", \"recent_only\", \"balanced\"\n\nOutput Format\nTop Papers (default: 5, user-configurable)\n[1] Paper Title (Year)\n Score: 95/100 | Citations: 234\n šŸ“„ PDF | šŸ“Š Figures | šŸ”¬ SI\n \n Summary: [One paragraph]\n \n Methodology: [Detailed breakdown]\n\nField Timeline\nšŸ“ˆ FIELD TIMELINE (N papers)\n\n2024: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 15 papers\n ā†’ Major: [Breakthrough 1]\n ā†’ Trend: [Trend 1]\n\n2023: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ 12 papers\n ā†’ Major: [Breakthrough 2]\n\nCredibility Distribution\nšŸ“Š Credibility Distribution\n\nScore 90-100: ā–ˆā–ˆ (5) ā˜… Top\nScore 70-89: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ (15)\nScore 50-69: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ (25)\nScore 30-49: ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆ (10)\nScore 0-29: ā–ˆā–ˆ (2)\n\n[ā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–ˆā–‘ā–‘ā–‘ā–‘ā–‘ā–‘ā–‘ā–‘ā–‘] Average: 58/100\n\nWorkflow\nSearch: Query across all enabled sources\nFetch: Download metadata + PDFs\nScore: Calculate credibility scores\nSort: Rank by score + relevance\nPresent: Top N papers + timeline\nExtract: Figures from top-scored papers (optional)\nUsage Examples\nFind papers on: machine learning\nFields: computer science, AI\nTop papers: 5\nExtract figures: true\n\nFind papers on: quantum computing\nFields: physics\nTop papers: 10\nExtract figures: false\n\nDependencies\nPython 3.8+\nrequests (API calls)\nbeautifulsoup4 (parsing)\npypdf2 (PDF extraction)\nopencv-python (figure detection)\ntransformers (summarization)\nmatplotlib (visualization)\nConfiguration\n\nSee config.json for:\n\nAPI keys\nSource enable/disable\nScoring weights\nDisplay preferences\nCustom sources\nNotes\nAlways prioritize open access sources\nCite sources in responses\nWarn about pre-print limitations\nCheck retraction status when available\nRespect rate limits" }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/jcheng67/scholar-research", "publisherUrl": "https://clawhub.ai/jcheng67/scholar-research", "owner": "jcheng67", "version": "1.0.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/scholar-research", "downloadUrl": "https://openagent3.xyz/downloads/scholar-research", "agentUrl": "https://openagent3.xyz/skills/scholar-research/agent", "manifestUrl": "https://openagent3.xyz/skills/scholar-research/agent.json", "briefUrl": "https://openagent3.xyz/skills/scholar-research/agent.md" } }