{ "schemaVersion": "1.0", "item": { "slug": "pharmaclaw-literature-agent", "name": "Pharmaclaw Literature Agent", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/Cheminem/pharmaclaw-literature-agent", "canonicalUrl": "https://clawhub.ai/Cheminem/pharmaclaw-literature-agent", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/pharmaclaw-literature-agent", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=pharmaclaw-literature-agent", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "SKILL.md", "scripts/biorxiv_search.py", "scripts/chain_entry.py", "scripts/chain_entry_v2.py", "scripts/clinicaltrials_search.py", "scripts/pubmed_search.py" ], "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. 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." } ] }, "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T16:55:25.780Z", "expiresAt": "2026-05-07T16:55:25.780Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null }, "scope": "source", "summary": "Source download looks usable.", "detail": "Yavira can redirect you to the upstream package for this source.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/pharmaclaw-literature-agent" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "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." ] }, "downloadPageUrl": "https://openagent3.xyz/downloads/pharmaclaw-literature-agent", "agentPageUrl": "https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent", "manifestUrl": "https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent.json", "briefUrl": "https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent.md" }, "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. 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." } ] }, "documentation": { "source": "clawhub", "primaryDoc": "SKILL.md", "sections": [ { "title": "Overview", "body": "Dual-source literature search combining PubMed (biomedical focus) and Semantic Scholar (broader CS/ML/AI coverage). Deduplicates across sources, enriches with citation metrics and TLDR summaries.\n\nKey capabilities:\n\nPubMed search with MeSH terms, abstracts, publication types\nSemantic Scholar search with citation counts, influential citations, TLDR\nPaper lookup by DOI or PMID\nCitation tracking (who cited this paper?)\nRelated paper discovery (what did this paper reference?)\nAutomatic query construction from compound/target/disease inputs\nCross-source deduplication and enrichment" }, { "title": "Quick Start", "body": "# Search by topic\npython scripts/pubmed_search.py --query \"KRAS G12C inhibitor\" --max-results 5\n\n# Search Semantic Scholar (includes ML/AI papers)\npython scripts/semantic_scholar.py --query \"graph neural network drug discovery\"\n\n# Full chain: compound + disease context\npython scripts/chain_entry.py --input-json '{\"compound\": \"sotorasib\", \"disease\": \"lung cancer\"}'\n\n# Look up a specific paper and find who cited it\npython scripts/semantic_scholar.py --paper-id \"DOI:10.1038/s41586-021-03819-2\" --citations\n\n# Recent papers only (last 3 years)\npython scripts/pubmed_search.py --query \"organometallic catalyst drug synthesis\" --years 3" }, { "title": "scripts/pubmed_search.py", "body": "PubMed via NCBI E-utilities (public, no key required, rate limit: 3 req/sec).\n\n--query Required. Search query\n--max-results 1-50 (default: 10)\n--sort relevance | date (default: relevance)\n--years Limit to last N years\n\nReturns: PMID, title, authors, journal, year, DOI, abstract, MeSH terms, keywords, publication types." }, { "title": "scripts/semantic_scholar.py", "body": "Semantic Scholar API (public, no key required, rate limit: 100 req/5 min).\n\n--query Search query\n--paper-id Paper ID (DOI:xxx, PMID:xxx, ArXiv:xxx)\n--related Get references of a paper (requires --paper-id)\n--citations Get papers citing a paper (requires --paper-id)\n--max-results 1-50 (default: 10)\n--year-range e.g., \"2020-2026\" or \"2023-\"\n\nReturns: title, authors, year, abstract, TLDR, citation count, influential citations, DOI, ArXiv ID, open-access PDF URL." }, { "title": "scripts/chain_entry.py", "body": "Standard PharmaClaw chain interface. Searches both PubMed and Semantic Scholar, deduplicates, and sorts by citation impact.\n\nInput keys: query, compound/name, target, disease, mechanism, reaction, topic, doi, pmid, max_results, years, context\n\nAutomatic query building: {\"compound\": \"aspirin\", \"disease\": \"colorectal cancer\"} → searches \"aspirin colorectal cancer\"" }, { "title": "Chaining", "body": "FromInputToChemistry QueryCompound name/SMILESLiterature → find published studiesCatalyst DesignReaction typeLiterature → find catalyst optimization papersLiteratureKey findingsPharmacology → validate claimsLiteratureSynthesis referencesChemistry Query → retrosynthesisLiteraturePatent mentionsIP Expansion → FTO analysis" } ], "body": "Literature Agent v1.0.0\nOverview\n\nDual-source literature search combining PubMed (biomedical focus) and Semantic Scholar (broader CS/ML/AI coverage). Deduplicates across sources, enriches with citation metrics and TLDR summaries.\n\nKey capabilities:\n\nPubMed search with MeSH terms, abstracts, publication types\nSemantic Scholar search with citation counts, influential citations, TLDR\nPaper lookup by DOI or PMID\nCitation tracking (who cited this paper?)\nRelated paper discovery (what did this paper reference?)\nAutomatic query construction from compound/target/disease inputs\nCross-source deduplication and enrichment\nQuick Start\n# Search by topic\npython scripts/pubmed_search.py --query \"KRAS G12C inhibitor\" --max-results 5\n\n# Search Semantic Scholar (includes ML/AI papers)\npython scripts/semantic_scholar.py --query \"graph neural network drug discovery\"\n\n# Full chain: compound + disease context\npython scripts/chain_entry.py --input-json '{\"compound\": \"sotorasib\", \"disease\": \"lung cancer\"}'\n\n# Look up a specific paper and find who cited it\npython scripts/semantic_scholar.py --paper-id \"DOI:10.1038/s41586-021-03819-2\" --citations\n\n# Recent papers only (last 3 years)\npython scripts/pubmed_search.py --query \"organometallic catalyst drug synthesis\" --years 3\n\nScripts\nscripts/pubmed_search.py\n\nPubMed via NCBI E-utilities (public, no key required, rate limit: 3 req/sec).\n\n--query Required. Search query\n--max-results 1-50 (default: 10)\n--sort relevance | date (default: relevance)\n--years Limit to last N years\n\n\nReturns: PMID, title, authors, journal, year, DOI, abstract, MeSH terms, keywords, publication types.\n\nscripts/semantic_scholar.py\n\nSemantic Scholar API (public, no key required, rate limit: 100 req/5 min).\n\n--query Search query\n--paper-id Paper ID (DOI:xxx, PMID:xxx, ArXiv:xxx)\n--related Get references of a paper (requires --paper-id)\n--citations Get papers citing a paper (requires --paper-id)\n--max-results 1-50 (default: 10)\n--year-range e.g., \"2020-2026\" or \"2023-\"\n\n\nReturns: title, authors, year, abstract, TLDR, citation count, influential citations, DOI, ArXiv ID, open-access PDF URL.\n\nscripts/chain_entry.py\n\nStandard PharmaClaw chain interface. Searches both PubMed and Semantic Scholar, deduplicates, and sorts by citation impact.\n\nInput keys: query, compound/name, target, disease, mechanism, reaction, topic, doi, pmid, max_results, years, context\n\nAutomatic query building: {\"compound\": \"aspirin\", \"disease\": \"colorectal cancer\"} → searches \"aspirin colorectal cancer\"\n\nChaining\nFrom\tInput\tTo\nChemistry Query\tCompound name/SMILES\tLiterature → find published studies\nCatalyst Design\tReaction type\tLiterature → find catalyst optimization papers\nLiterature\tKey findings\tPharmacology → validate claims\nLiterature\tSynthesis references\tChemistry Query → retrosynthesis\nLiterature\tPatent mentions\tIP Expansion → FTO analysis" }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/Cheminem/pharmaclaw-literature-agent", "publisherUrl": "https://clawhub.ai/Cheminem/pharmaclaw-literature-agent", "owner": "Cheminem", "version": "2.0.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/pharmaclaw-literature-agent", "downloadUrl": "https://openagent3.xyz/downloads/pharmaclaw-literature-agent", "agentUrl": "https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent", "manifestUrl": "https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent.json", "briefUrl": "https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent.md" } }