# Send Pharmaclaw Literature Agent to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- 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.
## Suggested prompts
### New install

```text
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.
```
### Upgrade existing

```text
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.
```
## Machine-readable fields
```json
{
  "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": {
    "downloadUrl": "/downloads/pharmaclaw-literature-agent",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=pharmaclaw-literature-agent",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "SKILL.md",
      "scripts/biorxiv_search.py",
      "scripts/chain_entry.py",
      "scripts/chain_entry_v2.py",
      "scripts/clinicaltrials_search.py",
      "scripts/pubmed_search.py"
    ],
    "downloadMode": "redirect",
    "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."
      ]
    }
  },
  "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"
  }
}
```
## Documentation

### Overview

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.

Key capabilities:

PubMed search with MeSH terms, abstracts, publication types
Semantic Scholar search with citation counts, influential citations, TLDR
Paper lookup by DOI or PMID
Citation tracking (who cited this paper?)
Related paper discovery (what did this paper reference?)
Automatic query construction from compound/target/disease inputs
Cross-source deduplication and enrichment

### Quick Start

# Search by topic
python scripts/pubmed_search.py --query "KRAS G12C inhibitor" --max-results 5

# Search Semantic Scholar (includes ML/AI papers)
python scripts/semantic_scholar.py --query "graph neural network drug discovery"

# Full chain: compound + disease context
python scripts/chain_entry.py --input-json '{"compound": "sotorasib", "disease": "lung cancer"}'

# Look up a specific paper and find who cited it
python scripts/semantic_scholar.py --paper-id "DOI:10.1038/s41586-021-03819-2" --citations

# Recent papers only (last 3 years)
python scripts/pubmed_search.py --query "organometallic catalyst drug synthesis" --years 3

### scripts/pubmed_search.py

PubMed via NCBI E-utilities (public, no key required, rate limit: 3 req/sec).

--query <text>          Required. Search query
--max-results <N>       1-50 (default: 10)
--sort <type>           relevance | date (default: relevance)
--years <N>             Limit to last N years

Returns: PMID, title, authors, journal, year, DOI, abstract, MeSH terms, keywords, publication types.

### scripts/semantic_scholar.py

Semantic Scholar API (public, no key required, rate limit: 100 req/5 min).

--query <text>          Search query
--paper-id <id>         Paper ID (DOI:xxx, PMID:xxx, ArXiv:xxx)
--related               Get references of a paper (requires --paper-id)
--citations             Get papers citing a paper (requires --paper-id)
--max-results <N>       1-50 (default: 10)
--year-range <range>    e.g., "2020-2026" or "2023-"

Returns: title, authors, year, abstract, TLDR, citation count, influential citations, DOI, ArXiv ID, open-access PDF URL.

### scripts/chain_entry.py

Standard PharmaClaw chain interface. Searches both PubMed and Semantic Scholar, deduplicates, and sorts by citation impact.

Input keys: query, compound/name, target, disease, mechanism, reaction, topic, doi, pmid, max_results, years, context

Automatic query building: {"compound": "aspirin", "disease": "colorectal cancer"} → searches "aspirin colorectal cancer"

### Chaining

FromInputToChemistry QueryCompound name/SMILESLiterature → find published studiesCatalyst DesignReaction typeLiterature → find catalyst optimization papersLiteratureKey findingsPharmacology → validate claimsLiteratureSynthesis referencesChemistry Query → retrosynthesisLiteraturePatent mentionsIP Expansion → FTO analysis
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: Cheminem
- Version: 2.0.0
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-30T16:55:25.780Z
- Expires at: 2026-05-07T16:55:25.780Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/pharmaclaw-literature-agent)
- [Send to Agent page](https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent)
- [JSON manifest](https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/pharmaclaw-literature-agent/agent.md)
- [Download page](https://openagent3.xyz/downloads/pharmaclaw-literature-agent)