Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add patsnap/mcp --skill patsnap-scientific-translational-evidencegit clone --depth 1 https://github.com/patsnap/mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/patsnap/mcp/patsnap-scientific-translational-evidence)<a href="https://agentmods.dev/skills/patsnap/mcp/patsnap-scientific-translational-evidence"><img src="https://agentmods.dev/badge/skills/patsnap/mcp/patsnap-scientific-translational-evidence/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/patsnap/mcp/patsnap-scientific-translational-evidence"><img src="https://agentmods.dev/badge/skills/patsnap/mcp/patsnap-scientific-translational-evidence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.00673 |
| Opus 5 | $0.00023 | $0.00336 |
| Sonnet 5 | $0.00009 | $0.00135 |
| Haiku 4.5 | $0.00005 | $0.00067 |
Grade A, and why
patsnap-scientific-translational-evidence scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup
Get your API Key at https://open.patsnap.com
Patsnap Scientific & Translational Evidence
This skill connects your AI agent to Patsnap's Scientific & Translational Evidence MCP server — providing professional-grade life sciences intelligence.
Retrieval platform focusing on scientific literature and translational outcomes, covering academic publication queries and translational medicine record tracking.
Prerequisites
This skill requires the Patsnap Scientific & Translational Evidence MCP server to be configured in your environment:
{
"mcpServers": {
"scientific_translational_evidence": {
"url": "https://connect.patsnap.com/9c333c/logic-mcp?apikey=YOUR_API_KEY",
"type": "streamableHttp"
}
}
}
Get your API key at open.patsnap.com. For the full list of available tools and input parameters, refer to the official MCP server documentation: https://open.patsnap.com/marketplace/mcp-servers/scientific-translational-evidence
Instructions for AI Agents
Step 1: Normalize Entities First
Before executing any search or fetch operation, normalize targets, drugs, diseases, companies, and clinical trial IDs to Patsnap internal IDs when possible. This improves retrieval accuracy.
Step 2: Choose the Right Tool
Select search tools for discovery and corresponding _fetch tools for full records. Use vector search tools for natural-language evidence queries.
Step 3: Fetch Full Records
Search tools return summary results with IDs. Follow up with the appropriate _fetch tool when the user needs complete details.
Step 4: Synthesize and Structure Output
Lead with key findings, cite sources, highlight data gaps, and use tables for comparisons.
Example Workflows
Translational Evidence Review
- Search
translational_medicine_searchby target and disease. - Fetch full records with
translational_medicine_fetch. - Synthesize biomarker and mechanism-of-action insights.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 72 lines · 47 tokens per session scan A c3824ec8ed65
patsnap-scientific-translational-evidence is a skill published in the GitHub repository patsnap/mcp (111 stars, last pushed 23d ago), licensed Apache-2.0. It adds 47 tokens to every session and 673 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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