start
Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
获取
https://deepseekmodel.com/api/download.php?id=anthropics-knowledge-work-plugins-bio-research-skills-start-skill-md&format=skill
下载 .skill
标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name start description Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project. Bio-Research Start If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md . You are helping a biological researcher get oriented with the bio-research plugin. Walk through the following steps in order. Step 1: Welcome Display this welcome message: Bio-Research Plugin Your AI-powered research assistant for the life sciences. This plugin brings together literature search, data analysis pipelines, and scientific strategy — all in one place. Step 2: Check Available MCP Servers Test which MCP servers are connected by listing available tools. Group the results: Literature & Data Sources: ~~literature database — biomedical literature search ~~literature database — preprint access (biology and medicine) ~~journal access — academic publications ~~data repository — collaborative research data (Sage Bionetworks) Drug Discovery & Clinical: ~~chemical database — bioactive compound database ~~drug target database — drug target discovery platform ClinicalTrials.gov — clinical trial registry ~~clinical data platform — clinical trial site ranking and platform help Visualization & AI: ~~scientific illustration — create scientific figures and diagrams ~~AI research platform — AI for biology (histopathology, drug discovery) Report which servers are connected and which are not yet set up. Step 3: Survey Available Skills List the analysis skills available in this plugin: Skill What It Does Single-Cell RNA QC Quality control for scRNA-seq data with MAD-based filtering scvi-tools Deep learning for single-cell omics (scVI, scANVI, totalVI, PeakVI, etc.) Nextflow Pipelines Run nf-core pipelines (RNA-seq, WGS/WES, ATAC-seq) Instrument Data Converter Convert lab instrument output to Allotrope ASM format Scientific Problem Selection Systematic framework for choosing research problems Step 4: Optional Setup — Binary MCP Servers Mention that two additional MCP servers are available as separate installations: ~~genomics platform — Access cloud analysis data and workflows Install: Download txg-node.mcpb from https://github.com/10XGenomics/txg-mcp/releases ~~tool database (Harvard MIMS) — AI tools for scientific discovery Install: Download tooluniverse.mcpb from https://github.com/mims-harvard/ToolUniverse/releases These require downloading binary files and are optional. Step 5: Ask How to Help Ask the researcher what they're working on today. Suggest starting points based on common workflows: Literature review — "Search ~~literature database for recent papers on [topic]" Analyze sequencing data — "Run QC on my single-cell data" or "Set up an RNA-seq pipeline" Drug discovery — "Search ~~chemical database for compounds targeting [protein]" or "Find drug targets for [disease]" Data standardization — "Convert my instrument data to Allotrope format" Research strategy — "Help me evaluate a new project idea" Wait for the user's response and guide them to the appropriate tools and skills.
Agent 识别该技能的关键词,点击任意一个即可复制。
该技能未提供触发词。
下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |