start
GitHub引导生物研究员熟悉插件环境，检查MCP服务器连接状态，列举可用分析技能（如单细胞测序、药物发现），并提示可选的二进制工具安装，最后询问用户具体研究需求。
Trigger Scenarios
Install
npx skills add anthropics/knowledge-work-plugins --skill start -g -y
SKILL.md
Frontmatter
{
"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.mcpbfrom https://github.com/10XGenomics/txg-mcp/releases - ~~tool database (Harvard MIMS) — AI tools for scientific discovery
Install: Download
tooluniverse.mcpbfrom 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.
Version History
- 6f13415 Current 2026-07-05 18:27
