菜单
Configure Model Context Protocol (MCP) servers and customize Tandem skills for your organization.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.
Strategic scientific problem selection, project ideation, and troubleshooting based on the Fischbach & Walsh framework.
Deep learning for single-cell analysis using scvi-tools and scverse ecosystem. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping, (7) RNA velocity with veloVI, or (8) QC analysis of single-cell RNA-seq data. Triggers include scVI, scANVI, totalVI, QC, quality control, batch correction, integration, multi-modal.
A conversational framework for systematic scientific problem selection, project ideation, troubleshooting, and strategic decision making.
| name | cowork-mcp-config-assistant |
| description | Configure Model Context Protocol (MCP) servers and customize Tandem skills for your organization. |
| requires | ["python","node"] |
Adapt Tandem skills to your specific organization by replacing customization points with actual tool names, configuring MCP servers, and applying organization-specific customizations.
Some skills use placeholders (e.g., ~~Jira, ~~your-team-channel) that need to be replaced with your actual tools and values. This assistant helps you identify these points and configure the necessary MCP servers to connect Tandem to your data.
To connect Tandem to your tools, you need to configure MCP servers.
Common MCP Servers:
SKILL.md files to use your specific tool names.jira.company.com).npm install or pip install).Example Config Entry:
"github": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-github"],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "your-token-here"
}
}