Biomedical Analysis Dispatch

SkillProductivity

Dispatch biomedical research and data analysis tasks to Claude Code with K-Dense Scientific Skills. Use this skill when the user asks to run any bioinformatics, genomics, drug discovery, clinical data analysis, proteomics, multi-omics, medical imaging, or scientific computation task. Also use for literature search (PubMed, bioRxiv), pathway analysis, protein structure prediction, or scientific writing tasks.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Biomedical Analysis Dispatch skill

What this skill tells your AI

The instructions your AI receives, as published by zaoqu-liu/scienceclaw in skills/medge-biomed-dispatch/SKILL.md and read by ahel’s review.

Purpose

Bridge between the OpenClaw conversational interface and Claude Code's scientific execution environment (K-Dense Scientific Skills).

When to use

  • Any bioinformatics task: RNA-seq, scRNA-seq, variant calling, sequence analysis
  • Drug discovery: molecular docking, virtual screening, ADMET prediction
  • Clinical data: survival analysis, variant interpretation, clinical trials search
  • Multi-omics: proteomics, metabolomics, pathway enrichment
  • Medical imaging: DICOM processing, digital pathology
  • Scientific communication: literature review, scientific writing, figure generation
  • Any request mentioning specific tools: DESeq2, Seurat, Scanpy, RDKit, BioPython, etc.

Workflow

  1. Identify task type from the user's request
  2. Locate data files — check if user mentioned a file path; if not, list /workspace/data/ and confirm with user
  3. Set up Dashboard — every analysis task must have a live dashboard:
    TASK_DIR=data/<task_name>
    mkdir -p "$TASK_DIR/dashboard" "$TASK_DIR/output"
    cp skills/dashboard/dashboard.html "$TASK_DIR/dashboard/"
    cp skills/dashboard/dashboard_serve.py "$TASK_DIR/dashboard/"
    # Write initial state.json with: progress(0%), 研究概要, 分析计划(list), empty steps
    # Start server
    python "$TASK_DIR/dashboard/dashboard_serve.py" --port <free_port> &
    # Tell user the URL immediately: http://localhost:<port>/dashboard/dashboard.html
    
  4. Construct the Claude Code prompt — include dashboard update instructions:
    • Which scientific skill(s) to use
    • Input file path(s)
    • Output directory: always $TASK_DIR/output/
    • Dashboard state.json path and update expectations:
      • Update progress after each step
      • Use step panels with desc, code, code_file, outputs
      • Use {"src": "/output/file.csv"} for table references (NOT inline data)
      • Image paths absolute: /output/fig1.png
    • Expected output format (table, figure, report)
  5. Execute via Claude Code CLI:
    claude --dangerously-skip-permissions -p "Use available scientific skills. [TASK]. Input: [PATH]. Outputs: $TASK_DIR/output/. Update dashboard at $TASK_DIR/dashboard/state.json after each step (step panels with code + outputs). Completion: openclaw system event --text 'Done: summary' --mode now"
    
  6. Monitor — if the task takes >30s, inform the user it is running in background
  7. Report back — summarize results, point user to dashboard URL for details

Output handling

  • Tables → summarize top rows, mention full file path
  • Figures → send the image file to the user directly
  • Reports → send the PDF/HTML file to the user directly
  • Errors → show the error message and suggest a fix

Example dispatches

Clinical data analysis (complete flow with dashboard):

# 1. Setup
TASK_DIR=data/charls_ace
mkdir -p "$TASK_DIR/dashboard" "$TASK_DIR/output"
cp skills/dashboard/dashboard.html "$TASK_DIR/dashboard/"
cp skills/dashboard/dashboard_serve.py "$TASK_DIR/dashboard/"
# 2. Write initial state.json
# 3. Start dashboard server
python "$TASK_DIR/dashboard/dashboard_serve.py" --port 7790 &
# 4. Dispatch to Claude Code
claude --dangerously-skip-permissions -p "分析 CHARLS 队列中 ACE 与 CVD 的关联。Input: data/charls_ace/charls.dta. Output: data/charls_ace/output/. 每步更新 dashboard state.json(step panels with code + outputs)。完成后: openclaw system event --text 'Done: ACE-CVD分析完成' --mode now"

RNA-seq differential expression:

claude --dangerously-skip-permissions -p "Use DESeq2 scientific skill. Run differential expression. Counts: /workspace/data/counts.csv, metadata: /workspace/data/meta.csv, contrast: treatment vs control. Save to /workspace/data/rnaseq/output/. Update dashboard at /workspace/data/rnaseq/dashboard/state.json."

Single-cell RNA-seq:

claude --dangerously-skip-permissions -p "Use Scanpy scientific skill. Analyze 10X data at /workspace/data/10x/. QC, clustering, markers. Save to /workspace/data/10x/output/. Update dashboard state.json with step panels."

Important rules

  • Always save outputs to /workspace/outputs/ — never to /workspace/data/
  • Never modify raw data files in /workspace/data/
  • If the user's request is ambiguous, ask one clarifying question before dispatching
  • If Claude Code returns an error about a missing package, retry with uv pip install [package] prepended to the command
  • 涉及中文可视化时,在 prompt 中加入:绘图前先导入 skills/cjk-viz/scripts/setup_cjk_font.py 执行字体检测,不要硬编码字体名

Signals

GitHub stars
60
Forks
14
Last commit
Mar 2026

ahel review

  • K1binfo
    installs-packages

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Catalog kind
skill
Gateway key
biomed-dispatch
Source
github.com/zaoqu-liu/scienceclaw