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biomed-dispatch

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.

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xjtulyc/MedgeClaw617 stars(GitHub 617 + cccskills 0)

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Biomedical Analysis Dispatch

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. 拆分长任务 — 如果任务包含多个阶段(如:文献搜索 + 写大纲 + 写正文 + 做图 + 编译),必须拆成多个 Claude Code session,每个 session 只做一件事:
    • Phase 1: 文献搜索 + 大纲
    • Phase 2: 写正文(或分章节)
    • Phase 3: 生成图表
    • Phase 4: 编译 PDF
    • 原因: 单次 CC session 超过 10 分钟大概率卡住(上下文窗口满、API 超时、生成超长文本)
  5. Construct the Claude Code prompt — 短而聚焦,包含 dashboard 更新指令:
    • Which scientific skill(s) to use(明确指定 skill 路径,如 先读 ~/next-medgeai/MedgeClaw/scientific-skills/scientific-skills/scientific-writing/SKILL.md)
    • Input file path(s)
    • Output directory: always $TASK_DIR/output/
    • Dashboard state.json path and update expectations:
      • Update progress after each step
      • Use step panels with desc, code, code_file, outputs
      • Use {"src": "/output/file.csv"} for table references (NOT inline data)
      • Image paths absolute: /output/fig1.png
    • Expected output format (table, figure, report)
  6. Execute via Claude Code CLI(推荐 stream-json + hooks):
    # 推荐:stream-json 模式(可观测)
    cd "$TASK_DIR" && claude -p "短任务描述。先读 skill 文件。完成后: openclaw system event --text 'Done: 摘要' --mode now" \
      --output-format stream-json \
      --verbose \
      --dangerously-skip-permissions \
      2>/dev/null | tail -1
    
    # 旧方式(不推荐,无可观测性)
    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"
    
  7. Monitor — 用 hooks 的 progress.json 判断进度:
    • 如果 last_update 超过 5 分钟没变 → 大概率卡了,kill 掉重来
    • 如果任务 >30s,告知用户后台运行中
  8. Report back — 总结结果,指向 dashboard URL

科学写作任务的特殊处理

文献综述 / 论文写作必须拆分:

# Phase 1: 文献搜索 + 大纲(5-10 分钟)
cd writing_outputs/<task_name> && claude -p "读 ~/next-medgeai/MedgeClaw/scientific-skills/scientific-skills/literature-review/SKILL.md 和 scientific-writing/SKILL.md。按 literature-review 流程搜索文献,创建 outline.md(Stage 1)。" \
  --output-format stream-json --verbose --dangerously-skip-permissions 2>/dev/null | tail -1

# Phase 2: 写正文(分章节,每章 5-10 分钟)
cd writing_outputs/<task_name> && claude -p "读 outline.md 的第 1-3 节。用 Edit 工具在 manuscript.tex 中补充这些章节的正文。写完整的学术散文。" \
  --output-format stream-json --verbose --dangerously-skip-permissions 2>/dev/null | tail -1

# Phase 3: 创建 BibTeX + 添加引用(5 分钟)
cd writing_outputs/<task_name> && claude -p "读 manuscript.tex 和 outline.md。创建 references/references.bib(至少 30 篇),在 tex 中添加 \cite{}(每节至少 5 处),在 \end{document} 前加 \bibliographystyle{unsrt} 和 \bibliography{references}。" \
  --output-format stream-json --verbose --dangerously-skip-permissions 2>/dev/null | tail -1

# Phase 4: 生成图表(5-10 分钟)
cd writing_outputs/<task_name> && claude -p "在 figures/ 下创建 5 个 Python 脚本生成图表 PDF。中文标签用 Noto Sans CJK SC 字体。" \
  --output-format stream-json --verbose --dangerously-skip-permissions 2>/dev/null | tail -1

# Phase 5: 编译 PDF(手动或简单 CC)
cd writing_outputs/<task_name>/drafts && xelatex -output-directory=../final manuscript.tex
cd ../final && bibtex manuscript && cd ../drafts && xelatex -output-directory=../final manuscript.tex && xelatex -output-directory=../final manuscript.tex

为什么必须拆分:

  • 单次让 CC 做完所有步骤(搜文献 + 写大纲 + 写正文 + 做图 + 编译)会导致:
    • 上下文窗口满(74 篇摘要 + task.md + skill 文件 + LaTeX 模板 = 超大上下文)
    • Opus 生成超长 LaTeX 文本(数千 token)需要 10+ 分钟,容易超时
    • 中途卡住后无法恢复,只能重来
  • 拆分后每个 phase 独立,失败了只需重跑该 phase

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."

输出路径约束(重要)

所有任务输出必须写入指定目录:

任务类型输出路径说明
数据分析data/<task_name>/output/CSV、图表、报告
Dashboarddata/<task_name>/dashboard/state.json, dashboard.html, serve.py
科学写作writing_outputs/<date>_<topic>/LaTeX、PDF、BibTeX、figures/
临时文件data/<task_name>/temp/中间产物

禁止写入:

  • ❌ 项目根目录(~/next-medgeai/MedgeClaw/)
  • ❌ /workspace/outputs/(已废弃)
  • ❌ /workspace/data/(只读,用户输入数据)

Important rules

  • 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

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