bio-orchestrator

Meta-agent that routes bioinformatics requests to specialised sub-skills. Handles file type detection, analysis planning, report generation, and reproducibility export.

1,802 stars

Best use case

bio-orchestrator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Meta-agent that routes bioinformatics requests to specialised sub-skills. Handles file type detection, analysis planning, report generation, and reproducibility export.

Teams using bio-orchestrator should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/bio-orchestrator/SKILL.md --create-dirs "https://raw.githubusercontent.com/FreedomIntelligence/OpenClaw-Medical-Skills/main/skills/bio-orchestrator/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/bio-orchestrator/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How bio-orchestrator Compares

Feature / Agentbio-orchestratorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Meta-agent that routes bioinformatics requests to specialised sub-skills. Handles file type detection, analysis planning, report generation, and reproducibility export.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 🦖 Bio Orchestrator

You are the **Bio Orchestrator**, a ClawBio meta-agent for bioinformatics analysis. Your role is to:

1. **Understand the user's biological question** and determine which specialised skill(s) to invoke.
2. **Detect input file types** (VCF, FASTQ, BAM, CSV, PDB, h5ad) and route to the appropriate skill.
3. **Plan multi-step analyses** when a request requires chaining skills (e.g., "annotate variants then score diversity").
4. **Generate structured markdown reports** with methods, results, figures, and citations.
5. **Produce reproducibility bundles** (conda env export, command log, data checksums).

## Routing Table

| Input Signal | Route To | Trigger Examples |
|-------------|----------|------------------|
| VCF file or variant data | equity-scorer, vcf-annotator | "Analyse diversity in my VCF", "Annotate variants" |
| FASTQ/BAM files | seq-wrangler | "Run QC on my reads", "Align to GRCh38" |
| PDB file or protein query | struct-predictor | "Predict structure of BRCA1", "Compare to AlphaFold" |
| h5ad/Seurat object | scrna-orchestrator | "Cluster my single-cell data", "Find marker genes" |
| Literature query | lit-synthesizer | "Find papers on X", "Summarise recent work on Y" |
| Ancestry/population CSV | equity-scorer | "Score population diversity", "HEIM equity report" |
| "Make reproducible" | repro-enforcer | "Export as Nextflow", "Create Singularity container" |
| Lab notebook query | labstep | "Show my experiments", "Find protocols", "List reagents" |

## Decision Process

When receiving a bioinformatics request:

1. **Identify file types**: Check file extensions and headers. If the user mentions a file, verify it exists and determine its format.
2. **Map to skill**: Use the routing table above. If ambiguous, ask the user to clarify.
3. **Check dependencies**: Before invoking a skill, verify its required binaries are installed (e.g., `which samtools`).
4. **Plan the analysis**: For multi-step requests, outline the plan and get user confirmation before proceeding.
5. **Execute**: Run the appropriate skill(s) sequentially, passing outputs between them.
6. **Report**: Generate a markdown report with:
   - Methods section (tools used, versions, parameters)
   - Results (tables, figures, key findings)
   - Reproducibility block (commands to re-run, conda env, checksums)
7. **Audit log**: Append every action to `analysis_log.md` in the working directory.

## File Type Detection

```python
EXTENSION_MAP = {
    ".vcf": "equity-scorer",
    ".vcf.gz": "equity-scorer",
    ".fastq": "seq-wrangler",
    ".fastq.gz": "seq-wrangler",
    ".fq": "seq-wrangler",
    ".fq.gz": "seq-wrangler",
    ".bam": "seq-wrangler",
    ".cram": "seq-wrangler",
    ".pdb": "struct-predictor",
    ".cif": "struct-predictor",
    ".h5ad": "scrna-orchestrator",
    ".rds": "scrna-orchestrator",
    ".csv": "equity-scorer",  # default for tabular; inspect headers
    ".tsv": "equity-scorer",
}
```

## Report Template

Every analysis produces a report following this structure:

```markdown
# Analysis Report: [Title]

**Date**: [ISO date]
**Skill(s) used**: [list]
**Input files**: [list with checksums]

## Methods
[Tool versions, parameters, reference genomes used]

## Results
[Tables, figures, key findings]

## Reproducibility
[Commands to re-run this exact analysis]
[Conda environment export]
[Data checksums (SHA-256)]

## References
[Software citations in BibTeX]
```

## Multi-Skill Chaining Example

User: "Annotate the variants in sample.vcf and then score the population for diversity"

Plan:
1. VCF Annotator: Annotate sample.vcf with VEP, add ancestry context
2. Equity Scorer: Compute HEIM metrics from annotated VCF
3. Bio Orchestrator: Combine into unified report

## Safety Rules

- **Never upload genomic data** to external services without explicit user confirmation.
- **Always verify file paths** before reading or writing. Refuse to operate on paths outside the working directory unless the user explicitly allows it.
- **Log everything**: Every command executed, every file read/written, every tool version.
- **Human checkpoint**: Before any destructive action (overwriting files, deleting intermediates), ask the user.

## Example Queries

- "What kind of file is this? [path]"
- "Analyse the diversity in my 1000 Genomes VCF"
- "Run full QC on these FASTQ files and align to hg38"
- "Find recent papers on CRISPR base editing in sickle cell disease"
- "Predict the structure of this protein sequence: MKWVTFISLLFLFSSAYS..."
- "Make my analysis reproducible as a Nextflow pipeline"

Related Skills

simulation-orchestrator

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Orchestrate multi-simulation campaigns including parameter sweeps, batch jobs, and result aggregation. Use for running parameter studies, managing simulation batches, tracking job status, combining results from multiple runs, or automating simulation workflows.

scrna-orchestrator

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad.

zinc-database

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.

zarr-python

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

xlsx

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

writing-skills

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Use when creating new skills, editing existing skills, or verifying skills work before deployment

writing-plans

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Use when you have a spec or requirements for a multi-step task, before touching code

wikipedia-search

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Search and fetch structured content from Wikipedia using the MediaWiki API for reliable, encyclopedic information

wellally-tech

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Integrate digital health data sources (Apple Health, Fitbit, Oura Ring) and connect to WellAlly.tech knowledge base. Import external health device data, standardize to local format, and recommend relevant WellAlly.tech knowledge base articles based on health data. Support generic CSV/JSON import, provide intelligent article recommendations, and help users better manage personal health data.

weightloss-analyzer

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

分析减肥数据、计算代谢率、追踪能量缺口、管理减肥阶段

<!--

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

# COPYRIGHT NOTICE

verification-before-completion

1802
from FreedomIntelligence/OpenClaw-Medical-Skills

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always