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Agent skill

Bio Orchestrator

by ClawBio in ClawBio/ClawBio

Meta-agent that routes bioinformatics requests to specialised sub-skills.

MITAuto-check passedResearch & Science

Install Bio Orchestrator

skills CLI
$ npx skills add ClawBio/ClawBio --skill bio-orchestrator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ClawBio/ClawBio bio-orchestrator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bio-orchestrator .claude/skills/bio-orchestrator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bio-orchestrator
GitHub stars
1.2k
Used in
3 other repos
Token cost
~2.5k tokens
SKILL.md length
1,043 words
Files
4
Skills in repo
104
Repo updated
First seen
Licence
MIT

At a glance

Meta-agent that routes bioinformatics requests to specialised sub-skills.

  • Works in 5 steps: Understand the user's biological… → Detect input file types (VCF, FASTQ,… → Plan multi-step analyses when a request… → …
  • Tasks that involve Bioinformatics
  • SKILL.md covers Routing Table, Decision Process, File Type Detection and Report Template, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Bio Orchestrator is an agent skill from ClawBio/ClawBio. Meta-agent that routes bioinformatics requests to specialised sub-skills. Handles file type detection, analysis planning, report generation, and reproducibility export.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `orchestrator.py`, `tests/test_orchestrator.py` and `tests/test_skill_intents.py`).

It sits in Research & Science, covering Bioinformatics and Reproducible research. The repository describes itself as: 🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free. The licence is MIT.

When your agent uses it

  • Tasks that involve Bioinformatics
  • Tasks that involve Reproducible research

Example prompts

  • “/bio-orchestrator”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  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).

What it can do on your machine

Read from SKILL.md and the folder at commit dece754. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bio Orchestrator loads about 2.5k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 1,043 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ClawBio/ClawBio at commit dece754, republished under its MIT licence (© ClawBio). 1,043 words, ~2,512 tokens.

Download SKILL.mdSave it as .claude/skills/bio-orchestrator/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
bio-orchestrator
description
Meta-agent that routes bioinformatics requests to specialised sub-skills. Handles file type detection, analysis planning, report generation, and reproducibility export.
license
MIT
metadata.version
0.1.0

🦖 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 SignalRoute ToTrigger Examples
VCF file or variant dataequity-scorer, vcf-annotator"Analyse diversity in my VCF", "Annotate variants"
Aligned FASTA/NEXUS or multi-sample VCF + population-genetics statisticdnasp"Compute Tajima's D on this alignment", "Nucleotide diversity per population", "McDonald-Kreitman test with an outgroup"
Illumina/DRAGEN export bundleillumina-bridge"Import this DRAGEN bundle", "Parse this SampleSheet and VCF export"
FASTQ/BAM filesseq-wrangler"Run QC on my reads", "Align to GRCh38"
PDB file or protein querystruct-predictor"Predict structure of BRCA1", "Compare to AlphaFold"
h5ad/10x Matrix Market inputscrna-orchestrator"Cluster my single-cell data", "Find marker genes"
scVI / scANVI / latent integration requestscrna-embedding"Run scVI on my h5ad", "Run scANVI on my labeled h5ad", "Batch-correct this dataset", "Build a latent embedding"
Bulk RNA-seq counts + metadatarnaseq-de"Run DESeq2 on this count matrix", "volcano plot for treated vs control"
integrated.h5ad / X_scvi downstream requestscrna-orchestrator"Use integrated.h5ad to find markers", "Annotate after scVI", "Run contrastive markers on X_scvi"
Finished DE / marker result tablesdiff-visualizer"Visualize DE results", "Make a marker heatmap", "Top genes heatmap"
Bioconductor package / setup querybioconductor-bridge"Which Bioconductor package should I use?", "Set up Bioconductor", "What does AnnotationHub do?"
Literature querylit-synthesizer"Find papers on X", "Summarise recent work on Y"
Ancestry/population CSVequity-scorer"Score population diversity", "HEIM equity report"
OT colocalisation row or (gene, exposure_qtl, outcome_gwas, lead_variant) tuplemr-region-run -> locuscompare-region-render"Compute MR and render locuscompare for SORT1 in liver eQTL vs LDL-C", "Replicate this Open Targets coloc row with a regional plot", "Wald-ratio MR for an eQTL x GWAS coloc and overlay it on the LocusCompare diagnostic"
"Make reproducible"repro-enforcer"Export as Nextflow", "Create Singularity container"
Image file (PNG/JPG/TIFF)data-extractor"Extract data from this figure", "Digitize this bar chart"
Lab notebook querylabstep"Show my experiments", "Find protocols", "List reagents"
FASTA / DNA sequence + promoter questiongi-promoter"Predict promoters in this sequence", "Find TSS", "Is this a promoter?"
FASTA / gene body + splice questiongi-splice"Predict splice sites", "Find splice donors / acceptors", "Score cryptic splice sites"
FASTA / DNA sequence + enhancer questiongi-enhancer"Predict enhancer activity", "Score this for cis-regulatory function", "DeepSTARR / STARR-seq prediction"
FASTA / DNA sequence + chromatin questiongi-chromatin"Predict chromatin state", "Histone marks / DNase / TF binding from sequence", "DeepSEA prediction"
FASTA / TSS-centred locus (≥9,198 bp) + expression questiongi-expression"Predict expression for this gene / sequence", "Sequence-to-TPM", "Cell-type expression prediction"
FASTA / genomic region + gene annotation questiongi-annotation"Annotate this DNA", "Predict transcripts / gene structure from sequence", "De novo gene prediction"

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 a query implies a two-step scRNA latent workflow, explain the scrna-embedding -> scrna-orchestrator --use-rep X_scvi chain rather than hiding it. If a query asks for MR plus visual replication of an Open Targets colocalisation, explain the mr-region-run -> locuscompare-region-render --mr-result-json chain rather than hiding it (both commands take the same unified config -- the (gene, exposure, outcome, lead) tuple; mr-region-run writes result.json which locuscompare-region-render consumes via --mr-result-json to overlay the causal-magnitude annotation on the regional plot). If ambiguous, ask the user to clarify.
    • For .csv / .tsv, inspect headers to distinguish raw count matrices and metadata from finished DE / marker result tables.
  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.
Show full SKILL.md (343 more words)Show less

File Type Detection

python
EXTENSION_MAP = {
    ".vcf": "equity-scorer",
    ".vcf.gz": "equity-scorer",
    "directory with SampleSheet + VCF": "illumina-bridge",
    ".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",
    ".mtx": "scrna-orchestrator",
    ".mtx.gz": "scrna-orchestrator",
    ".rds": "scrna-orchestrator",
    ".csv": "equity-scorer",  # default for tabular; inspect headers
    ".tsv": "equity-scorer",
}

Header-aware tabular routing:

  • gene + log2FoldChange + padj/pvalue → diff-visualizer
  • names + scores with optional cluster → diff-visualizer
  • sample_id plus design columns like condition / batch → rnaseq-de
  • Gene rows plus multiple numeric sample columns → rnaseq-de

NEXUS files (.nex, .nexus, .nxs) that contain a DATA or CHARACTERS block route to dnasp; tree-only NEXUS files are not routed.

Population-genetics routes to dnasp, used when no other explicit intent is named (so "alignment", "diversity", "variant", "compare", "unfolded" and "population structure" do not capture these requests, but "find papers about Tajima's D" still reaches lit-synthesizer):

  • tajima, nucleotide diversity, haplotype diversity, watterson, segregating sites
  • neutrality test, fu and li, fu's fs, fay and wu, hka test
  • mcdonald-kreitman, ka/ks, dn/ds, effective number of codons, codon usage bias, rscu
  • mismatch distribution, raggedness, indel polymorphism, four-gamete, site frequency spectrum
  • dnasp, dna polymorphism

Embedding-specific keyword routes:

  • scvi
  • latent
  • embedding
  • integration
  • batch correction

Bioconductor-specific keyword routes:

  • bioconductor
  • bioc
  • biocmanager
  • summarizedexperiment
  • singlecellexperiment
  • genomicranges
  • variantannotation
  • annotationhub
  • experimenthub

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.
  • Metadata-only cloud access: platform metadata lookups are acceptable only when genomic payloads remain local.
  • 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"
  • "Which Bioconductor package should I use for bulk RNA-seq?"
  • "Predict the structure of this protein sequence: MKWVTFISLLFLFSSAYS..."
  • "Make my analysis reproducible as a Nextflow pipeline"

© ClawBio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files in skills/bio-orchestrator of ClawBio/ClawBio.

  • SKILL.md
  • orchestrator.py
  • tests/test_orchestrator.py
  • tests/test_skill_intents.py

Open the folder on GitHubat commit dece754

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in ClawBio/ClawBio, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Bio Orchestrator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bio Orchestrator compared with similar skills
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Bio Orchestrator this skillClawBio/ClawBio1.2k3 repos~2.5kAutomated safety check: PassMIT
LaminDB Biological Data Managementdavila7/claude-code-templates32k12 repos~3.6kAutomated safety check: PassMIT
AI Scientist EvaluatorBioTender-max/awesome-bio-agent-skills199—~2.4kAutomated safety check: PassCustom licence
Latchbio Integrationdavila7/claude-code-templates32k11 repos~2.4kAutomated safety check: PassMIT
Remote Compute Sshaipoch/open-science5.5k—~5.7kAutomated safety check: PassApache-2.0
Latchbio IntegrationK-Dense-AI/scientific-agent-skills48k1 repos~2.5kAutomated safety check: NotesMIT

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Categories

Questions about Bio Orchestrator

What does Bio Orchestrator do?

Meta-agent that routes bioinformatics requests to specialised sub-skills. Bio Orchestrator is an agent skill from ClawBio/ClawBio. Meta-agent that routes bioinformatics requests to specialised sub-skills.

When should I use Bio Orchestrator?

Bio Orchestrator fits situations like: tasks that involve Bioinformatics; tasks that involve Reproducible research.

How do I install Bio Orchestrator in Claude Code?

Run `npx skills add ClawBio/ClawBio --skill bio-orchestrator -a claude-code`. Or copy the skill folder (skills/bio-orchestrator in ClawBio/ClawBio) into .claude/skills/bio-orchestrator in your project. Claude Code loads it when a task matches its description.

How do I install Bio Orchestrator in Codex?

Run `npx skills add ClawBio/ClawBio --skill bio-orchestrator -a codex`. Or copy the skill folder (skills/bio-orchestrator in ClawBio/ClawBio) into .agents/skills/bio-orchestrator in your project. Codex loads it when a task matches its description.

Can I use Bio Orchestrator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ClawBio/ClawBio --skill bio-orchestrator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bio-orchestrator, .gemini/skills/bio-orchestrator, .github/skills/bio-orchestrator and .opencode/skills/bio-orchestrator in your project.

What does Bio Orchestrator need to run?

Going by SKILL.md and its folder, Bio Orchestrator needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Bio Orchestrator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bio Orchestrator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bio Orchestrator use?

Bio Orchestrator is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bio Orchestrator use?

About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bio Orchestrator?

Skills that share tags, products or a category with Bio Orchestrator: LaminDB Biological Data Management (davila7/claude-code-templates, 32k stars), AI Scientist Evaluator (BioTender-max/awesome-bio-agent-skills, 199 stars), Latchbio Integration (davila7/claude-code-templates, 32k stars) and Remote Compute Ssh (aipoch/open-science, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bio Orchestrator?

ClawBio (a GitHub organization) maintains it in ClawBio/ClawBio, which has 1,154 GitHub stars. The repository holds 104 skills in this directory. The repository was last updated on October 8, 2026.

Source: ClawBio/ClawBio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.