Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wentorai/research-plugins --skill clawbio-guidegit clone --depth 1 https://github.com/wentorai/research-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wentorai/research-plugins/clawbio-guide)<a href="https://agentmods.dev/skills/wentorai/research-plugins/clawbio-guide"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/clawbio-guide/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wentorai/research-plugins/clawbio-guide"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/clawbio-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.01181 |
| Opus 5 | $0.00008 | $0.00590 |
| Sonnet 5 | $0.00003 | $0.00236 |
| Haiku 4.5 | $0.00002 | $0.00118 |
Grade A, and why
clawbio-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ClawBio Guide
Overview
ClawBio is a bioinformatics skill library for OpenClaw that provides pre-built skills for common genomics and biological analysis tasks — sequence alignment, variant calling, differential expression, pathway analysis, and more. Each skill encapsulates best-practice bioinformatics pipelines as conversational agent capabilities, making complex analyses accessible through natural language.
Installation
# Install as OpenClaw plugin
openclaw plugins install @clawbio/clawbio
# Or add to your OpenClaw configuration
# In openclaw.config.json:
{
"plugins": ["@clawbio/clawbio"]
}
Available Skills
| Skill | Pipeline | Description |
|---|---|---|
| sequence-align | BWA/Bowtie2 | Align reads to reference genome |
| variant-call | GATK/BCFtools | Call SNPs and indels |
| rna-seq | STAR + DESeq2 | Differential expression analysis |
| chip-seq | MACS2 + DiffBind | Peak calling and differential binding |
| metagenomics | Kraken2 + Bracken | Taxonomic classification |
| phylogenetics | IQ-TREE + RAxML | Phylogenetic tree construction |
| protein-structure | AlphaFold/ESMFold | Structure prediction |
| pathway-analysis | GSEA + enrichR | Gene set enrichment |
Usage Examples
RNA-Seq Analysis
# Through OpenClaw conversational interface:
# "Analyze differential expression between treated and control
# samples in the data/rnaseq/ directory"
# ClawBio executes:
# 1. Quality control (FastQC)
# 2. Trimming (Trimmomatic)
# 3. Alignment (STAR)
# 4. Quantification (featureCounts)
# 5. Differential expression (DESeq2)
# 6. Visualization (volcano plot, MA plot, heatmap)
# 7. Pathway enrichment (GSEA)
Variant Calling
# "Call variants from the whole-genome sequencing data
# in samples/ against hg38 reference"
# Pipeline:
# 1. Alignment: BWA-MEM2 → sorted BAM
# 2. Preprocessing: MarkDuplicates, BQSR
# 3. Variant calling: GATK HaplotypeCaller
# 4. Filtering: VQSR or hard filters
# 5. Annotation: VEP or SnpEff
# 6. Report: variant statistics, quality metrics
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 168 lines · 16 tokens per session scan A c991ade95be6
clawbio-guide is a skill published in the GitHub repository wentorai/research-plugins (291 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 1,181 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
arboreto
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for…
torchdrug
Build and troubleshoot TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.
deepspot-m
Generate transcriptome-wide virtual spatial transcriptomics from H&E histology with DeepSpot-M. Use when you need spatial gene expression in log1p-CPM for 224x224 tiles at about 20x, want to query protein-coding genes by symbol instead of a fixed panel, or want to run prediction across a whole slide after tiling with…
pyhealth
Build clinical/healthcare deep-learning pipelines with PyHealth — loading EHR/signal/imaging datasets (MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14, EHRShot), defining tasks (mortality, readmission, length-of-stay, drug recommendation, sleep staging, ICD coding, EEG events), instantiating models (Transformer…
pick-a-pii-model
Select an on-device OpenMed PII model from the committed registry by language, runtime format, and size budget, then require recall validation before deployment. Use when an agent must choose a local PII detector for CPU, Apple Silicon, or a mobile export without relying on live model discovery.
evo2
Score, embed, and generate DNA sequences with Evo 2, a long-context genomic foundation model. Use this skill when: (1) Computing per-nucleotide or per-sequence likelihoods for variant effect scoring, (2) Embedding genomic windows for downstream classification, (3) Generating DNA conditioned on a prefix, (4) Scoring…