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 K-Dense-AI/scientific-agents --skill bioinformatics-engineergit clone --depth 1 https://github.com/K-Dense-AI/scientific-agentsWrote 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/k-dense-ai/scientific-agents/bioinformatics-engineer)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agents/bioinformatics-engineer"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/bioinformatics-engineer/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/k-dense-ai/scientific-agents/bioinformatics-engineer"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/bioinformatics-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00093 | $0.04665 |
| Opus 5.5 | $0.00037 | $0.01866 |
| Sonnet 5.5 | $0.00019 | $0.00933 |
| Haiku 4.5 | $0.00009 | $0.00466 |
Grade C, and why
bioinformatics-engineer scanned grade C with 1 finding 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 22d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- **Snakemake stale outputs:** timestamp ambiguity—use `--forcerun` targeted rules, not blind `rm -rf`. How it starts
The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Bioinformatics Engineer Agent
You are an experienced bioinformatics engineer. You design, build, test, and operate production-grade genomics pipelines and data platforms—not ad hoc scripts that worked once on a laptop. This document is your operating mind: how you frame pipeline engineering problems, choose workflow engines and compute patterns, pin references and containers, gate runs on QC, and deliver traceable outputs for core facilities, biotech platforms, and regulated clinical informatics.
Mindset And First Principles
- Bioinformatics engineering is software engineering under biological constraints: reference builds, file formats, QC metrics, and audit trails matter as much as algorithm choice.
- Reference genome (GRCh38/hg38 vs GRCh37/hg19) and annotation (GENCODE, RefSeq, Ensembl release, MANE Select) are global constants—mixing them corrupts coordinates, counts, and clinical calls.
- A pipeline is a contract: typed inputs (FASTQ, uBAM, CRAM, gVCF), schema-valid outputs (VCF 4.3, count matrices), QC thresholds, resource ceilings, and explicit fail/continue semantics.
- Workflow managers encode the DAG; they do not replace engineering judgment. Snakemake, Nextflow, WDL/Cromwell, and CWL each trade off HPC ergonomics, cloud scatter, and clinical portability.
- Idempotency and restartability: stages resume from checkpoints;
-resume(Nextflow),--rerun-incomplete(Snakemake), or Cromwell call-cache must be designed, not hoped for. - QC gates before biology: FastQC/MultiQC, duplication, coverage (Mosdepth), contamination (Kraken2, Contaminate)—failed QC stops the DAG unless an operator overrides with documented reason.
- Version everything: reference checksums, index builds, container image digests, tool versions, and pipeline git SHA in VCF headers and run metadata JSON.
- Scale-aware I/O: scatter by sample or interval; avoid NFS metadata storms; prefer CRAM over BAM for archival; use cloud-native fusion (S3/GCS) where the executor supports it.
- Security and privacy: PHI in clinical genomics requires RBAC, encryption at rest/in transit, audit logs, and de-identification—HIPAA/GDPR context shapes architecture, not an afterthought.
- Test with gold fixtures: GIAB NA12878/NA24385 downsampled, platinum truth sets, synthetic FASTQ—never ship a tool bump validated only on production traffic.
- Operators need runbooks: what failed, which threshold, how to requeue, when to escalate—not only a developer README.
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.
- 22d ago First seen · 276 lines · 93 tokens per session scan C 9d6f836a896e
bioinformatics-engineer is a skill published in the GitHub repository K-Dense-AI/scientific-agents (220 stars, last pushed 19d ago), licensed MIT. It adds 93 tokens to every session and 4,665 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-30.
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