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 agentmods add skills/tiangzlab/omicsclaw/genomics-alignmentnpx skills add TianGzlab/OmicsClaw --skill genomics-alignmentgit clone --depth 1 https://github.com/TianGzlab/OmicsClawWrote 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/tiangzlab/omicsclaw/genomics-alignment)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/genomics-alignment"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/genomics-alignment.svg" alt="Measured on agentmods" 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 | $0.00079 | $0.01063 |
| Opus 5 | $0.00039 | $0.00531 |
| Sonnet 5 | $0.00016 | $0.00213 |
| Haiku 4.5 | $0.00008 | $0.00106 |
Grade A, and why
genomics-alignment 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 4d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
genomics-alignment
When to use
The user has a SAM or BAM file from any aligner (BWA-MEM, Bowtie2,
Minimap2, etc.) and wants standard alignment QC: mapped-read count,
mapping rate, MAPQ distribution, proper-pair rate, duplicate rate.
This skill mirrors samtools flagstat + per-MAPQ binning entirely
in pure Python (no samtools install needed). It does not
perform alignment — feed in an already-aligned .sam / .bam.
For pre-alignment FASTQ QC use genomics-qc. For variant calling
on the aligned reads use genomics-variant-calling.
Inputs & Outputs
Inputs
- File types:
.sam
Outputs
tables/alignment_stats.csvreport.mdresult.json
Flow
- Open the SAM in text mode (
genomics_alignment.py:73→open(sam_path, "r")) or synthesise a demo SAM atoutput_dir/demo_alignment.sam(genomics_alignment.py:151). - Stream the records, count flags (mapped / proper-pair / dup / supplementary / secondary).
- Bin MAPQ; compute insert-size mean / median (paired only).
- Write
tables/alignment_stats.csv(genomics_alignment.py:279) +report.md+ standardisedresult.jsonenvelope.
Gotchas
--inputREQUIRED unless--demo.genomics_alignment.py:267raisesValueError("--input required when not using --demo"); non-existent paths raiseFileNotFoundErrorat:270. There is noparser.errorshortcut —ValueErrorpropagates as a Python traceback, exit code 1.- Text SAM only — binary BAM raises
UnicodeDecodeError.genomics_alignment.py:73callsopen(sam_path, "r")(text mode); there is nopysamimport or BAM/CRAM decoder anywhere in the script. Convert BAMs upstream withsamtools view -h aligned.bam > aligned.sam. The "no pysam dependency" comment at:43documents this intent. - No subprocess to
samtools. Parsing is pure-Python — the script never shells out. CRAM input is not supported either. - No alignment is performed. This skill only summarises an already-aligned file. To produce the SAM/BAM, run BWA / Bowtie2 / Minimap2 yourself first; this skill consumes their output.
- Demo writes a synthetic SAM into
output_dir.genomics_alignment.py:151writesdemo_alignment.samdirectly into the user-specified output directory. If you re-run--demowith different parameters in the same dir, the file is overwritten silently. - Insert-size statistics are paired-only. Single-end alignments still emit a row — but the insert-size columns will be 0 / NaN. Inspect
summary['proper_pair_rate']to confirm the input is paired before drawing conclusions.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 86 lines · 79 tokens per session scan A fda5abd6a0f3
genomics-alignment is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 79 tokens to every session and 1,063 once invoked, about $0.0004 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 2026-08-30.
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