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 dralkh/iktinah --skill pysamgit clone --depth 1 https://github.com/dralkh/iktinahWrote 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/dralkh/iktinah/pysam)<a href="https://agentmods.dev/skills/dralkh/iktinah/pysam"><img src="https://agentmods.dev/badge/skills/dralkh/iktinah/pysam/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/dralkh/iktinah/pysam"><img src="https://agentmods.dev/badge/skills/dralkh/iktinah/pysam.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 | $0.00047 | $0.02319 |
| Opus 5 | $0.00023 | $0.01159 |
| Sonnet 5 | $0.00009 | $0.00464 |
| Haiku 4.5 | $0.00005 | $0.00232 |
Grade A, and why
pysam scanned grade A 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Without an index, use `fetch(until_eof=True)` for sequential reading. This is a copy
95% identical to pysam — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pysam
Overview
Pysam is a Python module for reading, manipulating, and writing genomic datasets. Read/write SAM/BAM/CRAM alignment files, VCF/BCF variant files, and FASTA/FASTQ sequences with a Pythonic interface to htslib. Query tabix-indexed files, perform pileup analysis for coverage, and execute samtools/bcftools commands.
When to Use This Skill
This skill should be used when:
- Working with sequencing alignment files (BAM/CRAM)
- Analyzing genetic variants (VCF/BCF)
- Extracting reference sequences or gene regions
- Processing raw sequencing data (FASTQ)
- Calculating coverage or read depth
- Implementing bioinformatics analysis pipelines
- Quality control of sequencing data
- Variant calling and annotation workflows
Quick Start
Installation
uv pip install pysam
Basic Examples
Read alignment file:
import pysam
# Open BAM file and fetch reads in region
samfile = pysam.AlignmentFile("example.bam", "rb")
for read in samfile.fetch("chr1", 1000, 2000):
print(f"{read.query_name}: {read.reference_start}")
samfile.close()
Read variant file:
# Open VCF file and iterate variants
vcf = pysam.VariantFile("variants.vcf")
for variant in vcf:
print(f"{variant.chrom}:{variant.pos} {variant.ref}>{variant.alts}")
vcf.close()
Query reference sequence:
# Open FASTA and extract sequence
fasta = pysam.FastaFile("reference.fasta")
sequence = fasta.fetch("chr1", 1000, 2000)
print(sequence)
fasta.close()
Core Capabilities
1. Alignment File Operations (SAM/BAM/CRAM)
Use the AlignmentFile class to work with aligned sequencing reads. This is appropriate for analyzing mapping results, calculating coverage, extracting reads, or quality control.
Common operations:
- Open and read BAM/SAM/CRAM files
- Fetch reads from specific genomic regions
- Filter reads by mapping quality, flags, or other criteria
- Write filtered or modified alignments
- Calculate coverage statistics
- Perform pileup analysis (base-by-base coverage)
- Access read sequences, quality scores, and alignment information
What ships with it
4 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.
- 8d ago First seen · 263 lines · 47 tokens per session scan A 550fd8a88de9
pysam is a skill published in the GitHub repository dralkh/iktinah (77 stars, last pushed 2mo ago), licensed MIT. It adds 47 tokens to every session and 2,319 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 95% identical to pysam, differing in 4 lines, and is treated as a copy.
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