seqinr

seqinr is a skill for Claude Code, Codex from LeoLin990405/r-analytics-skill. It costs 25 tokens per session (508 once invoked), scanned A, original, MIT.

Instructions for using the R seqinr package to work with biological sequences such as DNA and protein strings. It covers FASTA files, sequence properties, translation, codon usage, manipulation, and comparisons.

In plain words
What is it for?
Use it to read or write FASTA files, calculate GC content, count nucleotides or codons, translate DNA, find subsequences, analyze codon usage, and compare sequences.
Why use it?
It provides ready-to-use operations for common sequence-analysis tasks instead of requiring each one to be implemented manually.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to read or write FASTA files, calculate GC content, count nucleotides or codons, translate DNA, find subsequences, analyze codon usage, and compare sequences.

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Install with agentmods
npx agentmods add skills/leolin990405/r-analytics-skill/seqinr
Install

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.

Any agent
npx skills add LeoLin990405/r-analytics-skill --skill seqinr
Clone the repo
git clone --depth 1 https://github.com/LeoLin990405/r-analytics-skill

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for seqinr

README.md
[![agentmods](https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/seqinr.svg)](https://agentmods.dev/skills/leolin990405/r-analytics-skill/seqinr)
Your own site
<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/seqinr"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/seqinr.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 508 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00025 $0.00508
Opus 5 $0.00013 $0.00254
Sonnet 5 $0.00005 $0.00102
Haiku 4.5 $0.00003 $0.00051

Measured 7d ago against content hash 948de4b28680, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

seqinr 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 7d 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.

sub-skills/r-bio/r-bio-genomics/seqinr/SKILL.md · 129 lines

What it actually says

seqinr

Biological sequences retrieval and analysis.

Reading Sequences

library(seqinr)

# Read FASTA
seqs <- read.fasta("sequences.fasta")

# Get sequence
seq1 <- seqs[[1]]
getSequence(seq1)

# Get annotation
getAnnot(seq1)
getName(seq1)

Writing Sequences

# Write FASTA
write.fasta(sequences, names, file = "output.fasta")

# Multiple sequences
write.fasta(
  sequences = list(seq1, seq2),
  names = c("seq1", "seq2"),
  file.out = "output.fasta"
)

Sequence Properties

# GC content
GC(seq)

# Sequence length
length(seq)

# Count nucleotides
count(seq, wordsize = 1)

# Count codons
count(seq, wordsize = 3)

Codon Usage

# Codon usage table
uco(seq)

# Codon adaptation index
cai(seq, w = codon_weights)

# Effective number of codons
eff.nc(seq)

Translation

# Translate DNA to protein
translate(seq)

# With specific genetic code
translate(seq, numcode = 2)  # Vertebrate mitochondrial

Sequence Manipulation

# Reverse complement
comp(seq)
rev(comp(seq))

# Subsequence
seq[10:50]

# Convert to string
c2s(seq)

# Convert string to vector
s2c("ATCGATCG")

Dotplot

# Sequence comparison
dotPlot(seq1, seq2)

# With window
dotPlot(seq1, seq2, wsize = 10, wstep = 1)

Database Access

# Query GenBank
choosebank("genbank")
query <- query("myquery", "SP=Homo sapiens AND K=insulin")
seqs <- getSequence(query)
closebank()

Amino Acid Properties

# Amino acid composition
AAstat(protein_seq)

# Molecular weight
pmw(protein_seq)

# Isoelectric point
computePI(protein_seq)
Changes

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.

  1. 7d ago First seen · 129 lines · 25 tokens per session scan A 948de4b28680

Subscribe to this mod's changes

seqinr is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 508 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 2026-08-31.

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