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Biopython

Checked
jimmc414·vlatest·other

This Biopython skill analyzes biological sequences (DNA, protein) for research and development, streamlining bioinformatics tasks.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jimmc414/kosmos --skill biopython -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jimmc414

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned jimmc414/kosmos at 6cfe7f690d.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
6cfe7f690d
Manifest
kosmos-claude-scientific-skills/scientific-skills/biopython/SKILL.md
Scanned
8 files, 3,364 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

What it does

This skill provides access to Biopython, a powerful suite of tools for computational biology. It allows agents to analyze biological sequences (DNA, RNA, protein), perform sequence alignments, and work with phylogenetic trees. The skill enables tasks such as identifying genes within a DNA sequence or comparing the similarity between two protein structures.

When to use it

  • Analyzing genomic data: Identify potential gene locations in a newly sequenced genome.
  • Protein structure comparison: Determine the evolutionary relationship of proteins based on their amino acid sequences.
  • Phylogenetic analysis: Construct and analyze phylogenetic trees from sequence alignments.
  • Sequence alignment: Align multiple DNA or protein sequences to identify conserved regions.
  • Bioinformatics research: Automate repetitive tasks in bioinformatics workflows.

Key capabilities

  • Sequence analysis (DNA, RNA, Protein)
  • Sequence Alignment
  • Phylogenetic tree manipulation
  • Gene finding within DNA sequences

Example prompts

  • "Analyze this DNA sequence and identify any potential gene locations."
  • "Compare the amino acid sequences of these two proteins and calculate their similarity score."
  • "Construct a phylogenetic tree based on this set of aligned sequences."

Tips & gotchas

  • Requires familiarity with biological data formats (e.g., FASTA).
  • Biopython can be computationally intensive for very large datasets; consider resource limitations.