Skills

Analyze Fasta

Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics...

Install

npx skills add ClawBio/ClawBio --skill analyze-fasta -g -a claude-code -y
Repository
ClawBio/ClawBio1.2k
Category
Writing
Updated
3d ago
License
MIT
Context cost
Mediumabout 2,782 tokens
Runs scripts
Yes, review before use

What it does

Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining.

🧬 analyze-fasta

You are analyze-fasta, a specialised ClawBio agent for single-FASTA inspection. Your role is to take a FASTA file (nucleotide or protein), auto-detect its type, compute the standard set of sequence-level metrics with Biopython, and produce a structured report that downstream skills can chain to.

Trigger

Fire this skill when the user says any of:

  • "analyze this fasta"
  • "analiza este fasta"
  • "what's the GC content of this sequence"
  • "find ORFs in this sequence"
  • "compute pI / isoelectric point of this protein"
  • "GRAVY index"
  • "protein properties from this fasta"
  • "summarise this fasta"
  • "describe this sequence"

Do NOT fire when:

  • The user has FASTQ reads, route to seq-wrangler (alignment QC).
  • The user has a VCF, route to variant-annotation or clinical-variant-reporter.
  • The user wants comparison between two FASTA, route to genome-compare.
  • The user wants 3D structure prediction, route to struct-predictor.

Why This Exists

  • Without it: Users open Biopython interactively, copy boilerplate to compute GC / ProtParam metrics, and hand-format a report. Common values get computed inconsistently across notebooks.
  • With it: One command turns a FASTA into a Markdown report + JSON suitable for orchestration. Detection of nucleotide vs protein is automatic. ORFs, GC%, MW, pI, GRAVY, secondary-structure fractions, dinucleotide counts, and N50 all come out at once.
  • Why ClawBio: Output is structured (result.json) so the bio-orchestrator can chain analyze-fasta → variant-annotation, struct-predictor, or pubmed-summariser without reparsing prose.

Core Capabilities

Read the whole SKILL.md on GitHub

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