analyze-fasta
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.
npx skills add BioTender-max/awesome-bio-agent-skills --skill analyze-fasta --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 🧬 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 i
- Trigger
- Why This Exists
- Core Capabilities
- Scope
- Input Formats
- Workflow
- CLI Reference
- Demo
- Algorithm / Methodology
- Example Queries
- Example Output
- Output Structure
- Dependencies
- Gotchas
Standard usage (ClawBio convention) python skills/analyze-fasta/analyze_fasta.py \ Demo mode (uses bundled synthetic nucleotide FASTA) python skills/analyze-fasta/analyze_fasta.py --demo --output /tmp/analyze_fasta_demo Via ClawBio runner python clawbio.py run analyze-fasta --input <fasta_file> --output <dir> python clawbio.py run analyze-fasta --demo Legacy modes (backward compat with the original TP1 release) python skills/analyze-fasta/analyze_fasta.py <file.fasta> --json python skills/analyze-fasta/analyze_fasta.py <file.fasta> --html out.html
What does the analyze-fasta skill do?
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.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill analyze-fasta --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.