Agent skill

bio-workflows-genome-annotation-pipeline

End-to-end genome annotation pipeline from assembled contigs to functional annotation, covering repeat masking, gene prediction, and functional assignment for both prokaryotic and eukaryotic genomes. Use when annotating a newly assembled genome from scratch.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill genome-annotation-pipeline --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 13 KB
Bundled scripts: yes
Path: skills/bioskills/genome-annotation-pipeline/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: BRAKER3 3.0+, BUSCO 5.5+, Bakta 1.9+, Infernal 1.1+, InterProScan 5.66+, Prokka 1.14+, RepeatMasker 4.1+, RepeatModeler 2.0+, eggNOG-mapper 2.1+, pandas 2.2+, tRNAscan-SE 2.0+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Genome Annotation Pipeline **"Annotate my genome assembly"** → Orchestrate prokaryotic (Bakta) or eukaryotic (BRAKER3) gene prediction, repeat masking (RepeatMasker), functional annotation (eggNOG-mapper, InterProScan), and ncRNA annotation (Infernal). Complete workflow from assembled contigs to functional annotation for prokaryotic or eukaryotic genomes. ## Pipeline Overview ``` Assembled contigs | v [0. Assembly QC] ----------> QUAST, BUSCO (confirm assembly quality) | +----- Prokaryotic? -----> Path A: Bakta (one-step annotation) | | | v | Annotated genome (GFF3, GenBank,

What's inside
Steps it walks through
  1. Version Compatibility
  2. Pipeline Overview
  3. Path A: Prokaryotic Annotation (Bakta)
  4. Database Setup
  5. Run Bakta
  6. Prokaryotic QC Checkpoint
  7. Path B: Eukaryotic Annotation
  8. Step 1: Repeat Masking
  9. Step 2: Gene Prediction with BRAKER3
  10. Step 3: Functional Annotation
  11. Step 4: ncRNA Annotation
  12. Merging Annotations
  13. Troubleshooting
  14. Complete Pipeline Script
Ships with 3 files
  • examples/eukaryotic_annotation_pipeline.sh
  • examples/prokaryotic_annotation_pipeline.sh
  • usage-guide.md
Commands it runs
bakta_db download --output /path/to/bakta_db --type full
bakta \
assembly.fasta
Build species-specific repeat library
RepeatModeler -database mygenome -pa 8 -LTRStruct
Combine with known repeats
cat mygenome-families.fa /path/to/RepeatMasker/Libraries/RepeatMaskerLib.h5 > combined_lib.fa
Mask the genome
RepeatMasker \
BRAKER3 combines GeneMark-ETP, AUGUSTUS, and TSEBRA
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About this skill
What does the bio-workflows-genome-annotation-pipeline skill do?

End-to-end genome annotation pipeline from assembled contigs to functional annotation, covering repeat masking, gene prediction, and functional assignment for both prokaryotic and eukaryotic genomes. Use when annotating a newly assembled genome from scratch.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill genome-annotation-pipeline --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.

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