Agent skill · Data & Analytics

plannotate-plasmid-annotation

Auto-annotate plasmids with features (promoters, terminators, resistance, origins, tags, fluorescent proteins) via BLAST against curated DBs (Addgene, fpbase, SnapGene). FASTA or raw sequence in; annotated GenBank, interactive HTML maps, CSV tables out. Handles circular topology. Use to verify synthetic constructs, prep Addgene submissions, share maps, or batch-annotate cloning libraries.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill plannotate-plasmid-annotation --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 18 KB
Bundled scripts: none
Path: skills/sciagent/plannotate-plasmid-annotation/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

# pLannotate Plasmid Annotation ## Overview pLannotate annotates plasmid sequences by running BLAST searches against a curated library of over 5,000 features sourced from Addgene, NCBI, and fpbase. It identifies promoters, terminators, antibiotic resistance genes, origins of replication, tags, and fluorescent proteins while correctly handling circular plasmid topology — avoiding split-feature artifacts that arise from naive linear alignment. Results are written as annotated GenBank files for downstream use in SnapGene, Benchling, or BioPython, as interactive HTML plasmid maps for sharing and review, and as CSV tables for programmatic filtering. Both a Python API and a command-line interface are provided; a Streamlit web app is also bundled for exploratory use. ## When to Use - Annotating a plasmid sequence received from a collaborator or downloaded from Addgene with no accompanying map - Verifying that all expected elements (promoter, insert, resistance marker, origin) are present after assembly or mutagenesis - Preparing a GenBank submission or Addgene deposit that requires a complete feature table - Batch-annotating a library of synthetic constructs produced by combinatorial clon

What's inside
Steps it walks through
  1. Overview
  2. When to Use
  3. Prerequisites
  4. Quick Start
  5. Workflow
  6. Step 1: Load Plasmid Sequence
  7. Step 2: Run BLAST-Based Annotation
  8. Step 3: Filter Features by Quality Thresholds
  9. Step 4: Export Annotated GenBank File
  10. Step 5: Generate Interactive HTML Visualization
  11. Step 6: Parse GenBank Output with BioPython
  12. Step 7: Batch Annotate Multiple Plasmids
  13. Key Parameters
  14. Common Recipes
Commands it runs
Install via pip (requires BLAST+ on PATH)
pip install plannotate
Install via conda (recommended — handles BLAST+ automatically)
conda install -c conda-forge -c bioconda plannotate
Verify installation
plannotate --help
python -c "import plannotate; print('plannotate OK')"
Launch the pLannotate Streamlit web app (opens in browser at localhost:5000)
plannotate streamlit
Or specify a custom port
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About this skill
What does the plannotate-plasmid-annotation skill do?

Auto-annotate plasmids with features (promoters, terminators, resistance, origins, tags, fluorescent proteins) via BLAST against curated DBs (Addgene, fpbase, SnapGene). FASTA or raw sequence in; annotated GenBank, interactive HTML maps, CSV tables out. Handles circular topology. Use to verify synthetic constructs, prep Addgene submissions, share maps, or batch-annotate cloning libraries.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill plannotate-plasmid-annotation --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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