biological-expert

biological-expert is a skill for Claude Code from personamanagmentlayer/pcl. It costs 59 tokens per session (2,491 once invoked), scanned A, original, Apache-2.0.

A guide to biology and biotechnology with an emphasis on genetics, DNA, proteins, sequencing, and computational analysis. It includes bioinformatics, which uses software to study biological data such as DNA sequences.

In plain words
What is it for?
Use it to analyse DNA sequences, calculate sequence statistics, study mutations and gene expression, align sequences, analyse RNA sequencing data, and model biological systems.
Why use it?
It helps developers understand biological concepts and choose appropriate ways to analyse genetic or molecular data. It also connects laboratory ideas with code-based workflows.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to analyse DNA sequences, calculate sequence statistics, study mutations and gene expression, align sequences, analyse RNA sequencing data, and model biological systems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/personamanagmentlayer/pcl/biological-expert
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add personamanagmentlayer/pcl --skill biological-expert
Clone the repo
git clone --depth 1 https://github.com/personamanagmentlayer/pcl

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
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Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,491 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00059 $0.02491
Opus 5 $0.00030 $0.01246
Sonnet 5 $0.00012 $0.00498
Haiku 4.5 $0.00006 $0.00249

Measured 7d ago against content hash 1bda479496e5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

biological-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

stdlib/scientific/biological-expert/SKILL.md · 375 lines

How it starts

The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Biological Sciences Expert

Expert guidance for biology, biotechnology, genetics, bioinformatics, and computational biology applications.

Core Concepts

Molecular Biology

  • DNA, RNA, and protein structure
  • Central dogma (transcription, translation)
  • Gene expression and regulation
  • Genetic mutations and variations
  • CRISPR and gene editing
  • Protein folding and structure

Genomics & Bioinformatics

  • DNA sequencing (Sanger, NGS, long-read)
  • Genome assembly and annotation
  • Sequence alignment (BLAST, BLAT)
  • Variant calling and analysis
  • RNA-seq analysis
  • Phylogenetic analysis

Systems Biology

  • Metabolic pathways
  • Protein-protein interactions
  • Gene regulatory networks
  • Mathematical modeling
  • Pathway analysis
  • Network biology

DNA Sequence Analysis

from Bio import SeqIO, Seq
from Bio.Seq import Seq
from Bio.SeqUtils import gc_fraction, molecular_weight
from typing import Dict, List

class DNAAnalyzer:
    """Analyze DNA sequences"""

    def __init__(self, sequence: str):
        self.sequence = Seq(sequence.upper())

    def basic_stats(self) -> Dict:
        """Calculate basic sequence statistics"""
        return {
            "length": len(self.sequence),
            "gc_content": gc_fraction(self.sequence) * 100,
            "molecular_weight": molecular_weight(self.sequence, "DNA"),
            "nucleotide_counts": self._count_nucleotides()
        }

    def _count_nucleotides(self) -> Dict[str, int]:
        """Count each nucleotide"""
        return {
            'A': self.sequence.count('A'),
            'T': self.sequence.count('T'),
            'G': self.sequence.count('G'),
            'C': self.sequence.count('C')
        }

    def transcribe(self) -> str:
        """Transcribe DNA to RNA"""
        return str(self.sequence.transcribe())

    def translate(self, table: int = 1) -> str:
        """Translate DNA to protein"""
        return str(self.sequence.translate(table=table))

    def reverse_complement(self) -> str:
        """Get reverse complement"""
        return str(self.sequence.reverse_complement())

    def find_orfs(self, min_length: int = 100) -> List[Dict]:
        """Find Open Reading Frames"""
        orfs = []

        for strand, seq in [(+1, self.sequence), (-1, self.sequence.reverse_complement())]:
            for frame in range(3):
                trans = seq[frame:].translate(to_stop=False)

                for i, aa in enumerate(trans):
                    if aa == 'M':  # Start codon
                        for j in range(i + 1, len(trans)):
                            if trans[j] == '*':  # Stop codon
                                orf_len = (j - i) * 3

                                if orf_len >= min_length:
                                    orfs.append({
                                        "strand": strand,
                                        "frame": frame,
                                        "start": i * 3 + frame,
                                        "end": j * 3 + frame,
                                        "length": orf_len,
                                        "protein": str(trans[i:j])
                                    })
                                break

        return orfs

    def find_motif(self, motif: str) -> List[int]:
        """Find motif positions in sequence"""
        positions = []
        motif = motif.upper()

        for i in range(len(self.sequence) - len(motif) + 1):
            if str(self.sequence[i:i+len(motif)]) == motif:
                positions.append(i)

        return positions

Read the full file on GitHub · 375 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago Changed · +10 lines · +40 tokens per session 1bda479496e5
  2. 8d ago First seen · 365 lines · 19 tokens per session scan A 501c2cf1ca28

Subscribe to this mod's changes

biological-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed 2d ago), licensed Apache-2.0. It adds 59 tokens to every session and 2,491 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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