RRepoGEO

REPOGEO REPORT · LITE

GPTomics/bioSkills

Default branch main · commit 5de40da0 · scanned 6/16/2026, 7:57:08 PM

GitHub: 910 stars · 159 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface GPTomics/bioSkills, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README's opening to clearly state the problem solved for AI agents

    Why:

    CURRENT
    # bioSkills

A collection of skills that guide AI coding agents (Claude Code, OpenAI Codex, Google Gemini, OpenCode, OpenClaw) through common bioinformatics tasks.
    COPY-PASTE FIX
    # bioSkills: Expert Guides for AI Bioinformatics Agents

This repository provides a curated collection of expert skills, code patterns, and best practices specifically designed to guide AI coding agents (such as Claude Code, OpenAI Codex, Google Gemini, OpenCode, OpenClaw) through common bioinformatics tasks. It solves the problem of AI agents generating incorrect or non-idiomatic bioinformatics code by equipping them with the knowledge needed to produce accurate and robust solutions.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-agents, bioinformatics, large-language-models, llm-skills, code-generation, genomics, computational-biology, best-practices
  • mediumreadme#3
    Clarify the context of the 'Performance' section in README

    Why:

    CURRENT
    ## Performance

Evaluation summary report available at [bioskills_eval_20260328.pdf]. Evaluations were performed on the Bio-Task Bench dataset.
    COPY-PASTE FIX
    ## Performance (of the bioSkills)

To demonstrate the effectiveness of bioSkills in guiding AI agents, an evaluation summary report is available at [resources/bioskills_eval_20260328.pdf]. These evaluations were performed on the Bio-Task Bench dataset, showcasing how bioSkills improve AI agent proficiency in bioinformatics tasks.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface GPTomics/bioSkills
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Biopython
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Biopython · recommended 2×
  2. Rosalind · recommended 1×
  3. NCBI · recommended 1×
  4. BLAST · recommended 1×
  5. Entrez · recommended 1×
  • CATEGORY QUERY
    How can I equip AI coding assistants with best practices for bioinformatics tasks?
    you: not recommended
    AI recommended (in order):
    1. Biopython
    2. Rosalind
    3. NCBI
    4. BLAST
    5. Entrez
    6. Snakemake
    7. Nextflow
    8. Bioconductor
    9. Bioinformatics Algorithms: An Active Learning Approach (Pevzner & Compeau)
    10. Pylint
    11. Flake8
    12. Bioconda
    13. pysam
    14. PyVCF
    15. Docker
    16. Singularity

    AI recommended 16 alternatives but never named GPTomics/bioSkills. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What resources help AI agents generate correct code for genomic data analysis?
    you: not recommended
    AI recommended (in order):
    1. Biopython
    2. PySAM
    3. Pandas
    4. scikit-learn
    5. TensorFlow
    6. PyTorch
    7. AnVIL
    8. Galaxy

    AI recommended 8 alternatives but never named GPTomics/bioSkills. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of GPTomics/bioSkills?
    pass
    AI named GPTomics/bioSkills explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts GPTomics/bioSkills in production, what risks or prerequisites should they evaluate first?
    pass
    AI named GPTomics/bioSkills explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo GPTomics/bioSkills solve, and who is the primary audience?
    pass
    AI did not name GPTomics/bioSkills — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite