RRepoGEO

REPOGEO REPORT · LITE

199-biotechnologies/claude-deep-research-skill

Default branch main · commit f2f2c0fa · scanned 6/7/2026, 12:28:23 PM

GitHub: 750 stars · 84 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 199-biotechnologies/claude-deep-research-skill, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition README opening to clarify 'skill' vs. 'model'

    Why:

    CURRENT
    Enterprise-grade research engine for Claude Code. Produces citation-backed reports with source credibility scoring, multi-provider search, and automated validation.
    COPY-PASTE FIX
    This is an enterprise-grade deep research skill designed specifically to extend Claude Code's capabilities. It provides a robust 8-phase pipeline, source credibility scoring, and automated validation, significantly outperforming Claude's native research functions, as well as general AI assistants like OpenAI, Gemini, and Claude Desktop for quality and verification.
  • mediumlicense#2
    Add a LICENSE file and reference it in the README

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the MIT License. Add a 'License' section to the README with the text: 'This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.'

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 199-biotechnologies/claude-deep-research-skill
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 · recommended 1×
  2. Anthropic Claude 3 · recommended 1×
  3. Scopus · recommended 1×
  4. Web of Science · recommended 1×
  5. Google Scholar API · recommended 1×
  • CATEGORY QUERY
    How to generate enterprise-grade research reports with source credibility scoring and automated validation?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. Anthropic Claude 3
    3. Scopus
    4. Web of Science
    5. Google Scholar API
    6. Beautiful Soup (crummy/BeautifulSoup)
    7. Scrapy (scrapy/scrapy)
    8. Elasticsearch (elastic/elasticsearch)
    9. Apache Solr (apache/solr)
    10. Python
    11. NLTK (nltk/nltk)
    12. spaCy (explosion/spaCy)
    13. Pandas (pandas-dev/pandas)
    14. SciPy (scipy/scipy)
    15. NumPy (numpy/numpy)
    16. Jupyter Notebooks (jupyter/notebook)
    17. VS Code (microsoft/vscode)
    18. Tableau
    19. Power BI
    20. Looker

    AI recommended 20 alternatives but never named 199-biotechnologies/claude-deep-research-skill. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an AI tool for comprehensive, multi-source research that verifies information and provides detailed reports.
    you: not recommended
    AI recommended (in order):
    1. Elicit
    2. Scite.ai
    3. Perplexity AI
    4. ChatGPT
    5. Google Gemini
    6. Consensus
    7. Semantic Scholar

    AI recommended 7 alternatives but never named 199-biotechnologies/claude-deep-research-skill. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 199-biotechnologies/claude-deep-research-skill?
    pass
    AI named 199-biotechnologies/claude-deep-research-skill explicitly

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

  • If a team adopts 199-biotechnologies/claude-deep-research-skill in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 199-biotechnologies/claude-deep-research-skill 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 199-biotechnologies/claude-deep-research-skill solve, and who is the primary audience?
    pass
    AI did not name 199-biotechnologies/claude-deep-research-skill — 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?

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