RRepoGEO

REPOGEO REPORT · LITE

FloridSleeves/LLMDebugger

Default branch main · commit 49ac191f · scanned 5/30/2026, 12:28:42 PM

GitHub: 587 stars · 57 forks

AI VISIBILITY SCORE
35 /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
3 / 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 FloridSleeves/LLMDebugger, 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
  • mediumreadme#1
    Add a 'Comparison' or 'Why LDB?' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example, after 'Usage', with a title like 'Why LDB? Differentiating from other tools'. Include text that clarifies LDB's unique focus as a *runtime debugger for LLM-generated code*, distinguishing it from static code analysis tools (e.g., Pylint, Flake8) and general LLM frameworks or evaluators (e.g., LangChain, OpenAI Evals) by emphasizing its step-by-step verification of intermediate variables.
  • mediumhomepage#2
    Add the Hugging Face Space URL as the repository homepage

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://huggingface.co/spaces/shangdatalab-ucsd/LDB

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 FloridSleeves/LLMDebugger
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pylint
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Pylint · recommended 1×
  2. Flake8 · recommended 1×
  3. MyPy · recommended 1×
  4. ESLint · recommended 1×
  5. TypeScript · recommended 1×
  • CATEGORY QUERY
    How to debug code generated by large language models step-by-step effectively?
    you: not recommended
    AI recommended (in order):
    1. Pylint
    2. Flake8
    3. MyPy
    4. ESLint
    5. TypeScript
    6. PMD
    7. Checkstyle
    8. FxCop
    9. unittest
    10. pytest
    11. Jest
    12. Mocha
    13. JUnit
    14. NUnit
    15. xUnit.net
    16. VS Code
    17. PyCharm
    18. IntelliJ IDEA
    19. Visual Studio
    20. logging module
    21. console.log()
    22. console.warn()
    23. console.error()
    24. java.util.logging
    25. Log4j
    26. SLF4J
    27. System.Diagnostics.Debug.WriteLine()
    28. Serilog
    29. NLog
    30. Git
    31. Mercurial
    32. SVN

    AI recommended 32 alternatives but never named FloridSleeves/LLMDebugger. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for verifying LLM-generated program execution by tracking intermediate variables?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI Evals
    4. Weights & Biases Prompts
    5. MLflow
    6. Pydantic

    AI recommended 6 alternatives but never named FloridSleeves/LLMDebugger. 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 FloridSleeves/LLMDebugger?
    pass
    AI named FloridSleeves/LLMDebugger explicitly

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

  • If a team adopts FloridSleeves/LLMDebugger in production, what risks or prerequisites should they evaluate first?
    pass
    AI named FloridSleeves/LLMDebugger 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 FloridSleeves/LLMDebugger solve, and who is the primary audience?
    pass
    AI named FloridSleeves/LLMDebugger explicitly

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

Embed your GEO score

Drop this badge into the README of FloridSleeves/LLMDebugger. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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FloridSleeves/LLMDebugger — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite