RRepoGEO

REPOGEO REPORT · LITE

plasma-umass/ChatDBG

Default branch main · commit 9badd32e · scanned 5/27/2026, 9:26:55 PM

GitHub: 1,105 stars · 89 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 plasma-umass/ChatDBG, 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 core value proposition in README

    Why:

    CURRENT
    The current README starts with the project title, authors, badges, and links before the core description.
    COPY-PASTE FIX
    Move the core description to immediately follow the H1, rephrasing it to: "# ChatDBG: An AI-Powered Debugging Assistant

ChatDBG is an AI-based debugging assistant for C/C++/Python/Rust code that integrates large language models into standard debuggers (`pdb`, `lldb`, `gdb`). It enables natural language interaction with your debugger, providing AI-driven root cause analysis and suggested fixes for complex bugs."
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://www.youtube.com/watch?v=XsFGMKKaYSo
  • mediumcomparison#3
    Add a 'Key Differentiators' section to the README

    Why:

    CURRENT
    The README currently states "As far as we are aware, ChatDBG is the _first_ debugger to automatically perform root cause analysis and to provide suggested fixes."
    COPY-PASTE FIX
    Add a new section to the README, for example, "## Why ChatDBG? (Key Differentiators)" with content like: "Unlike generic AI assistants (e.g., Copilot Chat, ChatGPT), ChatDBG deeply integrates with your live debugging session, steering the debugger to answer specific 'why' questions about your program's state. Compared to traditional debuggers (e.g., GDB, UndoDB), it provides automated root cause analysis and suggests fixes using large language models, going beyond manual inspection."

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 plasma-umass/ChatDBG
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Copilot Chat
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot Chat · recommended 1×
  2. ChatGPT · recommended 1×
  3. Google Gemini Advanced · recommended 1×
  4. Cursor · recommended 1×
  5. Tabnine Chat · recommended 1×
  • CATEGORY QUERY
    How can I use AI to understand complex bugs and get suggested fixes?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Chat
    2. ChatGPT
    3. Google Gemini Advanced
    4. Cursor
    5. Tabnine Chat
    6. CodiumAI

    AI recommended 6 alternatives but never named plasma-umass/ChatDBG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to enhance C++ debugging with AI-driven root cause analysis.
    you: not recommended
    AI recommended (in order):
    1. UndoDB
    2. LiveRecorder
    3. TotalView Debugger
    4. GDB
    5. AWS CodeGuru Profiler
    6. Clang Static Analyzer
    7. Cppcheck (https://github.com/danmaru/cppcheck)
    8. PVS-Studio
    9. Valgrind
    10. Memcheck
    11. Helgrind

    AI recommended 11 alternatives but never named plasma-umass/ChatDBG. 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 plasma-umass/ChatDBG?
    pass
    AI named plasma-umass/ChatDBG explicitly

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

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

    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
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