RRepoGEO

REPOGEO REPORT · LITE

git-ai-project/git-ai

Default branch main · commit 8a92df6f · scanned 5/11/2026, 1:01:50 AM

GitHub: 1,825 stars · 166 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 git-ai-project/git-ai, 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
  • hightopics#1
    Add more specific topics for AI code tracking and attribution

    Why:

    CURRENT
    ai, ai-blame, coding-agents
    COPY-PASTE FIX
    ai, ai-blame, coding-agents, git-extension, ai-code-tracking, code-attribution, generative-ai, developer-tools, git-workflow
  • highreadme#2
    Strengthen the README's opening paragraph to explicitly state the core problem and unique value

    Why:

    CURRENT
    Git AI is an open source git extension that tracks AI-generated code in your repositories. Once installed, it automatically links every AI-written line to the agent, model, and transcripts that generated it — so you never lose the intent, requirements, and architecture decisions behind your code.
    COPY-PASTE FIX
    Git AI is an open source git extension that tracks AI-generated code in your repositories. It solves the critical problem of **losing context and accountability for AI-generated code**, automatically linking every AI-written line to the agent, model, and transcripts that generated it — so you never lose the intent, requirements, and architecture decisions behind your code.
  • mediumreadme#3
    Add a concise section clarifying how `git-ai` complements or differs from AI code generation tools

    Why:

    COPY-PASTE FIX
    ### How is `git-ai` different from AI coding assistants like GitHub Copilot?
`git-ai` does not generate code. Instead, it works *with* your existing AI coding assistants (like Copilot, Claude, ChatGPT) to provide crucial attribution and context for the code they produce, ensuring you always know the origin and intent behind AI-generated lines in your repository.

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 git-ai-project/git-ai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Python
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Python · recommended 1×
  2. Bash · recommended 1×
  3. GitHub Copilot · recommended 1×
  4. GitHub Pull Requests · recommended 1×
  5. GitLab Merge Requests · recommended 1×
  • CATEGORY QUERY
    How can I track AI-generated code contributions within my Git repositories?
    you: not recommended
    AI recommended (in order):
    1. Python
    2. Bash
    3. GitHub Copilot
    4. GitHub Pull Requests
    5. GitLab Merge Requests
    6. Bitbucket Pull Requests
    7. Conventional Commits
    8. Hugging Face Transformers
    9. OpenAI APIs
    10. SonarQube
    11. DeepSource

    AI recommended 11 alternatives but never named git-ai-project/git-ai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help attribute AI model and agent to specific lines of code in Git history?
    you: not recommended
    AI recommended (in order):
    1. Git
    2. GitHub
    3. GitLab
    4. Bitbucket
    5. MLflow
    6. DVC
    7. Weights & Biases
    8. Neptune.ai
    9. Pachyderm

    AI recommended 9 alternatives but never named git-ai-project/git-ai. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 git-ai-project/git-ai?
    pass
    AI named git-ai-project/git-ai explicitly

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

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

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

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