RRepoGEO

REPOGEO REPORT · LITE

ravenscroftj/turbopilot

Default branch main · commit 6d9c84f5 · scanned 5/28/2026, 3:07:47 AM

GitHub: 3,789 stars · 122 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 ravenscroftj/turbopilot, 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
    Add historical context before deprecation notice

    Why:

    CURRENT
    # TurboPilot 🚀

## Turbopilot is deprecated/archived as of 30/9/23. There are other mature solutions that meet the community's needs better. Please read my blog post about my decision to down tools and for recommended alternatives.
    COPY-PASTE FIX
    # TurboPilot 🚀

TurboPilot was an open-source, self-hosted code completion engine designed to run locally on CPU, inspired by projects like fauxpilot. **Important:** This project is deprecated/archived as of 30/9/23. Please see my blog post for recommended alternatives.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://fosstodon.org/@jamesravey
  • lowtopics#3
    Expand repository topics with relevant keywords

    Why:

    CURRENT
    code-completion, cpp, language-model, machine-learning
    COPY-PASTE FIX
    code-completion, cpp, language-model, machine-learning, local-llm, self-hosted, cpu-inference

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 ravenscroftj/turbopilot
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Code Llama
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Code Llama · recommended 2×
  2. LM Studio · recommended 2×
  3. Tabnine · recommended 1×
  4. Ollama · recommended 1×
  5. FauxPilot · recommended 1×
  • CATEGORY QUERY
    What are options for a self-hosted, open source code completion tool running locally?
    you: not recommended
    AI recommended (in order):
    1. Tabnine
    2. Code Llama
    3. Ollama
    4. LM Studio
    5. FauxPilot
    6. LocalAI
    7. YouCompleteMe
    8. Language Server Protocol
    9. pyright
    10. rust-analyzer
    11. tsserver

    AI recommended 11 alternatives but never named ravenscroftj/turbopilot. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a local AI code assistant that runs efficiently on CPU with minimal RAM.
    you: not recommended
    AI recommended (in order):
    1. TabbyML (TabbyML/tabby)
    2. Code Llama
    3. Ollama (ollama/ollama)
    4. Continue (Continue-team/continue)
    5. LM Studio
    6. FauxPilot (fauxpilot/fauxpilot)
    7. Phind-CodeLlama

    AI recommended 7 alternatives but never named ravenscroftj/turbopilot. 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 ravenscroftj/turbopilot?
    pass
    AI named ravenscroftj/turbopilot explicitly

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

  • If a team adopts ravenscroftj/turbopilot in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ravenscroftj/turbopilot 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 ravenscroftj/turbopilot solve, and who is the primary audience?
    pass
    AI named ravenscroftj/turbopilot 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 ravenscroftj/turbopilot. 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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HTML
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ravenscroftj/turbopilot — 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