RRepoGEO

REPOGEO REPORT · LITE

jondot/awesome-rust-llm

Default branch master · commit e8e8ba25 · scanned 6/16/2026, 4:22:44 PM

GitHub: 577 stars · 31 forks

AI VISIBILITY SCORE
28 /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
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 jondot/awesome-rust-llm, 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
    Clarify README's opening to emphasize its role as a discovery hub for Rust LLM resources

    Why:

    CURRENT
    Awesome Rust LLM is an awesome style list that keeps track and curates the best Rust based LLM frameworks, libraries, tools, tutorials, articles and more.
    COPY-PASTE FIX
    Awesome Rust LLM is the definitive curated list for discovering and navigating the best Rust-based LLM frameworks, libraries, tools, and resources. It serves as a central hub for developers seeking to build AI applications with Rust, providing a comprehensive overview of the ecosystem.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root containing the text of the MIT License.
  • mediumhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    In your GitHub repository settings, set the 'Homepage URL' to `https://github.com/jondot/awesome-rust-llm`.

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 jondot/awesome-rust-llm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
llm
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. llm · recommended 1×
  2. candle · recommended 1×
  3. rust-bert · recommended 1×
  4. llama-cpp-rs · recommended 1×
  5. tch-rs · recommended 1×
  • CATEGORY QUERY
    What are the best Rust libraries for building applications powered by large language models?
    you: not recommended
    AI recommended (in order):
    1. llm
    2. candle
    3. rust-bert
    4. llama-cpp-rs
    5. tch-rs

    AI recommended 5 alternatives but never named jondot/awesome-rust-llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I integrate local LLM inference capabilities into my Rust projects efficiently?
    you: not recommended
    AI recommended (in order):
    1. llm-rs (rustformers/llm-rs)
    2. candle (huggingface/candle)
    3. tract (sonos/tract)
    4. ort (microsoft/ort)
    5. tch-rs (LaurentMazare/tch-rs)

    AI recommended 5 alternatives but never named jondot/awesome-rust-llm. 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 jondot/awesome-rust-llm?
    pass
    AI did not name jondot/awesome-rust-llm — 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?

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

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

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jondot/awesome-rust-llm — 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