RRepoGEO

REPOGEO REPORT · LITE

sonos/tract

Default branch main · commit ee52857a · scanned 5/28/2026, 12:41:58 PM

GitHub: 2,923 stars · 259 forks

AI VISIBILITY SCORE
54 /100
Needs work
Category recall
1 / 2
Avg rank #7.0 when recommended
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 sonos/tract, 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
  • highabout#1
    Update 'About' description to highlight Rust-native, embedded, and edge focus

    Why:

    CURRENT
    Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference
    COPY-PASTE FIX
    Tiny, no-nonsense, self-contained, Rust-native Tensorflow and ONNX inference for embedded and edge devices.
  • hightopics#2
    Add specific topics for embedded, edge AI, and inference engines

    Why:

    CURRENT
    artificial-intelligence, neural-networks, onnx, rust, rust-library, tensorflow
    COPY-PASTE FIX
    artificial-intelligence, neural-networks, onnx, rust, rust-library, tensorflow, embedded, edge-ai, inference-engine
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://docs.rs/tract-core

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
1 / 2
50% of queries surface sonos/tract
Avg rank
#7.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
tensorflow/tensorflow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. tensorflow/tensorflow · recommended 1×
  2. microsoft/onnxruntime · recommended 1×
  3. pytorch/pytorch · recommended 1×
  4. ARM-software/armnn · recommended 1×
  5. NVIDIA/TensorRT · recommended 1×
  • CATEGORY QUERY
    Looking for a lightweight inference engine to run neural networks on embedded devices.
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite (tensorflow/tensorflow)
    2. ONNX Runtime (microsoft/onnxruntime)
    3. PyTorch Mobile (pytorch/pytorch)
    4. Arm NN (ARM-software/armnn)
    5. NVIDIA TensorRT (NVIDIA/TensorRT)
    6. DeepSparse (neuralmagic/deepsparse)

    AI recommended 6 alternatives but never named sonos/tract. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I efficiently deploy pre-trained AI models in a Rust application?
    you: #7
    AI recommended (in order):
    1. Tch-rs (LaurentMazare/tch-rs)
    2. Rustformers (huggingface/rustformers)
    3. ONNX Runtime (onnxruntime/onnxruntime-rs)
    4. candle (huggingface/candle)
    5. TensorFlow Lite (tensorflow/rust)
    6. OpenVINO (intel-isl/openvino-rs)
    7. tract (sonos/tract) ← you
    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 sonos/tract?
    pass
    AI named sonos/tract explicitly

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

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

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

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sonos/tract — 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