RRepoGEO

REPOGEO REPORT · LITE

evilsocket/cake

Default branch main · commit be522af1 · scanned 5/21/2026, 5:18:43 PM

GitHub: 3,032 stars · 183 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 evilsocket/cake, 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 specific topics for AI inference and distributed ML

    Why:

    COPY-PASTE FIX
    ai-inference, distributed-ai, multimodal-ai, edge-ai, rust, machine-learning, model-serving, gpu-acceleration, mobile-ai, desktop-ai
  • highabout#2
    Make the About description more explicit about AI inference server

    Why:

    CURRENT
    Distributed inference for mobile, desktop and server.
    COPY-PASTE FIX
    Multimodal AI inference server for distributed workloads across mobile, desktop, and server devices.
  • mediumreadme#3
    Add a clear statement about the project's license(s) to the README

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under [SPECIFY LICENSE(S) HERE, e.g., Apache-2.0 and MIT]. Please refer to the [LICENSE](LICENSE) file for complete details.

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 evilsocket/cake
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
tensorflow/federated
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. tensorflow/federated · recommended 1×
  2. OpenMined/PySyft · recommended 1×
  3. AWS IoT Greengrass · recommended 1×
  4. Azure IoT Edge · recommended 1×
  5. Google Cloud IoT Edge · recommended 1×
  • CATEGORY QUERY
    How to run large AI models across a cluster of mixed mobile and desktop devices?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Federated (tensorflow/federated)
    2. PySyft (OpenMined/PySyft)
    3. AWS IoT Greengrass
    4. Azure IoT Edge
    5. Google Cloud IoT Edge
    6. ONNX Runtime (microsoft/onnxruntime)
    7. OpenVINO (openvinotoolkit/openvino)
    8. NVIDIA TensorRT
    9. Ray (ray-project/ray)
    10. Apache Spark
    11. TensorFlow Lite (tensorflow/tensorflow)
    12. PyTorch Mobile (pytorch/pytorch)

    AI recommended 12 alternatives but never named evilsocket/cake. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a multimodal AI inference server supporting text, image, and voice generation.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Triton Inference Server
    2. KServe
    3. OpenVINO Model Server
    4. TorchServe
    5. TensorFlow Serving
    6. FastAPI
    7. transformers
    8. diffusers
    9. audiocraft
    10. TTS

    AI recommended 10 alternatives but never named evilsocket/cake. 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 evilsocket/cake?
    pass
    AI named evilsocket/cake explicitly

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

  • If a team adopts evilsocket/cake in production, what risks or prerequisites should they evaluate first?
    pass
    AI named evilsocket/cake 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 evilsocket/cake solve, and who is the primary audience?
    pass
    AI named evilsocket/cake 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 evilsocket/cake. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/evilsocket/cake"><img src="https://repogeo.com/badge/evilsocket/cake.svg" alt="RepoGEO" /></a>
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evilsocket/cake — 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