RRepoGEO

REPOGEO REPORT · LITE

cactus-compute/cactus

Default branch main · commit 3227a7f9 · scanned 5/29/2026, 3:52:08 AM

GitHub: 5,254 stars · 417 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 cactus-compute/cactus, 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
    Reposition README H1 to disambiguate from other 'Cactus' projects

    Why:

    CURRENT
    # Cactus
    COPY-PASTE FIX
    # Cactus: Low-latency On-Device AI Engine for Mobile & Wearables
  • highreadme#2
    Enhance README opening to clarify framework type and target

    Why:

    CURRENT
    A low-latency AI engine for mobile devices & wearables. Main features:
    COPY-PASTE FIX
    Cactus is a low-latency AI engine and SDK designed for mobile devices & wearables, enabling efficient on-device inference for LLMs, speech, and vision models. Key features include:
  • mediumlicense#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    ## License
Cactus is released under [describe the actual license(s) here, e.g., 'a custom license combining Apache 2.0 and MIT terms']. Please see the [LICENSE](LICENSE) file for full 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 cactus-compute/cactus
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MediaPipe
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. MediaPipe · recommended 2×
  2. ONNX Runtime · recommended 2×
  3. TensorFlow Lite · recommended 2×
  4. PyTorch Mobile · recommended 2×
  5. MLC LLM · recommended 1×
  • CATEGORY QUERY
    How to run large language models efficiently on mobile devices with low latency?
    you: not recommended
    AI recommended (in order):
    1. MLC LLM
    2. MediaPipe
    3. ONNX Runtime
    4. TensorFlow Lite
    5. Core ML
    6. PyTorch Mobile
    7. Qualcomm AI Engine Direct (QNN)

    AI recommended 7 alternatives but never named cactus-compute/cactus. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an on-device AI framework for ARM-powered edge devices with multimodal capabilities.
    you: not recommended
    AI recommended (in order):
    1. MediaPipe
    2. TensorFlow Lite
    3. PyTorch Mobile
    4. OpenVINO Toolkit
    5. ONNX Runtime
    6. Edge Impulse

    AI recommended 6 alternatives but never named cactus-compute/cactus. 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 cactus-compute/cactus?
    pass
    AI named cactus-compute/cactus explicitly

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

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

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite