RRepoGEO

REPOGEO REPORT · LITE

BBuf/tvm_mlir_learn

Default branch main · commit 7b1b95c4 · scanned 5/12/2026, 9:22:49 AM

GitHub: 2,727 stars · 371 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 BBuf/tvm_mlir_learn, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highlicense#1
    Add a LICENSE file to define usage terms

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file named 'LICENSE' to the repository root with the text of the MIT License.
  • mediumhomepage#2
    Set the repository's homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/BBuf/tvm_mlir_learn

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 BBuf/tvm_mlir_learn
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
apache/tvm
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. apache/tvm · recommended 2×
  2. tensorflow/tensorflow · recommended 2×
  3. microsoft/onnxruntime · recommended 2×
  4. llvm/llvm-project · recommended 1×
  5. pytorch/pytorch · recommended 1×
  • CATEGORY QUERY
    I need resources to learn about optimizing deep learning models using compiler frameworks.
    you: not recommended
    AI recommended (in order):
    1. TVM (Apache TVM) (apache/tvm)
    2. MLIR (Multi-Level Intermediate Representation) (llvm/llvm-project)
    3. TensorFlow XLA (Accelerated Linear Algebra) (tensorflow/tensorflow)
    4. PyTorch Inductor (pytorch/pytorch)
    5. ONNX Runtime (microsoft/onnxruntime)
    6. Halide (halide/Halide)

    AI recommended 6 alternatives but never named BBuf/tvm_mlir_learn. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to compile and deploy neural networks efficiently on different hardware backends?
    you: not recommended
    AI recommended (in order):
    1. Apache TVM (apache/tvm)
    2. TensorRT
    3. OpenVINO (openvinotoolkit/openvino)
    4. ONNX Runtime (microsoft/onnxruntime)
    5. TFLite (tensorflow/tensorflow)
    6. Core ML
    7. MACE (XiaoMi/mace)

    AI recommended 7 alternatives but never named BBuf/tvm_mlir_learn. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 BBuf/tvm_mlir_learn?
    pass
    AI did not name BBuf/tvm_mlir_learn — 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 BBuf/tvm_mlir_learn in production, what risks or prerequisites should they evaluate first?
    pass
    AI named BBuf/tvm_mlir_learn 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 BBuf/tvm_mlir_learn solve, and who is the primary audience?
    pass
    AI did not name BBuf/tvm_mlir_learn — 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?

Embed your GEO score

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MARKDOWN (README)
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BBuf/tvm_mlir_learn — 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