RRepoGEO

REPOGEO REPORT · LITE

RightNow-AI/autokernel

Default branch main · commit 78435821 · scanned 5/18/2026, 9:47:48 PM

GitHub: 1,367 stars · 133 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
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 RightNow-AI/autokernel, 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 the README's opening to emphasize the autonomous agent aspect

    Why:

    CURRENT
    # AutoKernel

**Autoresearch for GPU kernels.** Give it any PyTorch model, go to sleep, wake up to optimized Triton or CUDA C++ kernels.
    COPY-PASTE FIX
    # AutoKernel

**An autonomous AI agent for GPU kernel optimization.** Give it any PyTorch model, go to sleep, wake up to optimized Triton or CUDA C++ kernels.
  • mediumtopics#2
    Add topics related to AI agents and autonomous systems

    Why:

    CURRENT
    autoresearch, cuda, gpu, kernel-optimization, pytorch, triton
    COPY-PASTE FIX
    ai-agent, autonomous-optimization, autoresearch, cuda, gpu, kernel-optimization, pytorch, triton
  • lowreadme#3
    Add a "Core Differentiator" section to highlight autonomous self-correction

    Why:

    COPY-PASTE FIX
    ## Core Differentiator

Unlike traditional kernel optimization tools, AutoKernel operates as an autonomous AI agent with built-in capabilities for self-debugging and self-correction. It leverages an iterative execution-feedback loop within a sandboxed environment to continuously refine generated kernels, ensuring both performance and correctness.

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 RightNow-AI/autokernel
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TorchInductor
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TorchInductor · recommended 2×
  2. OpenAI Triton · recommended 2×
  3. TorchDynamo · recommended 1×
  4. Triton · recommended 1×
  5. TVM · recommended 1×
  • CATEGORY QUERY
    How to automatically optimize PyTorch model performance by generating custom GPU kernels?
    you: not recommended
    AI recommended (in order):
    1. TorchDynamo
    2. TorchInductor
    3. Triton
    4. TVM
    5. OpenAI Triton
    6. NVIDIA CUTLASS

    AI recommended 6 alternatives but never named RightNow-AI/autokernel. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools can autonomously generate and optimize Triton or CUDA kernels for deep learning?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Triton
    2. Apache TVM
    3. TorchInductor
    4. NVIDIA TensorRT
    5. CUTLASS
    6. MLIR

    AI recommended 6 alternatives but never named RightNow-AI/autokernel. 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 RightNow-AI/autokernel?
    pass
    AI named RightNow-AI/autokernel explicitly

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

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

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

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RightNow-AI/autokernel — 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