RRepoGEO

REPOGEO REPORT · LITE

Kuaishou-OneRec/OpenOneRec

Default branch main · commit a969edca · scanned 6/7/2026, 12:43:10 PM

GitHub: 807 stars · 116 forks

AI VISIBILITY SCORE
30 /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
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 Kuaishou-OneRec/OpenOneRec, 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
    Create a LICENSE file in the repository root

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root and add the full text of your chosen open-source license (e.g., Apache-2.0, MIT, or a custom license).
  • mediumhomepage#2
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://huggingface.co/OpenOneRec

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 Kuaishou-OneRec/OpenOneRec
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
deepset/Haystack
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. deepset/Haystack · recommended 1×
  2. LangChain · recommended 1×
  3. LlamaIndex · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. RecBole · recommended 1×
  • CATEGORY QUERY
    Seeking an open-source framework to accelerate generative recommendation using large language models.
    you: not recommended
    AI recommended (in order):
    1. Haystack (deepset/Haystack)
    2. LangChain
    3. LlamaIndex
    4. Hugging Face Transformers
    5. RecBole
    6. Surprise

    AI recommended 6 alternatives but never named Kuaishou-OneRec/OpenOneRec. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best benchmarks for evaluating generative AI recommendation models with LLMs?
    you: not recommended
    AI recommended (in order):
    1. WSDM Cup
    2. ACM RecSys Challenge
    3. Amazon Product Reviews Dataset
    4. MovieLens 1M
    5. MovieLens 20M
    6. MovieLens Latest Full
    7. Goodreads Book Reviews Dataset
    8. MIND (Microsoft News Dataset)
    9. Pushshift.io
    10. Yelp Dataset

    AI recommended 10 alternatives but never named Kuaishou-OneRec/OpenOneRec. 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 Kuaishou-OneRec/OpenOneRec?
    pass
    AI named Kuaishou-OneRec/OpenOneRec explicitly

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

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

    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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Kuaishou-OneRec/OpenOneRec — 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