RRepoGEO

REPOGEO REPORT · LITE

PaperGuru-AI/PaperGuru-Benchmark

Default branch main · commit 27e89061 · scanned 6/11/2026, 2:43:41 PM

GitHub: 900 stars · 131 forks

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 PaperGuru-AI/PaperGuru-Benchmark, 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 to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm-agents, long-term-memory, lifecycle-aware-memory, ai-benchmark, llm-benchmark, ai-research, memory-primitive
  • highhomepage#2
    Add a project homepage URL

    Why:

    COPY-PASTE FIX
    https://paperrguru.ai/benchmark
  • mediumreadme#3
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under a custom academic research license. Please refer to the LICENSE file for full details regarding usage and distribution.

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 PaperGuru-AI/PaperGuru-Benchmark
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pinecone
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pinecone · recommended 2×
  2. weaviate/weaviate · recommended 1×
  3. qdrant/qdrant · recommended 1×
  4. chroma-core/chroma · recommended 1×
  5. RedisLabs/redisstack · recommended 1×
  • CATEGORY QUERY
    What are robust long-term memory solutions for building advanced LLM agent systems?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. Weaviate (weaviate/weaviate)
    3. Qdrant (qdrant/qdrant)
    4. Chroma (chroma-core/chroma)
    5. Redis Stack (RedisLabs/redisstack)
    6. pgvector (pgvector/pgvector)
    7. Elasticsearch (elastic/elasticsearch)

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

    Show full AI answer
  • CATEGORY QUERY
    Seeking a lifecycle-aware memory primitive to enhance long-horizon LLM agent performance.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. MemGPT
    4. Redis
    5. Weaviate
    6. Pinecone

    AI recommended 6 alternatives but never named PaperGuru-AI/PaperGuru-Benchmark. 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 PaperGuru-AI/PaperGuru-Benchmark?
    pass
    AI named PaperGuru-AI/PaperGuru-Benchmark explicitly

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

  • If a team adopts PaperGuru-AI/PaperGuru-Benchmark in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PaperGuru-AI/PaperGuru-Benchmark 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 PaperGuru-AI/PaperGuru-Benchmark solve, and who is the primary audience?
    pass
    AI named PaperGuru-AI/PaperGuru-Benchmark 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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  • Brand-free category queries5 vs 2 in Lite
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