RRepoGEO

REPOGEO REPORT · LITE

ruixiangcui/AGIEval

Default branch main · commit 84ab72d9 · scanned 6/7/2026, 6:36:46 AM

GitHub: 774 stars · 53 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 ruixiangcui/AGIEval, 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
  • highabout#1
    Add a concise 'About' description to the repository

    Why:

    COPY-PASTE FIX
    AGIEval is a human-centric benchmark for evaluating foundation models' general abilities in human cognition and problem-solving, using 20 official, high-standard admission and qualification exams.
  • mediumreadme#2
    Reposition the core value proposition to the README's first paragraph

    Why:

    CURRENT
    # AGIEval
This repository contains information about AGIEval, data, code and output of baseline systems for the benchmark.
    COPY-PASTE FIX
    # AGIEval
AGIEval is a human-centric benchmark specifically designed to evaluate the general abilities of foundation models in tasks pertinent to human cognition and problem-solving. This repository contains information about AGIEval, data, code and output of baseline systems for the benchmark.

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 ruixiangcui/AGIEval
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
HELM (Holistic Evaluation of Language Models)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. HELM (Holistic Evaluation of Language Models) · recommended 1×
  2. BIG-bench (Beyond the Imitation Game Benchmark) · recommended 1×
  3. MMLU (Massive Multitask Language Understanding) · recommended 1×
  4. ARC (AI2 Reasoning Challenge) · recommended 1×
  5. Prolific · recommended 1×
  • CATEGORY QUERY
    How can I benchmark large language models against human-level cognitive tasks?
    you: not recommended
    AI recommended (in order):
    1. HELM (Holistic Evaluation of Language Models)
    2. BIG-bench (Beyond the Imitation Game Benchmark)
    3. MMLU (Massive Multitask Language Understanding)
    4. ARC (AI2 Reasoning Challenge)
    5. Prolific
    6. Amazon Mechanical Turk (MTurk)
    7. Figure Eight (now Appen)
    8. GLUE (General Language Understanding Evaluation)
    9. SuperGLUE
    10. Winograd Schema Challenge

    AI recommended 10 alternatives but never named ruixiangcui/AGIEval. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What benchmarks use standardized human exams to assess AI model reasoning skills?
    you: not recommended
    AI recommended (in order):
    1. MMLU
    2. ARC
    3. HellaSwag
    4. Big-Bench
    5. GSM8K
    6. LSAT
    7. Bar Exam
    8. MedQA

    AI recommended 8 alternatives but never named ruixiangcui/AGIEval. 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 ruixiangcui/AGIEval?
    pass
    AI named ruixiangcui/AGIEval explicitly

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

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