RRepoGEO

REPOGEO REPORT · LITE

petergpt/bullshit-benchmark

Default branch main · commit 7b92fe7b · scanned 5/30/2026, 4:43:44 AM

GitHub: 1,666 stars · 64 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 petergpt/bullshit-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

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

OVERALL DIRECTION
  • highreadme#1
    Clarify the README's H1 and opening sentence for better AI categorization

    Why:

    CURRENT
    <h1>
  
  BullshitBench v2
</h1>

BullshitBench measures whether models detect nonsense, call it out clearly, and avoid confidently continuing with invalid assumptions.
    COPY-PASTE FIX
    <h1>
  
  BullshitBench v2: An LLM Nonsense Detection Benchmark
</h1>

BullshitBench is a comprehensive benchmark suite designed to measure whether AI models detect nonsense, call it out clearly, and avoid confidently continuing with invalid assumptions.
  • mediumhomepage#2
    Update the repository homepage URL to the project viewer

    Why:

    CURRENT
    https://x.com/petergostev
    COPY-PASTE FIX
    https://petergpt.github.io/bullshit-benchmark/viewer/index.v2.html

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 petergpt/bullshit-benchmark
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Scale AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Scale AI · recommended 2×
  2. Appen · recommended 2×
  3. Ragas · recommended 1×
  4. Guardrails AI · recommended 1×
  5. GPT-4 · recommended 1×
  • CATEGORY QUERY
    How to assess if an AI model confidently answers nonsensical or invalid user prompts?
    you: not recommended
    AI recommended (in order):
    1. Scale AI
    2. Appen
    3. Ragas
    4. Guardrails AI
    5. GPT-4
    6. Claude 3 Opus
    7. Sentence-BERT
    8. Python with `re` module

    AI recommended 8 alternatives but never named petergpt/bullshit-benchmark. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help benchmark an LLM's tendency to generate confident answers to false premises?
    you: not recommended
    AI recommended (in order):
    1. TruthfulQA
    2. FactScore
    3. Wikidata
    4. HELM
    5. RAGAS
    6. DBpedia
    7. Scale AI
    8. Appen
    9. Amazon Mechanical Turk
    10. OpenAI Evals

    AI recommended 10 alternatives but never named petergpt/bullshit-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 petergpt/bullshit-benchmark?
    pass
    AI named petergpt/bullshit-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 petergpt/bullshit-benchmark in production, what risks or prerequisites should they evaluate first?
    pass
    AI named petergpt/bullshit-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 petergpt/bullshit-benchmark solve, and who is the primary audience?
    pass
    AI named petergpt/bullshit-benchmark explicitly

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

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petergpt/bullshit-benchmark — 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