RRepoGEO

REPOGEO REPORT · LITE

giuven95/chatgpt-failures

Default branch main · commit bef1097f · scanned 6/10/2026, 1:28:11 PM

GitHub: 596 stars · 25 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
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 giuven95/chatgpt-failures, 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
  • highlicense#1
    Add a LICENSE file to clarify usage rights

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository with the MIT License text. This clarifies usage rights for the collected examples and the repository itself.
  • highhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add `https://github.com/giuven95/chatgpt-failures` as the homepage URL in the repository's 'About' section.
  • mediumtopics#3
    Add more specific topics to emphasize the repo's nature as a collection

    Why:

    CURRENT
    bing, chatbot, chatgpt, error, failure, new-bing, openai
    COPY-PASTE FIX
    bing, chatbot, chatgpt, error, failure, new-bing, openai, llm-failures, ai-failures, failure-archive, curated-examples, research-data

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 giuven95/chatgpt-failures
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Anthropic
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Anthropic · recommended 1×
  2. AI Incident Database (AIID) · recommended 1×
  3. Hugging Face · recommended 1×
  4. Google · recommended 1×
  5. OpenAI · recommended 1×
  • CATEGORY QUERY
    Where can I find documented examples of large language model failures for research?
    you: not recommended
    AI recommended (in order):
    1. Anthropic
    2. AI Incident Database (AIID)
    3. Hugging Face
    4. Google
    5. OpenAI
    6. Awesome-LLM-Safety

    AI recommended 6 alternatives but never named giuven95/chatgpt-failures. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a collection of AI chatbot errors to create synthetic test data.
    you: not recommended
    AI recommended (in order):
    1. Common Sense Conversations (CSC) Dataset
    2. Persona-Chat Dataset
    3. Wizard of Wikipedia Dataset
    4. Multi-Domain Wizard-of-Oz (MultiWOZ) Dataset
    5. Adversarial NLI (ANLI) Dataset
    6. Reddit Conversations (various subreddits)

    AI recommended 6 alternatives but never named giuven95/chatgpt-failures. 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 giuven95/chatgpt-failures?
    pass
    AI named giuven95/chatgpt-failures explicitly

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

  • If a team adopts giuven95/chatgpt-failures in production, what risks or prerequisites should they evaluate first?
    pass
    AI named giuven95/chatgpt-failures 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 giuven95/chatgpt-failures solve, and who is the primary audience?
    pass
    AI named giuven95/chatgpt-failures explicitly

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

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giuven95/chatgpt-failures — 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