RRepoGEO

REPOGEO REPORT · LITE

the-crypt-keeper/can-ai-code

Default branch main · commit aa5a2f6d · scanned 5/31/2026, 8:33:03 PM

GitHub: 600 stars · 35 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 the-crypt-keeper/can-ai-code, 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
  • highreadme#1
    Reposition README's opening to state current purpose

    Why:

    CURRENT
    # From Coding to Cognition: Measuring Reasoning in the Age of o1

## The End of an Era
    COPY-PASTE FIX
    # Can-Ai-Code: A Benchmark for AI Reasoning and Multi-Step Logical Problem Solving

This repository provides a framework for evaluating the reasoning capabilities of large language models, focusing on their ability to tackle novel problems, complex logical structures, and maintain working memory across multi-step processes. While originally a benchmark for AI coding ability, Can-Ai-Code has evolved to address the more challenging question of whether AI can truly "think."

## The End of an Era
Two years ago, I built Can-Ai-Code to answer a simple question: could these new language models actually generate syntactically valid code?...
  • highabout#2
    Update the repository description

    Why:

    CURRENT
    Self-evaluating interview for AI coders
    COPY-PASTE FIX
    A benchmark for evaluating AI reasoning and multi-step logical problem-solving capabilities.
  • mediumtopics#3
    Refine repository topics to reflect reasoning focus

    Why:

    CURRENT
    ai, ggml, humaneval, langchain, llama-cpp, llm, transformers
    COPY-PASTE FIX
    ai, llm, reasoning, benchmark, evaluation, logical-problems, multi-step-tasks

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 the-crypt-keeper/can-ai-code
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
HumanEval
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. HumanEval · recommended 1×
  2. MBPP (Mostly Basic Python Problems) · recommended 1×
  3. CodeContests · recommended 1×
  4. APPS (Automated Programming Problem Solving) · recommended 1×
  5. GSM8K (Grade School Math 8K) · recommended 1×
  • CATEGORY QUERY
    How to benchmark large language models for complex coding and reasoning tasks?
    you: not recommended
    AI recommended (in order):
    1. HumanEval
    2. MBPP (Mostly Basic Python Problems)
    3. CodeContests
    4. APPS (Automated Programming Problem Solving)
    5. GSM8K (Grade School Math 8K)
    6. MATH
    7. Big-Bench Hard (BBH)
    8. AlpacaEval
    9. MT-Bench
    10. GPT-4

    AI recommended 10 alternatives but never named the-crypt-keeper/can-ai-code. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools are available to assess LLM performance on multi-step logical problems?
    you: not recommended
    AI recommended (in order):
    1. LangChain Evaluation
    2. DeepEval
    3. Ragas
    4. OpenAI Evals
    5. Humanloop
    6. MLflow
    7. NLTK
    8. SpaCy

    AI recommended 8 alternatives but never named the-crypt-keeper/can-ai-code. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 the-crypt-keeper/can-ai-code?
    pass
    AI named the-crypt-keeper/can-ai-code explicitly

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

  • If a team adopts the-crypt-keeper/can-ai-code in production, what risks or prerequisites should they evaluate first?
    pass
    AI named the-crypt-keeper/can-ai-code 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 the-crypt-keeper/can-ai-code solve, and who is the primary audience?
    pass
    AI named the-crypt-keeper/can-ai-code explicitly

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

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the-crypt-keeper/can-ai-code — 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