RRepoGEO

REPOGEO REPORT · LITE

HarryR/z80ai

Default branch main · commit f5567b60 · scanned 5/24/2026, 10:52:47 AM

GitHub: 1,090 stars · 47 forks

AI VISIBILITY SCORE
28 /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
2 / 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 HarryR/z80ai, 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 the README's opening to clarify the project's core purpose

    Why:

    CURRENT
    Z80-μLM is a 'conversational AI' that generates short character-by-character sequences, with quantization-aware training (QAT) to run on a Z80 processor with 64kb of ram.
    COPY-PASTE FIX
    Z80-μLM is a unique project that enables training and deploying small, conversational language models *directly onto* 8-bit Z80 processors with 64kb of RAM, generating character-by-character sequences. It is *not* a Z80 disassembler or reverse engineering tool.
  • mediumlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root to clearly state the terms of use.
  • lowhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add `https://harryr.github.io/z80ai/` (or similar project page) to the repository's 'About' section.

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 HarryR/z80ai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Apple II
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Apple II · recommended 1×
  2. Commodore 64 · recommended 1×
  3. ZX Spectrum · recommended 1×
  4. Applesoft BASIC · recommended 1×
  5. CBM BASIC · recommended 1×
  • CATEGORY QUERY
    How to deploy a small language model on vintage 8-bit hardware?
    you: not recommended
    AI recommended (in order):
    1. Apple II
    2. Commodore 64
    3. ZX Spectrum
    4. Applesoft BASIC
    5. CBM BASIC
    6. Sinclair BASIC
    7. TRS-80 Model I/III/4
    8. IBM PCjr

    AI recommended 8 alternatives but never named HarryR/z80ai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for training quantized conversational models and exporting as CP/M binaries?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite Micro
    2. PyTorch Mobile
    3. ONNX Runtime Mobile
    4. MicroTVM (Apache TVM)
    5. Turbo Pascal
    6. Microsoft BASIC
    7. Aztec C
    8. Small-C
    9. ELIZA

    AI recommended 9 alternatives but never named HarryR/z80ai. 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 HarryR/z80ai?
    pass
    AI did not name HarryR/z80ai — likely talking about a different project

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

  • If a team adopts HarryR/z80ai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named HarryR/z80ai 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 HarryR/z80ai solve, and who is the primary audience?
    pass
    AI named HarryR/z80ai explicitly

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

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HarryR/z80ai — 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