RRepoGEO

REPOGEO REPORT · LITE

itigges22/ATLAS

Default branch main · commit 64cd3583 · scanned 6/26/2026, 5:23:00 AM

GitHub: 2,053 stars · 180 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)

3 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 itigges22/ATLAS, 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
    Update repository description

    Why:

    CURRENT
    Adaptive Test-time Learning and Autonomous Specialization
    COPY-PASTE FIX
    ATLAS is a self-hosted, GPU-powered coding assistant for privacy-focused developers, offering local AI for feature writing, bug fixing, and code analysis without subscriptions.
  • mediumreadme#2
    Streamline README introduction for immediate clarity

    Why:

    CURRENT
    <p align="center"> <br/> <sub><i>The ATLAS TUI live, 10× sped up, running the V3 pipeline on a file creation.</i></sub> </p> <h1 align="center">A.T.L.A.S.</h1> <p align="center"><b>Adaptive Test-time Learning and Autonomous Specialization</b></p>
    COPY-PASTE FIX
    # ATLAS: Adaptive Test-time Learning and Autonomous Specialization
A self-hosted, GPU-powered coding assistant that runs locally on your machine, providing privacy-focused AI for feature writing, bug fixing, and code analysis without subscriptions.

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 itigges22/ATLAS
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Code Llama
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Code Llama · recommended 2×
  2. LM Studio · recommended 1×
  3. Ollama · recommended 1×
  4. Continue.dev · recommended 1×
  5. TabbyML · recommended 1×
  • CATEGORY QUERY
    How to get a coding assistant that runs locally on my GPU for privacy?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. Continue.dev
    4. TabbyML
    5. Code Llama
    6. llama.cpp
    7. Transformers
    8. Phind-7B

    AI recommended 8 alternatives but never named itigges22/ATLAS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for self-hosted AI coding tools to avoid subscriptions and keep code private.
    you: not recommended
    AI recommended (in order):
    1. Tabby (TabbyML/tabby)
    2. Code Llama
    3. Phind-CodeLlama
    4. Continue (Continue-team/continue)
    5. LocalAI (mudler/LocalAI)
    6. Ollama (ollama/ollama)
    7. FauxPilot (fauxpilot/fauxpilot)
    8. Deepseek Coder

    AI recommended 8 alternatives but never named itigges22/ATLAS. 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 itigges22/ATLAS?
    pass
    AI named itigges22/ATLAS explicitly

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

  • If a team adopts itigges22/ATLAS in production, what risks or prerequisites should they evaluate first?
    pass
    AI named itigges22/ATLAS 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 itigges22/ATLAS solve, and who is the primary audience?
    pass
    AI named itigges22/ATLAS explicitly

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

Embed your GEO score

Drop this badge into the README of itigges22/ATLAS. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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itigges22/ATLAS — 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