RRepoGEO

REPOGEO REPORT · LITE

jaylfc/taOS

Default branch master · commit 7761c0d7 · scanned 7/1/2026, 3:16:57 PM

GitHub: 515 stars · 30 forks

AI VISIBILITY SCORE
27 /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
1 / 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 jaylfc/taOS, 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 H1 to explicitly state "AI Agent Operating System"

    Why:

    CURRENT
    # taOS Your AI, your hardware, your data. Self-hosted AI where your agents' memory, conversations, and files live on machines you own, fully offline when you want, cloud only when you choose.
    COPY-PASTE FIX
    # taOS: The Self-Hosted AI Agent Operating System. Your AI, your hardware, your data.
  • highlicense#2
    Clarify the specific licenses in the README

    Why:

    COPY-PASTE FIX
    Add a "## License" section to your README, explicitly naming the licenses that apply to the project (e.g., "This project is licensed under [License Name 1] and [License Name 2]. See the [LICENSE](LICENSE) file for details.").
  • mediumabout#3
    Strengthen the "About" section to emphasize its role as an AI Agent OS

    Why:

    CURRENT
    Self-hosted AI agent OS. Your memory, chat, agents, and files stay on hardware you own, offline by default, cloud by choice. Offline AI memory (taOSmd), self-hosted multi-framework group chat, a full web desktop + app store, and auto-clustering across the consumer hardware you already have (Orange/Raspberry Pi, Mac mini, gaming PC).
    COPY-PASTE FIX
    taOS is a full-fledged operating system designed specifically for self-hosting AI agents and LLMs on your own hardware. It ensures your memory, chat, agents, and files remain private and offline by default, with optional cloud integration, and includes a web desktop, app store, and multi-device clustering.

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 jaylfc/taOS
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ollama/ollama
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ollama/ollama · recommended 1×
  2. LM Studio · recommended 1×
  3. janhq/jan · recommended 1×
  4. mudler/LocalAI · recommended 1×
  5. ggerganov/llama.cpp · recommended 1×
  • CATEGORY QUERY
    How can I run AI agents and LLMs entirely on my own hardware for data privacy?
    you: not recommended
    AI recommended (in order):
    1. Ollama (ollama/ollama)
    2. LM Studio
    3. Jan (janhq/jan)
    4. LocalAI (mudler/LocalAI)
    5. llama.cpp (ggerganov/llama.cpp)
    6. Hugging Face Transformers (huggingface/transformers)
    7. PrivateGPT (imartinez/privateGPT)

    AI recommended 7 alternatives but never named jaylfc/taOS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What solutions exist for deploying AI agents across various consumer hardware devices?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO Toolkit
    2. ONNX Runtime
    3. TensorFlow Lite
    4. PyTorch Mobile
    5. NVIDIA JetPack SDK
    6. Core ML
    7. Edge Impulse

    AI recommended 7 alternatives but never named jaylfc/taOS. 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 jaylfc/taOS?
    pass
    AI did not name jaylfc/taOS — 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 jaylfc/taOS in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jaylfc/taOS 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 jaylfc/taOS solve, and who is the primary audience?
    pass
    AI did not name jaylfc/taOS — 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?

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jaylfc/taOS — 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