RRepoGEO

REPOGEO REPORT · LITE

osaurus-ai/osaurus

Default branch main · commit 18c75a28 · scanned 5/29/2026, 4:46:49 AM

GitHub: 5,525 stars · 300 forks

AI VISIBILITY SCORE
33 /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
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 osaurus-ai/osaurus, 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
    Clarify README's opening paragraph to emphasize macOS agent orchestration

    Why:

    CURRENT
    <p align="center">
  <strong>Own your AI.</strong><br>
  Agents, memory, tools, and identity that live on your Mac. Built purely in Swift. Fully offline. Open source.
</p>
    COPY-PASTE FIX
    <p align="center">
  <strong>Own your AI.</strong><br>
  Osaurus is the native macOS orchestration platform for AI agents, providing persistent memory, tool integration, and cryptographic identity, all running fully offline and built purely in Swift.
</p>
  • mediumtopics#2
    Add specific topics for AI agents, macOS, and offline capabilities

    Why:

    CURRENT
    anthropic, apple-foundation-models, apple-intelligence, apple-neural-engine, llm, mcp, mcp-server, mlx, openai, swift
    COPY-PASTE FIX
    anthropic, apple-foundation-models, apple-intelligence, apple-neural-engine, llm, mcp, mcp-server, mlx, openai, swift, ai-agents, macos-app, offline-ai, local-ai, ai-orchestration, agent-framework, persistent-memory
  • lowreadme#3
    Add a 'Why Osaurus?' section to explicitly state core differentiators

    Why:

    COPY-PASTE FIX
    ## Why Osaurus?

Models are getting cheaper and more interchangeable by the day. What's irreplaceable is the layer around them -- your context, your memory, your tools, your identity. Others keep that layer on their servers. Osaurus keeps it on your machine.

Osaurus is the AI harness for macOS. It sits between you and any model -- local or cloud -- and provides the continuity that makes AI personal. It emphasizes privacy-first, self-hostable, local-first processing and user autonomy, ensuring your data never leaves your environment unless explicitly configured.

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 osaurus-ai/osaurus
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ggerganov/llama.cpp
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ggerganov/llama.cpp · recommended 2×
  2. ollama/ollama · recommended 1×
  3. chroma-core/chroma · recommended 1×
  4. facebookresearch/faiss · recommended 1×
  5. LM Studio · recommended 1×
  • CATEGORY QUERY
    How can I run AI agents locally on my Mac with persistent memory and offline capabilities?
    you: not recommended
    AI recommended (in order):
    1. Ollama (ollama/ollama)
    2. Chroma (chroma-core/chroma)
    3. FAISS (facebookresearch/faiss)
    4. LM Studio
    5. LocalAI (go-skynet/LocalAI)
    6. Llama.cpp (ggerganov/llama.cpp)
    7. LangChain (langchain-ai/langchain)

    AI recommended 7 alternatives but never named osaurus-ai/osaurus. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best open source Swift tools for building autonomous AI agents on macOS?
    you: not recommended
    AI recommended (in order):
    1. SwiftAI (Swift-AI/SwiftAI)
    2. Swift-AI
    3. Core ML Tools (apple/coremltools)
    4. SwiftNIO (apple/swift-nio)
    5. LLaMA.cpp (ggerganov/llama.cpp)
    6. OpenCV (opencv/opencv)
    7. Swift ArgumentParser (apple/swift-argument-parser)

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

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite