RRepoGEO

REPOGEO REPORT · LITE

superhq-ai/shuru

Default branch main · commit dae974da · scanned 6/8/2026, 9:51:59 PM

GitHub: 775 stars · 26 forks

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 superhq-ai/shuru, 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
  • highreadme#1
    Strengthen the README's opening to emphasize 'AI agents' and 'microVM sandbox'

    Why:

    CURRENT
    # shuru

Local-first microVM sandbox for AI agents on macOS, with experimental Linux support.

Shuru boots lightweight Linux VMs for AI agents. On macOS it uses Apple's Virtualization.framework. On Linux it uses a KVM backend that is now available as an experimental release build for ARM64 hosts. Every sandbox is ephemeral: the rootfs resets on every run, giving agents a disposable environment to execute code, install packages, and run tools without touching your host.
    COPY-PASTE FIX
    # shuru

**The local-first microVM sandbox specifically designed for safely running AI agents on macOS & Linux.**

Shuru provides lightweight, ephemeral Linux VMs for AI agents, ensuring a secure and disposable environment for executing untrusted code, installing packages, and running tools without impacting your host system. It leverages Apple's Virtualization.framework on macOS and an experimental KVM backend for ARM64 Linux hosts.
  • mediumreadme#2
    Add a 'Why Shuru?' or 'Comparison' section to explicitly differentiate from general virtualization

    Why:

    COPY-PASTE FIX
    ## Why Shuru?

While general virtualization and containerization tools like Docker, Firecracker, or gVisor offer isolation, Shuru is purpose-built and optimized for the unique needs of AI agents:

-   **AI-First Design:** Tailored for the specific workflows of AI agents, providing a secure, ephemeral environment for code execution, tool use, and package installation.
-   **MicroVM Efficiency:** Boots lightweight Linux VMs rapidly, offering stronger isolation than containers with minimal overhead.
-   **Ephemeral Sandboxes:** Each run provides a clean, disposable rootfs, ideal for testing untrusted agent code without persistent side effects.
-   **Local-First:** Designed for seamless local development and testing on macOS (Apple Silicon) and experimental Linux (ARM64).

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 superhq-ai/shuru
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
google/gvisor
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. google/gvisor · recommended 2×
  2. kata-containers/kata-containers · recommended 2×
  3. Docker · recommended 1×
  4. Podman · recommended 1×
  5. aws/firecracker · recommended 1×
  • CATEGORY QUERY
    How to safely execute untrusted AI agent code locally in an isolated environment?
    you: not recommended
    AI recommended (in order):
    1. Docker
    2. Podman
    3. Firecracker (aws/firecracker)
    4. gVisor (google/gvisor)
    5. Kata Containers (kata-containers/kata-containers)
    6. VirtualBox
    7. VMware Workstation Player
    8. NSjail (google/nsjail)
    9. chroot

    AI recommended 9 alternatives but never named superhq-ai/shuru. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a lightweight virtual machine solution for running AI agents with ephemeral sandboxes.
    you: not recommended
    AI recommended (in order):
    1. Firecracker (firecracker-microvm/firecracker)
    2. Kata Containers (kata-containers/kata-containers)
    3. gVisor (google/gvisor)
    4. QEMU (qemu/qemu)
    5. OSv (osv-team/osv)
    6. Nanos (nanos-world/nanos)

    AI recommended 6 alternatives but never named superhq-ai/shuru. 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 superhq-ai/shuru?
    pass
    AI named superhq-ai/shuru explicitly

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

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