RRepoGEO

REPOGEO REPORT · LITE

instavm/coderunner

Default branch main · commit 948095ee · scanned 6/5/2026, 6:26:59 PM

GitHub: 836 stars · 37 forks

AI VISIBILITY SCORE
40 /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
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 instavm/coderunner, 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 emphasize LLM agent sandboxing on macOS

    Why:

    CURRENT
    CodeRunner helps you sandbox your AI agents and its actions inside a sandbox.
    COPY-PASTE FIX
    CodeRunner provides a secure, local sandbox specifically designed for running and testing your AI agents (like Claude Code) on macOS with Apple Silicon, ensuring isolation and preventing data exfiltration.
  • mediumtopics#2
    Add more specific topics for LLM agent development and macOS

    Why:

    CURRENT
    anthropic, apple, apple-container, claude-code, claude-skills, containerization, gemini-cli, llm, llmstudio, mcp, openai
    COPY-PASTE FIX
    anthropic, apple, apple-silicon, claude-code, claude-skills, containerization, firecracker, gemini-cli, llm, llm-agents, llm-development, llmstudio, macos, mcp, micro-vm, openai, sandbox, secure-execution
  • mediumreadme#3
    Add a 'Why CodeRunner?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Why CodeRunner?
Unlike generic container-based sandboxes (like Docker), CodeRunner leverages Firecracker micro-VMs to provide VM-level isolation. This offers significantly stronger security guarantees for executing untrusted AI agent code, minimizing the risk of container escapes and data exfiltration, especially crucial for sensitive LLM agent development on macOS.

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 instavm/coderunner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Docker
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Docker · recommended 1×
  2. AppArmor · recommended 1×
  3. SELinux · recommended 1×
  4. Firejail · recommended 1×
  5. gVisor · recommended 1×
  • CATEGORY QUERY
    How can I securely run large language model agents in a local sandboxed environment?
    you: not recommended
    AI recommended (in order):
    1. Docker
    2. AppArmor
    3. SELinux
    4. Firejail
    5. gVisor
    6. Kata Containers
    7. VirtualBox
    8. VMware Workstation Player
    9. NSjail

    AI recommended 9 alternatives but never named instavm/coderunner. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a secure local environment for developing and testing LLM agents on macOS.
    you: not recommended
    AI recommended (in order):
    1. Docker Desktop
    2. VS Code Dev Containers
    3. ollama
    4. llama-cpp-python
    5. transformers
    6. langchain
    7. LlamaIndex
    8. Conda
    9. Miniconda
    10. Anaconda
    11. Python `venv`
    12. pip
    13. Multipass
    14. VMware Fusion
    15. Parallels Desktop
    16. OrbStack

    AI recommended 16 alternatives but never named instavm/coderunner. 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 instavm/coderunner?
    pass
    AI named instavm/coderunner explicitly

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

  • If a team adopts instavm/coderunner in production, what risks or prerequisites should they evaluate first?
    pass
    AI named instavm/coderunner 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 instavm/coderunner solve, and who is the primary audience?
    pass
    AI named instavm/coderunner 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 instavm/coderunner. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/instavm/coderunner.svg)](https://repogeo.com/en/r/instavm/coderunner)
HTML
<a href="https://repogeo.com/en/r/instavm/coderunner"><img src="https://repogeo.com/badge/instavm/coderunner.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

instavm/coderunner — 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