RRepoGEO

REPOGEO REPORT · LITE

bytedance/SandboxFusion

Default branch main · commit add46a79 · scanned 5/18/2026, 5:32:42 AM

GitHub: 1,007 stars · 95 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)

2 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 bytedance/SandboxFusion, 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
    Add a concise project description

    Why:

    COPY-PASTE FIX
    A secure, multi-language code sandbox for running and judging code generated by Large Language Models (LLMs), supporting various evaluation benchmarks.
  • highreadme#2
    Clarify the README's main heading for specific LLM use case

    Why:

    CURRENT
    # Code Sandbox
    COPY-PASTE FIX
    # SandboxFusion: Secure Code Sandbox for LLM Evaluation and Benchmarking

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 bytedance/SandboxFusion
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. google/gvisor · recommended 1×
  2. firecracker-microvm/firecracker · recommended 1×
  3. moby/moby · recommended 1×
  4. kata-containers/kata-containers · recommended 1×
  5. google/nsjail · recommended 1×
  • CATEGORY QUERY
    How can I securely execute code snippets generated by large language models?
    you: not recommended
    AI recommended (in order):
    1. gVisor (google/gvisor)
    2. Firecracker (firecracker-microvm/firecracker)
    3. Docker (moby/moby)
    4. Kata Containers (kata-containers/kata-containers)
    5. NSJail (google/nsjail)
    6. Plexus (sagemathinc/plexus)
    7. Wasmtime (bytecodealliance/wasmtime)
    8. Wasmer (wasmerio/wasmer)

    AI recommended 8 alternatives but never named bytedance/SandboxFusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools are available for evaluating LLM code generation across multiple programming languages?
    you: not recommended
    AI recommended (in order):
    1. HumanEval
    2. MultiPL-E
    3. HumanEval-X
    4. CodeContests
    5. MBPP
    6. APPS
    7. BigCode Benchmarks
    8. BigCode-HumanEval
    9. BigCode-MBPP
    10. CodeXGLUE
    11. pytest
    12. JUnit
    13. Google Test
    14. Jest
    15. Go testing

    AI recommended 15 alternatives but never named bytedance/SandboxFusion. 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 bytedance/SandboxFusion?
    pass
    AI named bytedance/SandboxFusion explicitly

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

  • If a team adopts bytedance/SandboxFusion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named bytedance/SandboxFusion 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 bytedance/SandboxFusion solve, and who is the primary audience?
    pass
    AI named bytedance/SandboxFusion 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 bytedance/SandboxFusion. 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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HTML
<a href="https://repogeo.com/en/r/bytedance/SandboxFusion"><img src="https://repogeo.com/badge/bytedance/SandboxFusion.svg" alt="RepoGEO" /></a>
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bytedance/SandboxFusion — 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