RRepoGEO

REPOGEO REPORT · LITE

e2b-dev/code-interpreter

Default branch main · commit 8dbc3e47 · scanned 6/19/2026, 11:21:51 AM

GitHub: 2,347 stars · 216 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
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 e2b-dev/code-interpreter, 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 "What is E2B?" section to lead with its SDK nature for AI apps

    Why:

    CURRENT
    E2B is an open-source infrastructure that allows you to run AI-generated code in secure isolated sandboxes in the cloud. To start and control sandboxes, use our JavaScript SDK or Python SDK.
    COPY-PASTE FIX
    E2B is a Python & JavaScript/TypeScript SDK that allows you to embed secure, sandboxed code execution capabilities directly into your AI applications and agents. It provides the infrastructure to run AI-generated code in isolated cloud environments.
  • mediumtopics#2
    Add more specific topics related to AI agent integration and LLM tools

    Why:

    CURRENT
    ai, ai-data-analysis, anthropic, code-interpreter, cohere, gpt, javascript, jupyter, jupyter-notebook, llm, openai, python, typescript
    COPY-PASTE FIX
    ai, ai-agents, ai-data-analysis, anthropic, code-interpreter, cohere, gpt, javascript, jupyter, jupyter-notebook, llm, llm-tools, openai, python, typescript
  • lowreadme#3
    Add a concise "Why E2B?" section to highlight benefits for AI agents

    Why:

    COPY-PASTE FIX
    ## Why E2B for AI?
E2B provides a secure, stateful, and cloud-based environment specifically optimized for AI agents to execute code, install packages, and manage files. Unlike generic container solutions, E2B is designed for seamless integration with LLMs and AI frameworks, offering a dedicated SDK for programmatic control.

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 e2b-dev/code-interpreter
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Docker
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Docker · recommended 2×
  2. gVisor · recommended 2×
  3. Firecracker · recommended 2×
  4. Kata Containers · recommended 1×
  5. NSJail · recommended 1×
  • CATEGORY QUERY
    How to safely execute AI-generated code in an isolated environment for my application?
    you: not recommended
    AI recommended (in order):
    1. Docker
    2. gVisor
    3. Firecracker
    4. Kata Containers
    5. NSJail
    6. chroot

    AI recommended 6 alternatives but never named e2b-dev/code-interpreter. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What SDKs allow embedding code execution capabilities into my LLM-powered application?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Open Interpreter
    4. Marvin
    5. AutoGPT
    6. Jupyter Kernel Gateway
    7. Enterprise Gateway
    8. Docker
    9. Firecracker
    10. gVisor

    AI recommended 10 alternatives but never named e2b-dev/code-interpreter. 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 e2b-dev/code-interpreter?
    pass
    AI named e2b-dev/code-interpreter explicitly

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

  • If a team adopts e2b-dev/code-interpreter in production, what risks or prerequisites should they evaluate first?
    pass
    AI named e2b-dev/code-interpreter 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 e2b-dev/code-interpreter solve, and who is the primary audience?
    pass
    AI named e2b-dev/code-interpreter explicitly

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

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MARKDOWN (README)
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e2b-dev/code-interpreter — 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