RRepoGEO

REPOGEO REPORT · LITE

e2b-dev/code-interpreter

Default branch main · commit 4b5da3b9 · scanned 5/9/2026, 2:42:19 PM

GitHub: 2,307 stars · 211 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 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 README's opening to clarify AI agent/LLM code execution focus

    Why:

    CURRENT
    What is E2B? 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
    What is E2B? E2B is an open-source **SDK and infrastructure for AI agents and LLMs** to run AI-generated code in secure, isolated cloud sandboxes. It provides a stateful, cloud-based environment, allowing your AI applications to execute code, persist files, and maintain context across multiple interactions, all controlled via our JavaScript or Python SDKs.
  • mediumreadme#2
    Add a 'Why E2B?' or 'Key Features' section to highlight differentiators

    Why:

    COPY-PASTE FIX
    ## Why E2B?
E2B stands out by offering:
*   **AI-Native Code Execution:** Specifically designed for AI agents and LLMs to execute code.
*   **Secure Cloud Sandboxes:** Run untrusted AI-generated code safely in isolated environments.
*   **Stateful & Persistent:** Maintain context, install packages, and persist files across multiple code executions.
*   **SDK-driven:** Easy integration into your AI applications with Python and JavaScript/TypeScript SDKs.
  • lowtopics#3
    Add 'sandbox' and 'code-execution' to topics

    Why:

    CURRENT
    ai, ai-data-analysis, anthropic, code-interpreter, cohere, gpt, javascript, jupyter, jupyter-notebook, llm, openai, python, typescript
    COPY-PASTE FIX
    ai, ai-data-analysis, anthropic, code-interpreter, cohere, gpt, javascript, jupyter, jupyter-notebook, llm, openai, python, typescript, sandbox, code-execution

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
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. containerd/containerd · recommended 1×
  5. pypy/pypy · recommended 1×
  • CATEGORY QUERY
    How can I safely execute AI-generated code snippets within my application's backend?
    you: not recommended
    AI recommended (in order):
    1. gVisor (google/gvisor)
    2. Firecracker (firecracker-microvm/firecracker)
    3. Docker (moby/moby)
    4. containerd (containerd/containerd)
    5. PyPy (pypy/pypy)
    6. Node.js `vm` module (nodejs/node)
    7. Wasmtime (bytecodealliance/wasmtime)
    8. Wasmer (wasmerio/wasmer)
    9. AWS Lambda
    10. Google Cloud Functions

    AI recommended 10 alternatives but never named e2b-dev/code-interpreter. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What SDKs allow programmatic execution of LLM-generated Python code for data analysis?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Evals
    2. OpenAI Function Calling
    3. execjs
    4. LangChain
    5. PythonREPLTool
    6. LlamaIndex
    7. Jupyter Kernel Gateway
    8. Papermill
    9. RestrictedPython

    AI recommended 9 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 did not name e2b-dev/code-interpreter — 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 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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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