RRepoGEO

REPOGEO REPORT · LITE

e2b-dev/e2b-cookbook

Default branch main · commit 65d76b73 · scanned 6/23/2026, 5:48:01 PM

GitHub: 1,364 stars · 243 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
28 /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
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/e2b-cookbook, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root. If the E2B SDK is proprietary, state the terms clearly. If it's open source, choose an appropriate SPDX-compatible license like MIT or Apache-2.0 and include the full text.
  • highreadme#2
    Reposition README H1 to highlight E2B's core offering

    Why:

    CURRENT
    # ✴️ E2B Cookbook
    
    Example code and guides for building with E2B SDK.
    COPY-PASTE FIX
    # ✴️ E2B Cookbook: Examples & Guides for E2B's AI Code Interpreter & Secure Sandbox SDK
    
    Example code and guides for building with E2B's AI code interpreter and secure sandbox SDK.
  • mediumabout#3
    Update repository description and topics for clarity

    Why:

    CURRENT
    Description: Examples of using E2B
    Topics: agent, ai, ai-agents, code-interpreter, cookbook, devtools, e2b, example, gpt, gpt4, guides, javascript, llm, openai, python, python3, sdk, tutorial, typescript
    COPY-PASTE FIX
    Description: Practical examples and guides for building with E2B's AI code interpreter and secure sandbox SDK.
    Topics: agent, ai-agents, code-interpreter, cookbook, devtools, e2b, gpt, gpt4, javascript, llm, openai, python, python3, sdk, typescript, ai-code-interpreter, secure-sandbox, agentic-workflows, 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/e2b-cookbook
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenInterpreter/OpenInterpreter
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenInterpreter/OpenInterpreter · recommended 1×
  2. langchain-ai/langchain · recommended 1×
  3. Docker · recommended 1×
  4. firecracker-microvm/firecracker · recommended 1×
  5. Significant-Gravitas/AutoGPT · recommended 1×
  • CATEGORY QUERY
    How to build AI agents that can execute code in a secure sandbox?
    you: not recommended
    AI recommended (in order):
    1. Open Interpreter (OpenInterpreter/OpenInterpreter)
    2. LangChain (langchain-ai/langchain)
    3. Docker
    4. Firecracker (firecracker-microvm/firecracker)
    5. AutoGPT (Significant-Gravitas/AutoGPT)
    6. nsjail (google/nsjail)
    7. Code Interpreter API (OpenAI)
    8. Azure OpenAI Code Interpreter
    9. Jupyter Kernel Gateway (jupyter/kernel_gateway)
    10. Piston (piston-bot/piston)

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

    Show full AI answer
  • CATEGORY QUERY
    Looking for Python examples to integrate large language models with agentic workflows.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack (deepset/haystack)
    4. CrewAI
    5. AutoGPT
    6. Transformers

    AI recommended 6 alternatives but never named e2b-dev/e2b-cookbook. 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 e2b-dev/e2b-cookbook?
    pass
    AI did not name e2b-dev/e2b-cookbook — 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/e2b-cookbook in production, what risks or prerequisites should they evaluate first?
    pass
    AI named e2b-dev/e2b-cookbook 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/e2b-cookbook solve, and who is the primary audience?
    pass
    AI named e2b-dev/e2b-cookbook 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/e2b-cookbook — 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