RRepoGEO

REPOGEO REPORT · LITE

shroominic/codeinterpreter-api

Default branch main · commit 9482d36f · scanned 5/17/2026, 2:51:46 PM

GitHub: 3,850 stars · 391 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
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 shroominic/codeinterpreter-api, 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 its role as a self-hostable API for LLM agents

    Why:

    CURRENT
    # 👾 Code Interpreter API

A LangChain implementation of the ChatGPT Code Interpreter.
Using CodeBoxes as backend for sandboxed python code execution.
    COPY-PASTE FIX
    # 👾 Code Interpreter API: Self-Hostable Alternative to ChatGPT's Code Interpreter

An open-source, self-hostable API that replicates the interactive, stateful, and data-centric code execution environment of the proprietary ChatGPT Code Interpreter. Integrate dynamic, sandboxed Python code execution and data analysis into your LLM applications.
  • mediumtopics#2
    Add more specific topics to clarify its function as an API and an open-source alternative

    Why:

    CURRENT
    chatgpt, chatgpt-code-generation, code-interpreter, codeinterpreter, langchain, llm-agent
    COPY-PASTE FIX
    chatgpt, chatgpt-code-generation, code-interpreter, codeinterpreter, langchain, llm-agent, api, self-hosted, open-source-alternative, llm-api, code-execution-api, sandboxed-execution
  • lowcomparison#3
    Add a dedicated 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Unlike generic sandboxing solutions (e.g., Docker, Piston) or data analysis tools (e.g., Jupyter, Superset), Code Interpreter API is specifically designed as a drop-in, self-hostable API for LLM agents, directly replicating the capabilities of OpenAI's proprietary ChatGPT Code Interpreter. This provides a dedicated, stateful environment for LLMs to perform complex tasks like data analysis, charting, and image manipulation with internet access and automatic package installation, all within your own infrastructure.

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 shroominic/codeinterpreter-api
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Piston
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Piston · recommended 1×
  2. Jupyter Kernel Gateway · recommended 1×
  3. Docker · recommended 1×
  4. Google Cloud Run · recommended 1×
  5. AWS Lambda · recommended 1×
  • CATEGORY QUERY
    How can I add sandboxed Python code execution capabilities to my LLM application?
    you: not recommended
    AI recommended (in order):
    1. Piston
    2. Jupyter Kernel Gateway
    3. Docker
    4. Google Cloud Run
    5. AWS Lambda
    6. Executors
    7. RestrictedPython
    8. PySandbox

    AI recommended 8 alternatives but never named shroominic/codeinterpreter-api. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an open-source tool to enable data analysis and charting for my AI agent.
    you: not recommended
    AI recommended (in order):
    1. Jupyter Notebook/JupyterLab
    2. Apache Superset
    3. Plotly Dash
    4. Grafana
    5. Metabase
    6. Redash

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

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

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shroominic/codeinterpreter-api — 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