REPOGEO REPORT · LITE

SeungyounShin/Llama2-Code-Interpreter

Default branch main · commit 466dc2c2 · scanned 6/15/2026, 1:03:12 PM

GitHub: 681 stars · 88 forks

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 SeungyounShin/Llama2-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 opening to clarify its specialized role as a code interpreter framework.

Why:

CURRENT

This project allows LLM to generate code, execute it, receive feedback, debug, and answer questions based on the whole process. It is designed to be intuitive and versatile, capable of dealing with multiple languages and frameworks.

COPY-PASTE FIX

This project offers a focused, intuitive framework for enabling LLMs like Llama2 to generate, execute, and debug code within a controlled environment. It provides a direct, specialized approach to integrating code execution, feedback, and debugging loops, distinguishing it from broader LLM agent frameworks.

mediumtopics#2

Add more specific topics to improve categorization.

Why:

CURRENT

codeinterpreter, codellama, llama, llm

COPY-PASTE FIX

code-interpreter, codellama, llama, llm, code-execution, debugging, llm-agents, ai-tools, python-interpreter

mediumlicense#3
Add a LICENSE file to clarify usage terms.
Why:
CURRENT
```
(no LICENSE file detected)
```
COPY-PASTE FIX
```
Create a LICENSE file (e.g., MIT License) in the repository root.
```

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 SeungyounShin/Llama2-Code-Interpreter

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LangChain

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

LangChain · recommended 2×
Auto-GPT · recommended 2×
BabyAGI · recommended 2×
OpenAI GPT-4 · recommended 1×
OpenAI Function Calling · recommended 1×

CATEGORY QUERY
How can I enable an AI model to generate, execute, and debug its own code?
you: not recommended
AI recommended (in order):
1. LangChain
2. Auto-GPT
3. BabyAGI
4. OpenAI GPT-4
5. OpenAI Function Calling
6. GPT-3.5 Turbo
7. Jupyter Kernels
8. ipykernel
9. jupyter_client
10. Replit AI
11. Google Colab APIs
AI recommended 11 alternatives but never named SeungyounShin/Llama2-Code-Interpreter. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools help large language models interact with code execution environments for debugging?
you: not recommended
AI recommended (in order):
1. Cursor
2. VS Code
3. GitHub Copilot Chat
4. CodeGPT
5. Continue
6. OpenAI's Code Interpreter
7. LangChain
8. Auto-GPT
9. BabyAGI
10. Google's Project IDX
AI recommended 10 alternatives but never named SeungyounShin/Llama2-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
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 SeungyounShin/Llama2-Code-Interpreter?
pass
AI did not name SeungyounShin/Llama2-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 SeungyounShin/Llama2-Code-Interpreter in production, what risks or prerequisites should they evaluate first?
pass
AI named SeungyounShin/Llama2-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 SeungyounShin/Llama2-Code-Interpreter solve, and who is the primary audience?
pass
AI named SeungyounShin/Llama2-Code-Interpreter 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 SeungyounShin/Llama2-Code-Interpreter. 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)

[![RepoGEO](https://repogeo.com/badge/SeungyounShin/Llama2-Code-Interpreter.svg)](https://repogeo.com/en/r/SeungyounShin/Llama2-Code-Interpreter)

HTML

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SeungyounShin/Llama2-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