REPOGEO REPORT · LITE

tvytlx/ai-agent-deep-dive

Default branch main · commit b86a62b5 · scanned 5/27/2026, 12:23:34 PM

GitHub: 5,738 stars · 1,650 forks

AI VISIBILITY SCORE

30 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 0 warn · 1 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 tvytlx/ai-agent-deep-dive, 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

hightopics#1

Add relevant topics to improve categorization

Why:

COPY-PASTE FIX

ai-agent, agent, python, deep-dive, learning, education, tutorial, source-code, llm, generative-ai

highlicense#2

Add a LICENSE file to the repository

Why:

COPY-PASTE FIX

Create a `LICENSE` file in the repository root containing the text of a common open-source license like MIT or Apache 2.0.

mediumreadme#3

Add a concise introductory sentence to the README

Why:

CURRENT

# AI Agent Deep Dive

<a href="https://www.star-history.com/?repos=tvytlx%2Fai-agent-deep-dive&type=date&legend=top-left">
 <picture>
   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=tvytlx/ai-agent-deep-dive&type=date&theme=dark&legend=top-left" />
   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=tvytlx/ai-agent-deep-dive&type=date&legend=top-left" />
   
 </picture>
</a>

## Quick Links

COPY-PASTE FIX

# AI Agent Deep Dive

This repository provides a deep dive into AI agent source code, featuring a minimal Python AI Agent project designed for teaching and learning the core structure of AI agents.

<a href="https://www.star-history.com/?repos=tvytlx%2Fai-agent-deep-dive&type=date&legend=top-left">
 <picture>
   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=tvytlx/ai-agent-deep-dive&type=date&theme=dark&legend=top-left" />
   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=tvytlx/ai-agent-deep-dive&type=date&legend=top-left" />
   
 </picture>
</a>

## Quick Links

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 tvytlx/ai-agent-deep-dive

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Python

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Python · recommended 1×
TensorFlow · recommended 1×
PyTorch · recommended 1×
scikit-learn · recommended 1×
NumPy · recommended 1×

CATEGORY QUERY
What are the essential building blocks for creating a basic AI agent?
you: not recommended
AI recommended (in order):
1. Python
2. TensorFlow
3. PyTorch
4. scikit-learn
5. NumPy
6. Pandas
7. NLTK (Natural Language Toolkit)
8. spaCy
9. Gym (now part of Gymnasium)
AI recommended 9 alternatives but never named tvytlx/ai-agent-deep-dive. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Where can I find a minimal Python AI agent project for learning purposes?
you: not recommended
AI recommended (in order):
1. Micrograd (karpathy/micrograd)
2. OpenAI Gym (openai/gym)
3. NanoGPT (karpathy/nanogpt)
4. Minigrid (Farama-Foundation/Minigrid)
5. PyTorch (pytorch/pytorch)
6. TensorFlow (tensorflow/tensorflow)
AI recommended 6 alternatives but never named tvytlx/ai-agent-deep-dive. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
fail
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 tvytlx/ai-agent-deep-dive?
pass
AI named tvytlx/ai-agent-deep-dive explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts tvytlx/ai-agent-deep-dive in production, what risks or prerequisites should they evaluate first?
pass
AI named tvytlx/ai-agent-deep-dive 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 tvytlx/ai-agent-deep-dive solve, and who is the primary audience?
pass
AI named tvytlx/ai-agent-deep-dive 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 tvytlx/ai-agent-deep-dive. 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)

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HTML

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tvytlx/ai-agent-deep-dive — 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