REPOGEO REPORT · LITE

Siddhant-Goswami/100x-LLM

Default branch main · commit b96ac280 · scanned 6/9/2026, 4:48:01 PM

GitHub: 523 stars · 207 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 Siddhant-Goswami/100x-LLM, 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 comprehensive topics to improve categorization

Why:

COPY-PASTE FIX

llm, large-language-models, ai-agents, prompt-engineering, rag, retrieval-augmented-generation, full-stack-ai, llm-applications, python, machine-learning, deep-learning, openai, groq, llamaindex, fastapi, streamlit

highreadme#2

Reposition README's opening to emphasize practical code implementations

Why:

CURRENT

Welcome to the 100x Applied AI repository! This is a comprehensive resource for learning and implementing Large Language Model (LLM) & Agentic applications. Whether you're a complete beginner or looking to enhance your AI engineering skills, this guide will help you navigate through practical implementations.

COPY-PASTE FIX

Welcome to the 100x Applied AI repository! This is a comprehensive collection of **140+ practical code implementations and examples** for building Large Language Model (LLM) & Agentic applications. Whether you're a complete beginner or an experienced developer, this guide provides hands-on code to master full-stack AI, prompt engineering, RAG, tool calling, and LLM workflows.

mediumabout#3

Strengthen the repository description

Why:

CURRENT

Code snippets and examples from the 100x Applied AI cohort lectures.

COPY-PASTE FIX

140+ practical code implementations and examples for building full-stack LLM and AI Agent applications, covering prompt engineering, RAG, and tool calling.

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 Siddhant-Goswami/100x-LLM

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

langchain-ai/langchain

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchain · recommended 1×
run-llama/llama_index · recommended 1×
huggingface/transformers · recommended 1×
Hugging Face Spaces · recommended 1×
gradio-app/gradio · recommended 1×

CATEGORY QUERY
How can I find practical code examples for building full-stack LLM applications?
you: not recommended
AI recommended (in order):
1. LangChain (langchain-ai/langchain)
2. LlamaIndex (run-llama/llama_index)
3. Hugging Face Transformers (huggingface/transformers)
4. Hugging Face Spaces
5. Gradio (gradio-app/gradio)
6. Streamlit (streamlit/streamlit)
AI recommended 6 alternatives but never named Siddhant-Goswami/100x-LLM. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Where can I find comprehensive guides and code for RAG and tool calling with LLMs?
you: not recommended
AI recommended (in order):
1. LangChain
2. LlamaIndex
3. OpenAI
4. Hugging Face Transformers Library
5. DeepLearning.AI
6. Google AI for Developers
AI recommended 6 alternatives but never named Siddhant-Goswami/100x-LLM. 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 Siddhant-Goswami/100x-LLM?
pass
AI named Siddhant-Goswami/100x-LLM explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts Siddhant-Goswami/100x-LLM in production, what risks or prerequisites should they evaluate first?
pass
AI named Siddhant-Goswami/100x-LLM 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 Siddhant-Goswami/100x-LLM solve, and who is the primary audience?
pass
AI did not name Siddhant-Goswami/100x-LLM — 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?

Embed your GEO score

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MARKDOWN (README)

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Siddhant-Goswami/100x-LLM — 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