REPOGEO REPORT · LITE

NVIDIA/RULER

Default branch main · commit ab17b785 · scanned 5/24/2026, 7:02:43 AM

GitHub: 1,543 stars · 127 forks

AI VISIBILITY SCORE

35 /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

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 NVIDIA/RULER, 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 the repository

Why:

CURRENT

(none)

COPY-PASTE FIX

llm-evaluation, long-context-llm, llm-benchmarking, language-model-evaluation, nlp, deep-learning, context-window

highreadme#2

Add a disambiguation sentence to the README introduction

Why:

CURRENT

This repository contains code for our paper RULER: What’s the Real Context Size of Your Long-Context Language Models. RULER generates synthetic examples to evaluate long-context language models with configurable sequence length and task complexity.

COPY-PASTE FIX

This repository contains code for our paper RULER: What’s the Real Context Size of Your Long-Context Language Models. Unlike other projects named RULER, this repository specifically focuses on evaluating long-context language models. RULER generates synthetic examples to evaluate long-context language models with configurable sequence length and task complexity.

mediumhomepage#3
Add the paper's project page or a relevant external link as the homepage
Why:
CURRENT
```
(none)
```
COPY-PASTE FIX
```
[Insert URL of the paper's project page or a relevant external link here]
```

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 NVIDIA/RULER

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LongBench

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

LongBench · recommended 2×
LangChain · recommended 2×
NarrativeQA · recommended 2×
Needle-in-a-Haystack (NIAH) Test · recommended 1×
L-Eval · recommended 1×

CATEGORY QUERY
How can I effectively benchmark the long-context understanding of different large language models?
you: not recommended
AI recommended (in order):
1. LongBench
2. Needle-in-a-Haystack (NIAH) Test
3. LangChain
4. L-Eval
5. HotpotQA
6. ELI5 (Explain Like I'm 5)
7. NarrativeQA
8. ArXiv Long Abstract Summarization
9. Multi-News
10. DialogSum
11. SAMSum
12. HumanEval
13. CodeXGLUE
14. Faker
AI recommended 14 alternatives but never named NVIDIA/RULER. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools help assess the true effective context window of large language models?
you: not recommended
AI recommended (in order):
1. Original NIAH
2. Llama-recipes
3. LM-Harness
4. Hugging Face `transformers` library
5. NarrativeQA
6. QMSum
7. LongBench
8. LangChain
9. LlamaIndex
AI recommended 9 alternatives but never named NVIDIA/RULER. 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 NVIDIA/RULER?
pass
AI named NVIDIA/RULER explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts NVIDIA/RULER in production, what risks or prerequisites should they evaluate first?
pass
AI named NVIDIA/RULER 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 NVIDIA/RULER solve, and who is the primary audience?
pass
AI named NVIDIA/RULER 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 NVIDIA/RULER. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/NVIDIA/RULER.svg)](https://repogeo.com/en/r/NVIDIA/RULER)

HTML

<a href="https://repogeo.com/en/r/NVIDIA/RULER"><img src="https://repogeo.com/badge/NVIDIA/RULER.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

NVIDIA/RULER — 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