REPOGEO REPORT · LITE

InternRobotics/PointLLM

Default branch master · commit cb72f4e6 · scanned 6/28/2026, 2:47:45 PM

GitHub: 1,031 stars · 58 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

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 InternRobotics/PointLLM, 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

highlicense#1

Add a standard open-source LICENSE file

Why:

COPY-PASTE FIX

Create a `LICENSE` file in the repository root, containing the text of a standard open-source license such as MIT or Apache-2.0.

highreadme#2

Add a clear positioning statement at the top of the README

Why:

CURRENT

The README immediately starts with an academic description and author list.

COPY-PASTE FIX

Insert the following sentence directly after the main title/author block and before the "About" section: "PointLLM serves as a foundational framework for integrating large language models with direct 3D point cloud understanding, enabling the creation of advanced conversational AI applications that reason about spatial information."

mediumreadme#3

Add a 'Quick Start' or 'Integration' section to the README

Why:

COPY-PASTE FIX

Add a new section titled "Quick Start" or "Integration Guide" to the README, providing concrete code snippets or steps on how to set up and use PointLLM for a basic 3D point cloud understanding task or conversational interaction.

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 InternRobotics/PointLLM

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Open3D

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Open3D · recommended 1×
GPT-4 · recommended 1×
Claude 3 Opus · recommended 1×
PointCLIP · recommended 1×
PointCLIP V2 · recommended 1×

CATEGORY QUERY
How can I integrate large language models with 3D point cloud data for interpretation?
you: not recommended
AI recommended (in order):
1. Open3D
2. GPT-4
3. Claude 3 Opus
4. PointCLIP
5. PointCLIP V2
6. GPT-3.5
7. Llama 3
8. LlamaIndex
9. LangChain
10. PyTorch3D
11. PCL
12. Google Gemini Pro
13. Mistral Large
14. Kaolin
15. ChatGPT
16. Cohere Command R+
17. GPT-4o
AI recommended 17 alternatives but never named InternRobotics/PointLLM. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools help build conversational AI that understands and processes 3D spatial information?
you: not recommended
AI recommended (in order):
1. NVIDIA Omniverse
2. NVIDIA Isaac Sim
3. NVIDIA Riva
4. Unity
5. ROS (Robot Operating System)
6. Hugging Face Transformers (huggingface/transformers)
7. spaCy (explosion/spaCy)
8. Unreal Engine
9. Open3D (isl-org/Open3D)
10. PyTorch (pytorch/pytorch)
11. TensorFlow (tensorflow/tensorflow)
12. Gazebo (osrf/gazebo)
13. Microsoft AirSim (microsoft/airsim)
AI recommended 13 alternatives but never named InternRobotics/PointLLM. 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 InternRobotics/PointLLM?
pass
AI named InternRobotics/PointLLM explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts InternRobotics/PointLLM in production, what risks or prerequisites should they evaluate first?
pass
AI named InternRobotics/PointLLM 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 InternRobotics/PointLLM solve, and who is the primary audience?
pass
AI named InternRobotics/PointLLM 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 InternRobotics/PointLLM. 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/InternRobotics/PointLLM.svg)](https://repogeo.com/en/r/InternRobotics/PointLLM)

HTML

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

Pro

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InternRobotics/PointLLM — 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