REPOGEO REPORT · LITE

dexmal/dexbotic

Default branch main · commit e2753a1e · scanned 6/17/2026, 5:02:10 PM

GitHub: 1,220 stars · 173 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

33 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 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 dexmal/dexbotic, 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

highabout#1

Clarify the 'About' description to explicitly counter miscategorization

Why:

CURRENT

Dexbotic: Open-Source Vision-Language-Action Toolbox

COPY-PASTE FIX

Dexbotic: An open-source Vision-Language-Action (VLA) toolbox for embodied AI and robotics research. Not a DEX trading bot.

mediumreadme#2

Enhance README introduction with more specific keywords and use cases

Why:

CURRENT

**Dexbotic** is a VLA (Vision-Language-Action) development toolbox built on the PyTorch framework, designed to provide a unified and efficient solution for embodied intelligence research.

COPY-PASTE FIX

**Dexbotic** is a comprehensive Vision-Language-Action (VLA) development toolbox built on PyTorch, specifically designed for embodied AI and robotics. It provides a unified and efficient solution for researchers and developers to reproduce, fine-tune, and infer cutting-edge VLA algorithms for real-world manipulation and navigation tasks.

lowtopics#3

Add more specific and general category topics

Why:

CURRENT

codebase, cogact, memoryvla, openvla-oft, pi0, real-world, robotics, simulation, toolbox, vla, vln

COPY-PASTE FIX

codebase, cogact, memoryvla, openvla-oft, pi0, real-world, robotics, simulation, toolbox, vla, vln, pytorch, deep-learning, embodied-ai, reinforcement-learning

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 dexmal/dexbotic

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenVLA

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

OpenVLA · recommended 1×
Robotics Transformer (RT-X) · recommended 1×
Hugging Face Transformers · recommended 1×
RLlib · recommended 1×
PyTorch Lightning · recommended 1×

CATEGORY QUERY
What open-source toolkits are available for developing vision-language-action models in robotics?
you: not recommended
AI recommended (in order):
1. OpenVLA
2. Robotics Transformer (RT-X)
3. Hugging Face Transformers
4. RLlib
5. PyTorch Lightning
6. TensorFlow Keras
AI recommended 6 alternatives but never named dexmal/dexbotic. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Need a PyTorch framework for pretraining and fine-tuning embodied intelligence models for real-world robotics.
you: not recommended
AI recommended (in order):
1. RLlib (ray-project/ray)
2. Stable Baselines3 (DLR-RM/stable-baselines3)
3. Surreal Robotics (StanfordVL/Surreal)
4. OpenSpiel (deepmind/open_spiel)
5. PyTorch Lightning (Lightning-AI/lightning)
AI recommended 5 alternatives but never named dexmal/dexbotic. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
pass
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 dexmal/dexbotic?
pass
AI named dexmal/dexbotic explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts dexmal/dexbotic in production, what risks or prerequisites should they evaluate first?
pass
AI named dexmal/dexbotic 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 dexmal/dexbotic solve, and who is the primary audience?
pass
AI did not name dexmal/dexbotic — 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?

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MARKDOWN (README)

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Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite