REPOGEO REPORT · LITE

valentinfrlch/ha-llmvision

Default branch main · commit 85fcb983 · scanned 6/23/2026, 12:22:23 PM

GitHub: 1,387 stars · 123 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

40 /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

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 valentinfrlch/ha-llmvision, 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

highreadme#1

Strengthen README opening to highlight Home Assistant LLM integration and differentiation

Why:

CURRENT

LLM Vision is a Home Assistant integration that uses multimodal large language models to analyze images, videos, live camera feeds, and Frigate events.

COPY-PASTE FIX

LLM Vision is a Home Assistant integration that elevates your smart home cameras with multimodal large language models. It goes beyond basic object detection (like Frigate) by providing deep contextual understanding and conversational AI for your live feeds, videos, and Frigate events.

mediumcomparison#2

Add a dedicated comparison section to the README

Why:

COPY-PASTE FIX

Add a new section, e.g., '## LLM Vision vs. Other Solutions' or '## Why LLM Vision?' that compares it to Frigate, DeepStack, or even just general LLMs (GPT-4o, Gemini) in the context of Home Assistant. Focus on its unique 'multimodal LLM integration for Home Assistant' aspect.

lowexamples#3

Add concrete use cases or examples to the README

Why:

COPY-PASTE FIX

Add a '## Use Cases' or '## Examples' section with 2-3 bullet points describing common scenarios, e.g., 'Ask Assist about a package delivery,' 'Get notified if a pet is on the counter,' 'Summarize activity while you were away.'

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 valentinfrlch/ha-llmvision

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Frigate

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Frigate · recommended 1×
DeepStack · recommended 1×
Blue Iris · recommended 1×
CodeProject.AI Server · recommended 1×
Agent DVR · recommended 1×

CATEGORY QUERY
How can I integrate AI-powered visual analysis into my Home Assistant setup?
you: not recommended
AI recommended (in order):
1. Frigate
2. DeepStack
3. Blue Iris
4. CodeProject.AI Server
5. Agent DVR
6. MotionEye
7. OpenCV
AI recommended 7 alternatives but never named valentinfrlch/ha-llmvision. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools use multimodal LLMs for smart home camera event monitoring and notifications?
you: not recommended
AI recommended (in order):
1. Home Assistant (home-assistant/core)
2. Frigate (blakeblackshear/frigate)
3. GPT-4o
4. Google Gemini
5. Llama 3
6. DeepMotion
7. OpenCV AI Kit (OAK) cameras (luxonis/depthai-python)
8. OAK-D Pro PoE
9. GPT-4o Vision API
10. Google Gemini Vision API
11. Wyze Cam Plus
12. IFTTT
13. Ring Alarm Pro
14. Ring Edge
AI recommended 14 alternatives but never named valentinfrlch/ha-llmvision. 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 valentinfrlch/ha-llmvision?
pass
AI named valentinfrlch/ha-llmvision explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts valentinfrlch/ha-llmvision in production, what risks or prerequisites should they evaluate first?
pass
AI named valentinfrlch/ha-llmvision 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 valentinfrlch/ha-llmvision solve, and who is the primary audience?
pass
AI named valentinfrlch/ha-llmvision explicitly
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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HTML

<a href="https://repogeo.com/en/r/valentinfrlch/ha-llmvision"><img src="https://repogeo.com/badge/valentinfrlch/ha-llmvision.svg" alt="RepoGEO" /></a>

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valentinfrlch/ha-llmvision — 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