Element to LLM ავტორი insitu.im
Give AI eyes. One click captures live UI state — Claude, GPT, Gemini act on what they actually see.
16 მომხმარებელი16 მომხმარებელი
გაფართოების მონაცემები
ეკრანის სურათები
გაფართოების შესახებ
Element to LLM — AI Agent Perception Layer
Your AI agent is blind.
It guesses from screenshots. Drowns in raw HTML.
Misses what users actually see.
Element to LLM fixes this.
One click. Your browser's live UI state — structured,
semantic, token-efficient — delivered to any LLM.
Claude, GPT, Gemini, Llama. Your choice.
Now your AI agent doesn't guess. It sees.
━━━━━━━━━━━━━━━━━━━━━━
🤖 Built for AI Agents
The era of AI agents is here.
Agents that fill forms, navigate apps, debug interfaces,
automate workflows — they all need one thing:
accurate perception of the UI.
Element to LLM is that perception layer.
Not screenshots (no element IDs, burns tokens).
Not raw HTML (2.3MB of noise).
Not accessibility trees (miss visual context).
SiFR v2 — structured, semantic, actionable:
→ Every element labeled and scored by importance
→ Actions tagged: [clickable] [fillable] [hoverable]
→ Spatial relationships mapped
→ Smaller than raw HTML
→ Zero system prompt overhead — live DOM is the context
Your agent stops hallucinating UI elements.
It acts on what's actually there.
━━━━━━━━━━━━━━━━━━━━━━
⚡ What changes when AI sees your screen
Before E2LLM:
"There's a button somewhere on the left, I think it says Submit..."
After E2LLM:
AI receives: btn_003 "Submit" [clickable] salience:high
position:(540,320) — stacked above input_007,
no occlusion, aria-label matches visible text.
The difference feels unfair. In a good way.
━━━━━━━━━━━━━━━━━━━━━━
🧰 Use cases
→ LLM Agents — accurate UI state for autonomous action
→ AI Debugging — root cause in seconds, not hours
→ QA Automation — capture real runtime behavior
→ RPA — eliminate brittle selectors forever
→ Design review — spec vs implementation, instantly
→ Accessibility — what assistive tech actually perceives
━━━━━━━━━━━━━━━━━━━━━━
🔒 100% Local. 100% Private.
Nothing leaves your browser. Ever.
No cloud. No servers. No tracking.
DOM stays on your machine.
This is the rare AI tool that works
without touching your data.
━━━━━━━━━━━━━━━━━━━━━━
🚀 v2.8.0 — Persistent Captures
Save captures to disk as JSON files.
Diff workflows. Audit trails. Repeatable pipelines.
Toggle Clipboard / File mode — existing workflows unaffected.
━━━━━━━━━━━━━━━━━━━━━━
Works with Claude · ChatGPT · Gemini · Grok · Llama
Chrome · Firefox · Arc · Brave · Edge
Install. One click. Your AI finally sees.
Your AI agent is blind.
It guesses from screenshots. Drowns in raw HTML.
Misses what users actually see.
Element to LLM fixes this.
One click. Your browser's live UI state — structured,
semantic, token-efficient — delivered to any LLM.
Claude, GPT, Gemini, Llama. Your choice.
Now your AI agent doesn't guess. It sees.
━━━━━━━━━━━━━━━━━━━━━━
🤖 Built for AI Agents
The era of AI agents is here.
Agents that fill forms, navigate apps, debug interfaces,
automate workflows — they all need one thing:
accurate perception of the UI.
Element to LLM is that perception layer.
Not screenshots (no element IDs, burns tokens).
Not raw HTML (2.3MB of noise).
Not accessibility trees (miss visual context).
SiFR v2 — structured, semantic, actionable:
→ Every element labeled and scored by importance
→ Actions tagged: [clickable] [fillable] [hoverable]
→ Spatial relationships mapped
→ Smaller than raw HTML
→ Zero system prompt overhead — live DOM is the context
Your agent stops hallucinating UI elements.
It acts on what's actually there.
━━━━━━━━━━━━━━━━━━━━━━
⚡ What changes when AI sees your screen
Before E2LLM:
"There's a button somewhere on the left, I think it says Submit..."
After E2LLM:
AI receives: btn_003 "Submit" [clickable] salience:high
position:(540,320) — stacked above input_007,
no occlusion, aria-label matches visible text.
The difference feels unfair. In a good way.
━━━━━━━━━━━━━━━━━━━━━━
🧰 Use cases
→ LLM Agents — accurate UI state for autonomous action
→ AI Debugging — root cause in seconds, not hours
→ QA Automation — capture real runtime behavior
→ RPA — eliminate brittle selectors forever
→ Design review — spec vs implementation, instantly
→ Accessibility — what assistive tech actually perceives
━━━━━━━━━━━━━━━━━━━━━━
🔒 100% Local. 100% Private.
Nothing leaves your browser. Ever.
No cloud. No servers. No tracking.
DOM stays on your machine.
This is the rare AI tool that works
without touching your data.
━━━━━━━━━━━━━━━━━━━━━━
🚀 v2.8.0 — Persistent Captures
Save captures to disk as JSON files.
Diff workflows. Audit trails. Repeatable pipelines.
Toggle Clipboard / File mode — existing workflows unaffected.
━━━━━━━━━━━━━━━━━━━━━━
Works with Claude · ChatGPT · Gemini · Grok · Llama
Chrome · Firefox · Arc · Brave · Edge
Install. One click. Your AI finally sees.
Captures runtime DOM → JSON snapshots for debugging, QA, and UI/UX design.
5 შეფასება 3 მიმომხილველისგან
ნებართვები და მონაცემები
მოთხოვნილი ნებართვები:
- აღებულ ასლის საცავში მონაცემის ჩამატება
- ფაილების ჩამოტვირთვა, ჩამოტვირთვების ისტორიის ნახვა და შეცვლა
- თქვენს მონაცემებთან წვდომა ყველა საიტზე
დამატებითი ნებართვები:
- თქვენს მონაცემებთან წვდომა stats.insitu.im-ზე
აღსარიცხი მონაცემები:
- შემქმნელის თქმით ეს გაფართოება არ საჭიროებს მონაცემთა აღრიცხვას.
არააუცილებლად აღსარიცხი მონაცემები შემქმნელის თქმით:
- ტექნიკური და გამოყენების მონაცემები
დამატებითი მონაცემები
- დამატების ბმულები
- ვერსია
- 2.8.1
- ზომა
- 103,35 კბ
- ბოლო განახლება
- თვის წინ (12 მარ 2026)
- მსგავსი კატეგორიები
- ლიცენზია
- MIT-ლიცენზია
- პირადი მონაცემების დაცვის დებულება
- გაეცანით ამ დამატების პირადულობის დაცვის დებულებას
- ვერსიის ისტორია
- კრებულში დამატება