agentatlas 0.2.0

Shared browser interaction schema registry for AI agents. Reduces LLM token usage by 80-100% on known sites.

AgentAtlas

Shared browser interaction schema registry for AI agents.

Reduces LLM token usage by 80-100% on known sites by storing and sharing site interaction schemas across all users.

How it works

First user  → LLM learns the site → saved to shared registry
Every user after → 0 tokens, instant response

Benchmark results (real data)

	Without AgentAtlas	With AgentAtlas
Tokens	2,597	0-445
Cost	$0.018	$0.000-$0.002
Time	19s	0.2-12s
Real URLs	❌	✅

82.9% token reduction when LLM still needed. 100% reduction for repeat workflows.

Install

pip install agentatlas
playwright install chromium

Usage

from agentatlas.atlas import Atlas

atlas = Atlas()

# Get schema for any site
# Found in registry → 0 tokens
# New site → learns once, saves for everyone
schema = await atlas.get_schema(
    site="greenhouse.io",
    url="https://boards.greenhouse.io/anthropic"
)

# Pass compact schema to YOUR LLM
# 150-500 tokens instead of 50,000
print(schema.elements)
print(schema.tokens_used)  # 0 if registry hit
print(schema.source)       # "registry" or "llm_learned"

Environment variables

SUPABASE_URL=your_supabase_url
SUPABASE_SERVICE_ROLE_KEY=your_key
OPENAI_API_KEY=your_key

The flywheel

More developers use AgentAtlas
        ↓
More new sites get learned automatically
        ↓
Registry grows → higher hit rate
        ↓
Less tokens burned across the whole network
        ↓
Cheaper + faster → more developers adopt

License

MIT