Privacy-First Framework

Multi-Agent Context Control

Control what each agent sees in your AI workflow. Define context boundaries, maintain privacy, and build cleaner agent pipelines.

npx ps-lang@alpha init
Context Control
// Agent A sees this
<@. Research findings for Agent B .@>
Query results, processed data, clean outputs

// Agent A doesn't see this
<. Internal notes, debug logs, raw data .>
API keys, reasoning chains, test outputs

// Agent B receives only what it needs
<#. Analysis ready for Agent C .#>
Structured insights, recommendations

// Privacy by default
Each agent sees only its context zone

Why PS-Lang

Precise Control

Define exactly what context each agent receives. No leakage, no contamination.

Agent Privacy

Isolate sensitive data, internal reasoning, and debug information from downstream agents.

Cleaner Pipelines

Build multi-agent workflows with clear boundaries. Research → Analysis → Output.

Use Cases

Multi-Agent Platforms

Control agent-to-agent visibility in automation systems. Grant context permissions explicitly.

Agent Pipelines

Build clean handoffs between specialized agents. Research agents pass findings to analysis agents without debug noise.

Benchmark Testing

Test agent performance without context contamination. Each test run starts clean.

Privacy-First Workflows

Keep sensitive context isolated. API keys, credentials, and internal notes stay hidden from production agents.

Open Source

Build smarter agent workflows.
Control every handoff.