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yuriharrison1
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1337-lang

Encode typed inter-agent messages with COGON vectors and DAGs.

3|Updated Mar 26, 2026
Search Tags:#validation#dag#semantics#inter-agent#1337#cogon#rust-python
One-click install
npx skills add https://github.com/yuriharrison1/1337-lang --skill 1337-lang
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: 1337-lang
Source: https://github.com/yuriharrison1/1337-lang/tree/main/1337-lang
Command: npx skills add https://github.com/yuriharrison1/1337-lang --skill 1337-lang

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

1337 provides a compact, typed inter-agent communication language built around COGON vectors to enable deterministic AI-to-AI messaging with formal validation and cross-language interoperability.

Core Features & Use Cases

  • Self-describing messages (COGON, DAG) with canonical space and 32 axes
  • Deterministic operations: BLEND, DELTA, FOCUS, DIST, ANOMALY_SCORE
  • Cross-language bindings and C ABI for Rust/Python integrations, plus a Python fallback
  • Validation rules R1–R21 to ensure safe, predictable exchanges
  • Reference material and implementation guidance in references/

Quick Start

Initialize two agents and exchange a COGON_ZERO followed by a simple COGON to validate end-to-end envelope handling.

Frequently Asked Questions about 1337-lang

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enable deterministic inter-agent communication in a multi-agent AI system?▼

Deterministic inter-agent communication is enabled by encoding meaning in COGON vectors and DAGs, allowing AI agents to exchange typed, validated messages predictably. This enforces a 32-dimensional semantic space to ensure reliable interactions.

Can I bridge AI messaging protocols between Rust and Python?▼

Yes, you can bridge messaging between Rust and Python using a C ABI for high-performance integrations, alongside a Python fallback. This allows cross-language interoperability for deterministic inter-agent messaging.

What is the best way to validate AI-to-AI messaging interactions?▼

The best way to validate AI-to-AI messaging is by applying validation rules R1–R21 to enforce safe, predictable exchanges. These rules ensure that COGON-based interactions within the DAG structure meet formal protocol requirements.

How do I perform semantic operations like distance and anomaly scoring on agent messages?▼

You perform semantic operations using deterministic functions like BLEND, DELTA, FOCUS, DIST, and ANOMALY_SCORE. These operations process COGON vectors within the 32-dimensional semantic space to analyze message meaning.

Do I need front-matter driven envelopes for cross-language AI messaging?▼

Yes, front-matter driven envelopes are required to structure and validate interactions securely. They provide the necessary metadata framework to enforce the 32-dimensional semantic space during cross-language agent communication.

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