STL Documentation

Welcome to the documentation for Semantic Tension Language (STL) and its Python toolkit stl-parser.

STL is a calculable, universal standard for structuring knowledge through directional semantic relations. It introduces a tension-path model where knowledge flows directionally from source to target, carrying semantic magnitude and type information.

[Theory_Relativity] -> [Prediction_TimeDilation] ::mod(
  rule="logical",
  confidence=0.99,
  source="doi:10.1002/andp.19053221004",
  author="Einstein"
)

Unlike JSON or plain text, STL statements are traceable, verifiable, and inference-ready.

Where to Start

New to STL?

1. Installation — Install stl-parser in under a minute
2. Quickstart — Parse, build, and validate your first STL statements
3. Key Concepts — Understand anchors, paths, modifiers, and the tension-path model

Learning STL

Step-by-step tutorials covering every capability:

Looking Something Up?

• API Reference — Complete function and class documentation
• CLI Reference — All 10 CLI commands with examples
• Modifier Reference — All 30+ modifier fields
• Error Codes — E001-E969, W001-W099 with fixes
• STL Syntax Card — One-page syntax quick reference

Solving a Specific Problem?

• Custom Schemas — Create domain-specific validation schemas
• LLM Integration — Use STL with ChatGPT, Claude, and other LLMs
• Knowledge Graph Pipeline — Build end-to-end knowledge graphs
• Event Logging — Use STL for structured event logging
• Confidence Decay — Manage knowledge freshness over time

Specifications

• STL Core Specification v1.0 — The formal language specification
• STL Core Specification Supplement — Extended features and semantics

Project

• Project Index — Module reference and architecture overview
• Schema Ecosystem — 6 domain-specific schemas + template
• GitHub Repository