SOP-Lang Pipeline Current Specifications

SOP-Lang Pipeline is a Domain-Specific Language (DSL) designed to be the glue of the ACHILLES IDE, orchestrating complex agent behaviours and build processes. Its parser and runtime are developed as a back-end concern, while complementary UI tools such as variable-state visualisation are developed in UI layers.

At a high level, SOP-Lang Pipeline is useful when you need to coordinate agent workflows declaratively instead of wiring imperative scripts by hand. It targets AI-agent build systems, reusable behaviour definitions, and structured document-driven automation where commands, data, and generated artefacts evolve together.

The language is built for long-running, inspectable automation flows: each document can hold specifications, commands, and generated artefacts in one place, so teams can evolve behaviour incrementally without losing traceability.

Within ACHILLES context, SOP-Lang Pipeline supports DSL-based agent behaviour design and build orchestration, the structured document concept, and variable-state visibility in the workspace UI.

Quick Start: First Script

Minimal example for composing values through variables. Detailed execution semantics are covered in Language Foundations.

@name := "World"
@greeting := "Hello, " $name

# Basic variable composition

Ready to dive in? Start with the Language Foundations.

Documentation Map

Language Essentials

Learn the Foundations, how to Assign variables, and how to use Math and Logic.

Built-in Toolbox

Explore the Full Command Catalog, including Prompting, Object Instantiation, and Optimization.

Data & Objects

Work with structured data using Tables, Sets, Documents, and Folders.

AI & Orchestration

Build complex assistants using Chat, Forms, and Workflows.

Design Philosophy

SOP-Lang Pipeline prioritizes Prompt Engineering and document-centered orchestration, so natural language intent and executable commands can coexist in the same workflow.

It is designed to interoperate with containerized agents and reactive UI layers, providing a stable execution model for non-deterministic AI tasks.