PROJECT CONSTITUTION Architecture Freeze Candidate

Blueprint & Whitepaper

Open Workspace Intelligence Specification (OWIS)

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Overview

Open Workspace Intelligence Specification (OWIS) is an open interoperability standard that normalizes software workspace context, enabling consistent and deterministic project understanding for both humans and AI IDE Agents.

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Purpose

To build an open standard that enables a software workspace to be understood consistently by both humans and AI Agents. This standard does not aim to replace AI IDEs, LLMs, frameworks, or programming languages. Instead, it serves as an interoperability layer that normalizes the entire project context into a knowledge model usable across different vendors.

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Scope

Included:

• Workspace discovery.
• Knowledge normalization.
• Source of Truth hierarchy.
• Dependency intelligence.
• Architecture intelligence.
• Implementation boundary.
• Execution readiness.
• Confidence model.

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Non Goals

Excluded:

• Code generation.
• Deployment pipelines.
• Model inference.
• Agent runtime implementation.
• IDE applications.

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Architecture

OWIS acts as an abstraction layer between the codebase and the executing AI.

Software Workspace
        │
        ▼
Workspace Intelligence Layer (OWIS)
        │
        ▼
Any AI IDE Agent

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Components

Universal Agent Runtime Specification (UARS)

The operational contract governing AI behavior during project understanding and modification.

Workspace Intelligence Report (WIR)

The data structure representing the agent's validated workspace understanding.

Together, they form the Workspace Intelligence Layer.

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Interfaces

OWIS defines machine-readable schemas (JSON/YAML Schema) as the main interface between the repository context and AI agents. Runtimes consume documents matching these interfaces.

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Constraints

OWIS locks the project direction on the following principles:

• Open Specification First.
• Vendor Agnostic.
• Workspace-Centric.
• Documentation-Driven.
• Intelligence Before Execution.
• Tooling Follows Adoption.
• Zero-Cost Friendly.
• Community Before Commercialization.
• Standards Before Products.

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Future Extensions

Future phases will introduce formal JSON/YAML schemas, SDKs, validating CLIs, and certification suites to verify AI agent compliance with UARS.