Where should I store global Typedown configurations?

Global configurations and exported symbols must be placed strictly in a config.td file, where they are automatically inherited by the directory scope.

How do I check if my Typedown code is valid?

You can verify your files by running the command 'uvx typedown check ' to trigger the compiler and catch syntax or validation errors.

Typedown is a Consensus Modeling Language that embeds Pydantic models and validation logic into Markdown files, allowing you to treat documentation as structured, verifiable data.

How do I reference other entities in Typedown?

Use the Wiki Link syntax [[Identifier]]. Typedown resolves these using a three-layer strategy: L0 (hashes), L1 (exact System IDs), and L2 (contextual handles).

Can I define multiple Pydantic models in one code block?

No, Typedown follows a 'One Model Per Block' rule. Each class must be defined in its own model:ClassName block to ensure structural clarity.

Typedown Expert

Name: Typedown Expert
Author: IndenScale

byIndenScale

•

Database Management

Transforms unstructured Markdown documentation into rigorous, machine-verifiable data schemas using Pydantic models and YAML entities.

About

Typedown Expert empowers Claude to guide users through the process of 'Consensus Modeling,' a method for bridging the gap between natural language text and strict systemic data. By embedding Pydantic models, YAML entities, and Pytest-style validation logic directly into Markdown files, this skill enables the progressive formalization of requirements and architectures. It provides expert assistance in maintaining syntax correctness, managing complex cross-entity references using a three-layer matching strategy, and enforcing architectural constraints, making it an essential tool for teams who treat documentation as a single source of truth for structured data.

Key Features

Validates Pydantic-based model blocks and YAML-based entity declarations within Markdown.
5 GitHub stars
Implements a robust three-layer referencing system (L0-L2) for stable entity linking.
Supports cross-entity validation through specialized spec blocks and Python-based constraint engineering.
Enforces a 5-step Consensus Modeling workflow for reliable data discovery and abstraction.
Provides expert guidance on evolution semantics using the former keyword for version tracking.

Use Cases

Documenting evolving system architectures with traceable historical changes and identity stability.
Converting loose business requirements into structured, verifiable API or database schemas.
Managing complex configuration files with strict validation and internal cross-references.

About

Key Features

Validates Pydantic-based model blocks and YAML-based entity declarations within Markdown.
5 GitHub stars
Implements a robust three-layer referencing system (L0-L2) for stable entity linking.
Supports cross-entity validation through specialized spec blocks and Python-based constraint engineering.
Enforces a 5-step Consensus Modeling workflow for reliable data discovery and abstraction.
Provides expert guidance on evolution semantics using the former keyword for version tracking.

Use Cases

Documenting evolving system architectures with traceable historical changes and identity stability.
Converting loose business requirements into structured, verifiable API or database schemas.
Managing complex configuration files with strict validation and internal cross-references.