Syntax

DataSheetLang specs are written in YAML. A spec file contains:

• A required spec header
• Optional presets
• One or more entity sections (items, equipment, itemStrings)

If you want “what fields exist”, see Entities.

Spec structure

Minimal spec:

spec:
  version: "1.0"

Typical spec:

spec:
  version: "1.0"

presets:
  items: { }
  equipment: { }
  itemStrings: { }

items:
  create: [ ]
  update: [ ]
  delete: [ ]

Required

• spec.version — currently "1.0"

Optional

• presets
• items, equipment, itemStrings

Operations

Create

items:
  create:
    - id: 99001
      name: "training_sword"
      level: 1

Update

items:
  update:
    - id: 99001
      preset: some_preset   # optional
      changes:
        level: 10
        buyPrice: 250

Delete

items:
  delete:
    - 99001
    - 99002

Preset references (overview)

Presets are defined under presets.<entity> and referenced with preset:.

• Presets can extends: another preset (single inheritance)
• Presets merge via null-coalescing (child ?? parent)
• Lists replace by default

Full details: Presets

Inline equipment block

Items can include an equipment: block which expands into related equipment changes.

Common pattern:

items:
  create:
    - id: 99001
      name: "iron_sword"
      level: 60

      equipment:
        computed: true
        compute:
          formula: "standard"

Full details: Equipment computation

Inline strings block

Items can include a strings: block to define display name / tooltip.

items:
  create:
    - id: 99001
      name: "iron_sword"

      strings:
        name: "Iron Sword"
        toolTip: "A basic training weapon."

Data types and YAML style

• YAML supports inline lists ([a, b]) and multi-line lists
• Strings can be quoted or unquoted (quotes recommended for safety)
• Numbers should be written as numbers (no quotes) unless explicitly required

Validation

Specs are validated before applying:

• required fields present
• supported entity sections and operations
• preset resolution succeeds (no cycles, depth limits)
• values fit expected types / ranges

When validation fails, you’ll get an error code.