startswith

What It Is

On this page, startswith centers on document-level structure checks, explicit section targeting, and typed field extraction to keep startswith parsing deterministic and schema-driven. The example expects a compact markdown payload and returns top-level keys owner directly from the declared startswith extraction rules. Violations produce issue codes like missing_section, which avoids brittle string checks and keeps startswith failure handling explicit.

When to Use

Apply startswith when your document flow requires tightening scalar constraints without redefining the base shape for startswith and strict schema adherence over permissive parsing. It is less suitable for very loose drafts where strict refinement would block iteration under startswith, because teams must accept key-level strictness that improves typing but rejects ad-hoc variations. Use document(), section(), fields(), and string() around startswith to keep startswith contracts transparent and reduce ambiguity in validation behavior.

Input Markdown

## 1. OWNER

- Role: Lead Engineer

Schema

import { md } from '@markschema/mdshape'

const schema = md.document({
  owner: md.section('1. OWNER').fields({
    Role: md.string().startsWith('Lead'),
  }),
})

Result

Success

{
  "success": true,
  "data": {
    "owner": {
      "Role": "Lead Engineer"
    }
  }
}

Error

{
  "success": false,
  "error": {
    "issues": [
      {
        "code": "missing_section",
        "message": "Missing section \"1. OWNER\"",
        "path": [
          "owner"
        ],
        "line": 1,
        "position": {
          "start": {
            "line": 1,
            "column": 1
          }
        }
      }
    ]
  }
}