transform

Type: wrappers

Signature: transform(fn)

What It Is

transform(fn) parses markdown with document-level structure checks, explicit section targeting, and typed field extraction, so this page defines a strict transform contract instead of permissive text scraping. The schema combines operators such as document(), section(), fields(), and string() to map 1 h1 heading, 1 h2 section, and list content into top-level keys meta for this transform behavior. If parsing fails, the result carries issue codes like missing_section, giving the caller precise debugging context for transform paths.

When to Use

Use transform(fn) when you need typed markdown parsing with deterministic contracts for transform workflows and want parsing behavior that remains enforceable in review and CI. Avoid it for exploratory drafts that intentionally avoid strict validation in transform documents, because it introduces key-level strictness that improves typing but rejects ad-hoc variations. It pairs well with document(), section(), fields(), and string() to keep transform extraction boundaries explicit while preserving typed output for downstream code.

transform(fn)

Input Markdown

## 1. META

- Alias: ALEX

Schema

import { md } from '@markschema/mdshape'

const schema = md.document({
  meta: md.section('1. META').fields({
    Alias: md.string().transform((value) => value.toLowerCase()),
  }),
})

Result

Success

{
  "success": true,
  "data": {
    "meta": {
      "Alias": "alex"
    }
  }
}

Error

Failure trigger: The input violates one or more constraints declared in the schema; use issues[].path and issues[].code to locate the exact failing node.

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