@markschema/mdshape

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value ​

Type: match

Signature: match.label(name).value(schema)

What It Is ​

match.label(name).value(schema) parses markdown with document-level structure checks, so this page defines a strict value contract instead of permissive text scraping. The schema combines operators such as document() and heading() to map 1 h1 heading into top-level keys title for this value behavior. If parsing fails, the result carries issue codes like missing_heading, giving the caller precise debugging context for value paths.

When to Use ​

Use match.label(name).value(schema) when you need label-oriented parsing from inline markers in prose for value workflows and want parsing behavior that remains enforceable in review and CI. Avoid it for documents that lack stable labels or marker prefixes in value documents, because it introduces more explicit schema maintenance to keep output deterministic. It pairs well with document() and heading() to keep value extraction boundaries explicit while preserving typed output for downstream code.

match.label(name).value(schema) ​

Input Markdown ​

md
## 3. EVENTS

### Detection

**STATUS:** ACTIVE

Schema ​

ts
import { md } from '@markschema/mdshape'

const schema = md.document({
  events: md
    .section('3. EVENTS')
    .subsections(3)
    .each(
      md.object({
        title: md.headingText(),
        status: md.match.label('STATUS').value(md.enum(['ACTIVE', 'PAUSED'])),
      }),
    ),
})

Result ​

Success ​

json
{
  "success": true,
  "data": {
    "events": [
      {
        "title": "Detection",
        "status": "ACTIVE"
      }
    ]
  }
}

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.

json
{
  "success": false,
  "error": {
    "issues": [
      {
        "code": "missing_section",
        "message": "Missing section \"3. EVENTS\"",
        "path": [
          "events"
        ],
        "line": 1,
        "position": {
          "start": {
            "line": 1,
            "column": 1
          }
        }
      }
    ]
  }
}