status Tool

Overview

The status tool reports the current state of the QMD index:

Total document count
Embedding status (for vector search)
Collection details
Health indicators

Input Schema

No parameters required. Call with an empty object:

{}

Response Format

content

array

Array with a single text element containing a human-readable summary

Show content[0]

type

string

Always "text"

text

string

Summary like:

QMD Index Status:
  Total documents: 1234
  Needs embedding: 0
  Vector index: yes
  Collections: 3
    - /home/user/notes (450 docs)
    - /home/user/docs (300 docs)
    - /home/user/journals (484 docs)

structuredContent

object

Machine-readable status details

Show StatusResult object

totalDocuments

number

Total number of indexed documents across all collections

needsEmbedding

number

Number of documents without embeddings. Run qmd embed if > 0.

hasVectorIndex

boolean

Whether vector search is available. false means qmd embed has never been run.

collections

array

Array of collection objects

Show Collection object

name

string

Collection name (from qmd collection add --name)

path

string

Absolute filesystem path to collection root

pattern

string

Glob pattern for indexed files (e.g., **/*.md)

documents

number

Number of documents in this collection

lastUpdated

string

ISO 8601 timestamp of last index update

Example

Request:

{}

Response:

{
  "content": [
    {
      "type": "text",
      "text": "QMD Index Status:\n  Total documents: 1234\n  Needs embedding: 0\n  Vector index: yes\n  Collections: 3\n    - /home/user/notes (450 docs)\n    - /home/user/docs (300 docs)\n    - /home/user/journals (484 docs)"
    }
  ],
  "structuredContent": {
    "totalDocuments": 1234,
    "needsEmbedding": 0,
    "hasVectorIndex": true,
    "collections": [
      {
        "name": "notes",
        "path": "/home/user/notes",
        "pattern": "**/*.md",
        "documents": 450,
        "lastUpdated": "2025-05-15T14:23:10.000Z"
      },
      {
        "name": "docs",
        "path": "/home/user/docs",
        "pattern": "**/*.md",
        "documents": 300,
        "lastUpdated": "2025-05-15T14:23:10.000Z"
      },
      {
        "name": "journals",
        "path": "/home/user/journals",
        "pattern": "**/*.md",
        "documents": 484,
        "lastUpdated": "2025-05-15T14:23:10.000Z"
      }
    ]
  }
}

Use Cases

Check if Embeddings are Available

Before using vec or hyde search:

{}

Check hasVectorIndex in the response. If false, vector search will fail. Run:

qmd embed

Verify Index is Up-to-Date

Check needsEmbedding count. If > 0, run:

qmd embed

to generate embeddings for new documents.

List All Collections

Use structuredContent.collections to see all indexed collections and their document counts.

Debugging Search Issues

If search returns no results:

Check totalDocuments — is the index populated?
Check collections — is the expected collection present?
Check hasVectorIndex — are you using vec/hyde without embeddings?

CLI Equivalent

qmd status

Outputs the same information in a formatted table.

query Tool

Search the index after verifying status

Embeddings

Learn how to generate embeddings

Collections

Manage collections via CLI

Tools

Integration

Overview

Input Schema

Response Format

Example

Use Cases

Check if Embeddings are Available

Verify Index is Up-to-Date

List All Collections

Debugging Search Issues

CLI Equivalent

query Tool

Embeddings

Collections

Build docs developers (and LLMs) love

Tools

Integration

​Overview

​Input Schema

​Response Format

​Example

​Use Cases

​Check if Embeddings are Available

​Verify Index is Up-to-Date

​List All Collections

​Debugging Search Issues

​CLI Equivalent

​Related Tools

query Tool

Embeddings

Collections

Build docs developers (and LLMs) love

Overview

Input Schema

Response Format

Example

Use Cases

Check if Embeddings are Available

Verify Index is Up-to-Date

List All Collections

Debugging Search Issues

CLI Equivalent

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