"Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters. Use when finding notes by status, priority, confidence, or any custom YAML field rather than free-text content."
Install
npx skillscat add basicmachines-co/basic-memory-skills/memory-metadata-search Install via the SkillsCat registry.
Memory Metadata Search
Find notes by their structured frontmatter fields instead of (or in addition to) free-text content. Any custom YAML key in a note's frontmatter beyond the standard set (title, type, tags, permalink, schema) is automatically indexed as entity_metadata and becomes queryable.
When to Use
- Filtering by status or priority — find all notes with
status: draftorpriority: high - Querying custom fields — any frontmatter key you invent is searchable
- Range queries — find notes with
confidence > 0.7orscore between 0.3 and 0.8 - Combining text + metadata — narrow a text search with structured constraints
- Tag-based filtering — find notes tagged with specific frontmatter tags
- Schema-aware queries — filter by nested schema fields using dot notation
Two Tools, Two Patterns
| Tool | Use When |
|---|---|
search_by_metadata |
Metadata filters only, no text query needed |
search_notes |
Combining a text query with metadata filters |
Both accept the same filter syntax.
Filter Syntax
Filters are a JSON dictionary. Each key targets a frontmatter field; the value specifies the match condition. Multiple keys combine with AND logic.
Equality
{"status": "active"}Array Contains (all listed values must be present)
{"tags": ["security", "oauth"]}$in (match any value in list)
{"priority": {"$in": ["high", "critical"]}}Comparisons ($gt, $gte, $lt, $lte)
{"confidence": {"$gt": 0.7}}Numeric values use numeric comparison; strings use lexicographic comparison.
$between (inclusive range)
{"score": {"$between": [0.3, 0.8]}}Nested Access (dot notation)
{"schema.version": "2"}Quick Reference
| Operator | Syntax | Example |
|---|---|---|
| Equality | {"field": "value"} |
{"status": "active"} |
| Array contains | {"field": ["a", "b"]} |
{"tags": ["security", "oauth"]} |
$in |
{"field": {"$in": [...]}} |
{"priority": {"$in": ["high", "critical"]}} |
$gt / $gte |
{"field": {"$gt": N}} |
{"confidence": {"$gt": 0.7}} |
$lt / $lte |
{"field": {"$lt": N}} |
{"score": {"$lt": 0.5}} |
$between |
{"field": {"$between": [lo, hi]}} |
{"score": {"$between": [0.3, 0.8]}} |
| Nested | {"a.b": "value"} |
{"schema.version": "2"} |
Rules:
- Keys must match
[A-Za-z0-9_-]+(dots separate nesting levels) - Operator dicts must contain exactly one operator
$inand array-contains require non-empty lists$betweenrequires exactly[min, max]
Using search_by_metadata
Metadata-only search. Results are scoped to entity-level items.
# All notes with status "in-progress"
search_by_metadata(filters={"status": "in-progress"})
# High-priority specs in a specific project
search_by_metadata(
filters={"type": "spec", "priority": {"$in": ["high", "critical"]}},
project="research",
limit=10,
)
# Notes with confidence above a threshold
search_by_metadata(filters={"confidence": {"$gt": 0.7}})
# Paginate through results
search_by_metadata(filters={"type": "meeting"}, limit=10, offset=20)Using search_notes with Metadata
Combine text search with structured filters by passing metadata_filters, tags, or status alongside the text query.
# Text search narrowed by metadata
search_notes("authentication", metadata_filters={"status": "draft"})
# Filter-only (empty query string)
search_notes("", metadata_filters={"type": "spec"})
# Convenience shortcuts for tags and status
search_notes("planning", status="active")
search_notes("", tags=["security", "oauth"])
# Mix text, tag shortcut, and advanced filter
search_notes(
"oauth flow",
tags=["security"],
metadata_filters={"confidence": {"$gt": 0.7}},
)Merging rules: tags and status are convenience shortcuts merged into metadata_filters via setdefault. If the same key exists in metadata_filters, the explicit filter wins.
Tag Search Shorthand
The tag: prefix in a query converts to a tag filter automatically:
# These are equivalent:
search_notes("tag:tier1")
search_notes("", tags=["tier1"])
# Multiple tags (comma or space separated) — all must match:
search_notes("tag:tier1,alpha")Example: Custom Frontmatter in Practice
A note with custom fields:
---
title: Auth Design
type: spec
tags: [security, oauth]
status: in-progress
priority: high
confidence: 0.85
---
# Auth Design
## Observations
- [decision] Use OAuth 2.1 with PKCE for all client types #security
- [requirement] Token refresh must be transparent to the user
## Relations
- implements [[Security Requirements]]Queries that find it:
# By status and type
search_by_metadata(filters={"status": "in-progress", "type": "spec"})
# By numeric threshold
search_by_metadata(filters={"confidence": {"$gt": 0.7}})
# By priority set
search_by_metadata(filters={"priority": {"$in": ["high", "critical"]}})
# By tag shorthand
search_notes("tag:security")
# Combined text + metadata
search_notes("OAuth", metadata_filters={"status": "in-progress"})Guidelines
- Use metadata search for structured queries. If you're looking for notes by a known field value (status, priority, type), metadata filters are more precise than text search.
- Use text search for content queries. If you're looking for notes about something, text search is better. Combine both when you need precision.
- Custom fields are free. Any YAML key you put in frontmatter becomes queryable — no schema or configuration required.
- Multiple filters are AND.
{"status": "active", "priority": "high"}requires both conditions. - Prefer
search_by_metadatafor filter-only queries. It's purpose-built and returns entity-level results. Usesearch_noteswith empty query only when you also need text search features. - Dot notation for nesting. Access nested YAML structures with dots:
{"schema.version": "2"}queries theversionkey inside aschemaobject. - Tags shortcut is convenient but limited.
tagsandstatusare sugar for common fields. For anything else, usemetadata_filtersdirectly.