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Agent skill

Memory Metadata Search

by basicmachines-co in basicmachines-co/basic-memory

Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters.

AGPL-3.0Auto-check passed

Install Memory Metadata Search

skills CLI
$ npx skills add basicmachines-co/basic-memory --skill memory-metadata-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install basicmachines-co/basic-memory memory-metadata-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/basicmachines-co/basic-memory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/memory-metadata-search .claude/skills/memory-metadata-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
memory-metadata-search
GitHub stars
4.1k
Used in
1 other repo
Token cost
~1.8k tokens
SKILL.md length
653 words
Files
1
Skills in repo
49
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters.

  • Finding notes by status
  • SKILL.md covers When to Use, The Tool, Filter Syntax and Using search_notes with Metadata, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Any custom YAML field rather than free-text content

What it does

Memory Metadata Search is an agent skill from basicmachines-co/basic-memory. 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.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: AI conversations that actually remember. Never re-explain your project to your AI again. Join our Discord: https://discord.gg/tyvKNccgqN. The licence is AGPL-3.0.

When your agent uses it

  • Finding notes by status
  • Any custom YAML field rather than free-text content

Example prompts

  • “/memory-metadata-search”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit cb7407f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json, python and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Memory Metadata Search loads about 1.8k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 653 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from basicmachines-co/basic-memory at commit cb7407f, republished under its AGPL-3.0 licence (© basicmachines-co). 653 words, ~1,841 tokens.

Download SKILL.mdSave it as .claude/skills/memory-metadata-search/SKILL.md (or your agent's skills folder).
name
memory-metadata-search
description
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.

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: draft or priority: high
  • Querying custom fields — any frontmatter key you invent is searchable
  • Range queries — find notes with confidence > 0.7 or score 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

The Tool

All metadata searching uses search_notes. Pass filters via metadata_filters, or use the tags and status convenience shortcuts. Omit query (or pass None) for filter-only searches.

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
json
{"status": "active"}
Array Contains (all listed values must be present)
json
{"tags": ["security", "oauth"]}
$in (match any value in list)
json
{"priority": {"$in": ["high", "critical"]}}
Comparisons ($gt, $gte, $lt, $lte)
json
{"confidence": {"$gt": 0.7}}

Numeric values use numeric comparison; strings use lexicographic comparison.

$between (inclusive range)
json
{"score": {"$between": [0.3, 0.8]}}
Null (field missing or explicitly null)
json
{"owner": null}

Matches notes with no owner key and notes whose owner is explicitly null. Null works only as a plain equality value — inside $in, $between, an array-contains list, or a comparison it is rejected, because those compare against the value and a comparison with null is never true.

Nested Access (dot notation)
json
{"schema.version": "2"}
Quick Reference
OperatorSyntaxExample
Equality{"field": "value"}{"status": "active"}
Is null{"field": null}{"owner": null}
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
  • $in and array-contains require non-empty lists
  • $between requires exactly [min, max]
  • null is an is-null match and only valid as a plain equality value
  • Comparison and $between bounds must be finite numbers — a magnitude no float can hold (a 400-digit integer, which JSON keeps as an ordinary int) is refused rather than compared against an infinite bound
  • Metadata filters match Markdown notes only — indexed PDFs, images and other regular files carry no frontmatter and are never hits, not even for null

Warning: Operators MUST include the $ prefix — write $gte, not gte. Without the prefix the filter is treated as an exact-match key and will silently return no results. Correct: {"confidence": {"$gte": 0.7}}. Wrong: {"confidence": {"gte": 0.7}}.

Show full SKILL.md (207 more words)Show less

Using search_notes with Metadata

Pass metadata_filters, tags, or status to search_notes. Omit query for filter-only searches, or combine text and filters together.

python
# Filter-only — find all notes with a given status
search_notes(metadata_filters={"status": "in-progress"})

# Filter-only — high-priority specs in a specific project
search_notes(
    metadata_filters={"type": "spec", "priority": {"$in": ["high", "critical"]}},
    project="research",
    page_size=10,
)

# Filter-only — notes with confidence above a threshold
search_notes(metadata_filters={"confidence": {"$gt": 0.7}})

# Convenience shortcuts for tags and status
search_notes(status="active")
search_notes(tags=["security", "oauth"])

# Text search narrowed by metadata
search_notes("authentication", metadata_filters={"status": "draft"})

# 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:

python
# 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:

markdown
---
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:

python
# By status and type
search_notes(metadata_filters={"status": "in-progress", "type": "spec"})

# By numeric threshold
search_notes(metadata_filters={"confidence": {"$gt": 0.7}})

# By priority set
search_notes(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.
  • Omit query for filter-only searches. search_notes(metadata_filters={"status": "active"}) works without a text query.
  • Dot notation for nesting. Access nested YAML structures with dots: {"schema.version": "2"} queries the version key inside a schema object.
  • Tags shortcut is convenient but limited. tags and status are sugar for common fields. For anything else, use metadata_filters directly.

© basicmachines-co, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/memory-metadata-search of basicmachines-co/basic-memory.

Open the folder on GitHubat commit cb7407f

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in basicmachines-co/basic-memory, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Memory Metadata Search next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Memory Metadata Search compared with similar skills
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Bigquery Basicsdavila7/claude-code-templates32k—~1.1kAutomated safety check: PassMIT
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Questions about Memory Metadata Search

What does Memory Metadata Search do?

Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters. Memory Metadata Search is an agent skill from basicmachines-co/basic-memory. Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters.

When should I use Memory Metadata Search?

Memory Metadata Search fits situations like: finding notes by status; any custom YAML field rather than free-text content.

How do I install Memory Metadata Search in Claude Code?

Run `npx skills add basicmachines-co/basic-memory --skill memory-metadata-search -a claude-code`. Or copy the skill folder (skills/memory-metadata-search in basicmachines-co/basic-memory) into .claude/skills/memory-metadata-search in your project. Claude Code loads it when a task matches its description.

How do I install Memory Metadata Search in Codex?

Run `npx skills add basicmachines-co/basic-memory --skill memory-metadata-search -a codex`. Or copy the skill folder (skills/memory-metadata-search in basicmachines-co/basic-memory) into .agents/skills/memory-metadata-search in your project. Codex loads it when a task matches its description.

Can I use Memory Metadata Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add basicmachines-co/basic-memory --skill memory-metadata-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory-metadata-search, .gemini/skills/memory-metadata-search, .github/skills/memory-metadata-search and .opencode/skills/memory-metadata-search in your project.

What does Memory Metadata Search need to run?

SKILL.md names no scripts, command-line tools or credentials: Memory Metadata Search is instructions for the agent only. Our summary lists: Python 3.

Does Memory Metadata Search access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Memory Metadata Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Memory Metadata Search use?

Memory Metadata Search is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Memory Metadata Search use?

About 1.8k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Memory Metadata Search?

Skills that share tags, products or a category with Memory Metadata Search: Basic (bergside/awesome-design-skills, 3.1k stars), Makepad Basics (sickn33/agentic-awesome-skills, 47k stars), Bigquery Basics (davila7/claude-code-templates, 32k stars) and Gke Basics (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Memory Metadata Search?

basicmachines-co (a GitHub organization) maintains it in basicmachines-co/basic-memory, which has 4,115 GitHub stars. The repository holds 49 skills in this directory. The repository was last updated on October 7, 2026.

Source: basicmachines-co/basic-memory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.