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Agent Skill · 研究检索

memory-metadata-search(内存元数据搜索)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

memory-metadata-search 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 19,213。

总安装 5,712周安装 238GitHub Stars 18下载 1,904核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:memory-metadata-search(内存元数据搜索)
来源仓库:https://github.com/basicmachines-co/basic-memory-skills
仓库路径:skills/memory-metadata-search
安装命令:
npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-metadata-search
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-metadata-search

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

memory-metadata-search 用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。

使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。该技能适用于研究检索类别,主要用于数据处理和分析支持。使用时需特别注意数据隐私和权限控制要求。

来源仓库内路径:skills/memory-metadata-search

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill m…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

memory-metadata-search 怎么安装?

在终端执行 npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-meta…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

memory-metadata-search 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

memory-metadata-search 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

memory-metadata-search 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

memory-metadata-search 用的人多吗?

公开数据是累计安装 5,712 次,近一周安装 238 次,下载 1,904 次,GitHub 18 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

memory-metadata-search 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
memory-metadata-search

内存元数据搜索 · 本页

5,71218接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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: 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

{"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

OperatorSyntaxExample
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
  • $in and array-contains require non-empty lists
  • $between requires exactly [min, max]
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}}.

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.

# 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:

# 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_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.

平台分布

Codex

37.1%
按下载量换算706

Claude

29.01%
按下载量换算552

Cursor

21.42%
按下载量换算408

Gemini CLI

9.58%
按下载量换算182

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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