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memosmemos 搜索

Agent Skill

memos 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

212

周安装

9

GitHub Stars

2

下载量

74
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:memos(memos 搜索)
来源仓库:https://github.com/jtsang4/efficient-coding
仓库路径:skills/memos
安装命令:
npx skills add https://github.com/jtsang4/efficient-coding --skill memos
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/jtsang4/efficient-coding --skill memos

简介

memos 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。
  • 可结合来源仓库和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网或命令执行。
  • 使用时需注意其功能边界,避免过度依赖自动化结果。

SKILL.md

Memos API Skill

This skill combines two layers:

  • low-level API access for exact Memos endpoints
  • task-oriented query helpers for common memo retrieval jobs
  • tag inventory helpers so the calling agent can inspect existing hashtags before deciding whether to reuse them

Scope is intentionally limited to:

  • attachment operations
  • memo operations
  • activity operations

It does not cover user management, auth setup beyond the local .env, shortcuts, identity providers, or instance settings. If the request drifts there, say the skill scope is limited instead of guessing unsupported commands.

What this skill provides

  • A Bun CLI at scripts/memos.ts
  • Endpoint discovery and direct API calling via ops, describe, and call
  • Task-oriented memo helpers via latest, recent, and search
  • A list-tags helper that aggregates existing tags, counts, recency, and sample memo snippets
  • A file-to-attachment helper so agents do not have to hand-roll base64 payloads
  • A compact operation catalog at references/api-summary.md
  • Query recipes and time-window guidance at references/query-recipes.md

Setup

  1. Work from the skill directory.
  2. Ensure .env contains:

- MEMOS_BASE_URL - MEMOS_ACCESS_TOKEN

  1. Verify config:
bun run scripts/memos.ts config

MEMOS_BASE_URL may be either the instance root such as http://localhost:5230 or the API base such as http://localhost:5230/api/v1. The CLI normalizes both.

Choose the right path

Use the high-level commands first when the user asked for a retrieval task, not a specific endpoint.

  • Latest memo or latest N memos:
bun run scripts/memos.ts latest --count 5
  • Recent memos inside a time window:
bun run scripts/memos.ts recent --days 7 --window rolling --include-content
  • Search by text or tag:
bun run scripts/memos.ts search --text agent --tag Thought --days 30
  • Inspect existing tags before deciding which hashtags to reuse in a new memo:
bun run scripts/memos.ts list-tags --limit 100 --sample-size 2

Use call when the user explicitly needs one documented endpoint or a write operation.

  • Inspect the exact endpoint first:
bun run scripts/memos.ts describe MemoService_UpdateMemo
  • Then call it directly:
bun run scripts/memos.ts call MemoService_UpdateMemo \
  --path memo=YOUR_MEMO_ID \
  --query updateMask=content,visibility \
  --body '{"content":"Updated content","visibility":"PROTECTED"}'

Known quirks

  • call --paginate returns {operationId, pageCount, pages: [...]}, not a top-level {memos: [...]}. Flatten pages[*].memos before post-processing.
  • Memo time checks should use displayTime first, then fall back to createTime.
  • For time-range queries, prefer orderBy='display_time desc' plus local filtering. Do not assume the server-side filter field supports stable time semantics across versions.
  • The task-oriented commands default state=NORMAL so archived or deleted content does not silently leak into user-facing summaries.
  • search --tag matches the memo tags array exactly. It is not a full-text hashtag parser over content.
  • Memo.tags is extracted by the server from hashtags in content. Treat it as output-only unless the deployed API docs explicitly say otherwise.

Recommended workflow

1. Retrieval tasks

When the user asks questions like:

  • 最近一周有哪些备忘录
  • 最新的一条 memo 是什么
  • Thought tag 的 memo 有哪些
  • 搜一下包含某个关键词的 memo

Use:

  1. latest, recent, or search
  2. Return the important fields from the JSON result
  3. Summarize content for the user when they asked for meaning, not raw JSON

Read references/query-recipes.md when you need concrete examples or want to choose between rolling and calendar time windows.

2. Tag-aware memo creation

When the user asks to create a memo with tags or hashtags:

  1. Run bun run scripts/memos.ts list-tags... first to inspect the existing tag vocabulary.
  2. If one or more candidate tags might match, run search --tag... on the likely choices to inspect prior memo context.
  3. Let the calling agent decide which existing tags to reuse. Do not hard-code similarity logic in scripts for this decision.
  4. Put the final tags directly into the memo content as hashtags, usually at the top, for example:
{
  "state": "NORMAL",
  "visibility": "PRIVATE",
  "content": "#memos #openclaw\n\nImplemented tag discovery before creating this memo."
}
  1. Call MemoService_CreateMemo with that content body.

Prefer reusing an existing tag when it clearly expresses the same concept. If the meaning is uncertain, inspect old memo examples first instead of inventing normalization rules.

3. Long content fallback

When creating or updating a memo, if the content is too long for one memo:

  1. Keep the first chunk in the memo itself.
  2. Append the overflow to comments with MemoService_CreateMemoComment.
  3. If one comment is still too long, keep splitting the remaining overflow into multiple ordered comments until everything is stored.

Use this as the default fallback instead of truncating content silently.

4. Exact API work

When the user asks to create, update, delete, attach files, add reactions, or inspect one exact endpoint:

  1. Run bun run scripts/memos.ts ops
  2. If needed, run bun run scripts/memos.ts describe <operationId>
  3. Use bun run scripts/memos.ts call <operationId>...

This keeps the agent aligned with the documented API surface instead of inventing raw requests.

5. Resource naming rules

Path placeholders usually expect bare ids:

  • --path memo=0195c...
  • --path attachment=abc123
  • --path activity=evt_123

Request bodies often expect full resource names:

  • memos/0195c...
  • attachments/abc123

If you accidentally pass a full resource name into a path flag, the CLI strips the leading path and keeps the last segment.

6. Update requests

Patch endpoints such as:

  • AttachmentService_UpdateAttachment
  • MemoService_UpdateMemo

need --query updateMask=....

Without it, many updates fail or update less than expected.

7. Complex bodies and binary uploads

Prefer @file.json for larger bodies:

bun run scripts/memos.ts call MemoService_CreateMemo --body @/tmp/memo.json

Use the helper for attachments instead of hand-building base64:

bun run scripts/memos.ts attachment-body --file /path/to/file --output /tmp/body.json

Then create the attachment:

bun run scripts/memos.ts call AttachmentService_CreateAttachment --body @/tmp/body.json

Read next when needed

  • Read references/query-recipes.md for recent/latest/search workflows, time-window semantics, and memo post-processing examples.
  • Read references/api-summary.md for the compact endpoint catalog, body hints, and pagination details.

Output expectations

When using this skill for execution:

  • call the real API instead of only describing it
  • prefer latest, recent, or search for retrieval tasks instead of hand-writing pagination logic each time
  • return the important response fields to the user
  • if you create or update resources, include the resource name or id in your answer
  • if the API returns an error, surface the status and body plainly instead of hiding it

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.89%
按下载量换算27

Claude

30.35%
按下载量换算22

Cursor

20.46%
按下载量换算15

Gemini CLI

10.68%
按下载量换算8

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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