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Agent Skill · 开发

reader-recap(读者回顾)

reader-recap 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

reader-recap 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 5,318。

总安装 6,528周安装 272GitHub Stars 201下载 2,176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:reader-recap(读者回顾)
来源仓库:https://github.com/readwiseio/readwise-skills
仓库路径:skills/reader-recap
安装命令:
npx skills add https://github.com/readwiseio/readwise-skills --skill reader-recap
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/readwiseio/readwise-skills --skill reader-recap

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在需要围绕仓库状态、代码变更或协作事项进行整理的场景中使用。通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限和维护状态。使用前建议核实是否会触发联网、命令执行或文件读写等操作。

可结合原始 README 和仓库路径进一步核验具体用法和功能边界。

来源仓库内路径:skills/reader-recap

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/readwiseio/readwise-skills --skill reader-reca…;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

    它需要调用外部服务,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

reader-recap 怎么安装?

在终端执行 npx skills add https://github.com/readwiseio/readwise-skills --skill reader-recap。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

reader-recap 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。

reader-recap 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

reader-recap 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。

reader-recap 用的人多吗?

公开数据是累计安装 6,528 次,近一周安装 272 次,下载 2,176 次,GitHub 201 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。

reader-recap 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
reader-recap

读者回顾 · 本页

6,528201调用外部服务未明确有提醒

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

You are summarizing the user's recent reading activity from Readwise Reader. Follow this process carefully.

Readwise Access

Check if Readwise MCP tools are available (e.g. mcp__readwise__reader_list_documents). If they are, use them throughout. If not, use the equivalent readwise CLI commands instead (e.g. readwise list, readwise read <id>, readwise highlights <id>). The instructions below reference MCP tool names — translate to CLI equivalents as needed.

Setup

  1. Check for persona file. Read reader_persona.md in the current working directory if it exists. Use it to personalize the briefing tone and to contextualize the user's annotations (e.g. connecting highlights to their known interests). If no persona file exists, proceed without it — the recap works fine standalone.
  2. Determine time window. Parse the argument as a number of days. Default to 1 (last 24 hours) if no argument is given.
/reader-recap           # last 24 hours
/reader-recap 7         # last 7 days
/reader-recap 30        # last 30 days

Step 1: Fetch Recent Documents

Query Reader for documents the user archived or moved to "later" within the time window. Run both calls in parallel:

mcp__readwise__reader_list_documents(location="archive", updated_after=<cutoff>, limit=100, response_fields=["title", "author", "category", "notes", "source_url"])
mcp__readwise__reader_list_documents(location="later", updated_after=<cutoff>, limit=100, response_fields=["title", "author", "category", "notes", "source_url"])

Combine and deduplicate results by document ID.

If no documents are found, report "No archived or moved documents in the last [N] days" and stop.

Step 2: Get Highlights

For each document returned, fetch highlights:

mcp__readwise__reader_get_document_highlights(document_id=<id>)

After fetching, split documents into three groups:

  • Annotated — has highlights where the user left notes (the note field is non-empty), OR has a non-empty document-level notes field
  • Highlighted only — has highlights but none with user notes
  • No engagement — zero highlights and no document-level notes (archived without reading)

Step 3: Classify Annotations

For each annotated document, scan the user's notes on highlights and the document-level notes field. Flag anything actionable:

FlagPattern
QuestionContains "?" or asks something
TODOSays to look up, verify, follow up, try, or do something
IdeaConnects multiple concepts or proposes something new
DisagreementPushes back on the source's claim
Cross-referenceMentions another book, article, or author by name

Annotations that don't match any pattern are just context — the user thinking out loud. Still include them in the briefing.

Step 4: Write the Briefing

Write a conversational recap — like a well-read assistant catching someone up over coffee. Warm, concise, and useful. Not a data dump.

Structure:

  1. Opening line — a one-sentence overview of the time period. "You had a busy week — 12 articles and a book, mostly history and AI stuff." "Quiet day — just two articles, but you had a lot to say about one of them."
  2. Per-document paragraphs — one short paragraph per annotated document, ordered by engagement (most annotated first). Each paragraph should naturally weave together:

- What the piece was about (1 sentence) - How much the user highlighted (folded into the flow, not as a stat line) - The most interesting annotations, especially actionable ones — paraphrase the user's notes conversationally: "You had a question about whether this applies to mammals too." "You noted you want to try this workflow yourself." "You pushed back on the author's claim about pricing." - If the user left a document-level note, lead with it — it's usually the overall reaction

  1. Light reads — a single sentence listing documents the user highlighted but didn't annotate. "You also highlighted a few things in [Title] and [Title] but didn't leave notes."
  2. Action items — if any annotations were flagged as TODOs, questions, or ideas, collect them at the end as a short bulleted list under "Things you might want to follow up on:". Skip this section entirely if nothing is actionable.

Example output:

Busy couple of days — you finished 8 articles and a chunk of that Ottoman
history book. Most of your attention went to the logistics stuff.

You were really into Sarah Chen's piece on supply chain resilience. 14
highlights, and you left a note saying the comparison to Roman grain
logistics was "exactly what I've been looking for." You also flagged a
question — whether the same bottleneck pattern shows up in digital
infrastructure.

The Ottoman book got 9 new highlights across three chapters. Your note on
the harem education system connected it to that article about elite
training programs you read last month. You also marked a claim about
succession rates that you want to verify.

You also highlighted a few things in "Why Bridges Fail" and a Substack
post about medieval farming, but didn't leave notes on either.

**Things you might want to follow up on:**
- Does the supply chain bottleneck pattern apply to digital infrastructure?
- Verify the Ottoman succession rate claim (Chapter 7)
- You wanted to connect harem education to the elite training piece

Tone rules:

  • Second person ("you read", "you noted"), not third person
  • Contractions are fine
  • No bullet-point lists for the main body — prose paragraphs only
  • Keep it skimmable — short paragraphs, one idea each
  • Don't editorialize on the content itself — just report what the user did and said
  • The action items list at the end IS bulleted — that's the one exception
  • If the persona file exists, use it to add context (e.g. "this connects to your interest in X")

Notes

  • This skill is read-only. It doesn't move, tag, or modify any documents.
  • The "archive" and "later" locations catch most finished reading. Documents still in "feed" or "new" are works in progress and aren't included.
  • Annotations (the user's own notes on highlights) are the interesting part. Raw highlights without notes are counted but not shown individually.
  • For large time windows (30 days), there may be many documents. Prioritize the most-annotated ones and summarize the rest in aggregate rather than writing a paragraph for every single one.

平台分布

Codex

37.46%
按下载量换算815

Claude

29.12%
按下载量换算634

Cursor

18.79%
按下载量换算409

Gemini CLI

9.9%
按下载量换算215

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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