weread-skills

A WeRead assistant for searching books, managing a bookshelf, viewing notes and highlights, reading statistics, reviews, and recommendations. WeRead is a Chinese reading service accessed through an agent API.

In plain words
What is it for?
Use it to find books, inspect book details and reading progress, view or export notes and highlights, check reading statistics, browse reviews, and get book recommendations.
Why use it?
It lets an agent retrieve and organize reading information without manually searching through the reading service.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/uvwt/agentdock-skills/docs
Any agent
npx skills add uvwt/agentdock-skills --skill docs
Clone the repo
git clone --depth 1 https://github.com/uvwt/agentdock-skills

Made for: Claude Code, Codex.

Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,400 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00036 $0.02400
Opus 5 $0.00018 $0.01200
Sonnet 5 $0.00007 $0.00480
Haiku 4.5 $0.00004 $0.00240

Measured 2d ago against content hash 38d5a72c8ba9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

weread-skills scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -X POST "https://i.weread.qq.com/api/agent/gateway" \
skills/weread-skills/docs/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

WeRead — 微信读书助手

通过 Agent API Gateway 调用微信读书接口,提供搜索、书架、笔记、书评等能力。

支持的能力

能力 说明 用户示例 详细说明
搜索书籍 在书城搜索 "帮我搜一下三体" search.md
书籍信息 查看书籍详情、章节目录、阅读进度 "这本书有多少章" "我读到哪了" book.md
书架管理 查看书架 "看看我的书架" shelf.md
阅读统计 阅读时长、天数、偏好分析、阅读统计摘要 "我这个月读了多久" "今年读了几本书" readdata.md
笔记划线 查看个人笔记数量与内容,包括划线、想法/点评、书签数量 "看看我在三体里的笔记" "导出我的划线" "在这本书有多少笔记" notes.md
章节热门划线 查看书籍/章节热门划线、划线热度及划线下想法 "看看这章有什么热门划线" "这段话下面有什么想法" notes.md
书籍点评 查看书籍的公开点评 "三体这本书有什么点评?" "看看推荐的点评" review.md
推荐好书 个性化推荐/相似推荐 "给我推荐几本书" discover.md

根据用户意图参考对应说明文件了解接口参数、回包结构和工作流。


接口调用规范

统一入口

POST https://i.weread.qq.com/api/agent/gateway

鉴权

  • Header:Authorization: Bearer $WEREAD_API_KEY
  • WEREAD_API_KEY 从环境变量获取,格式 wrk-xxxxxxxx
  • 若未设置,提示用户:export WEREAD_API_KEY=<你的apikey>
  • API Key 绑定用户身份(vid),需要用户身份的接口会自动注入,无需手动传 vid

请求格式

  • Method:POST
  • Content-Type:application/json
  • Body:JSON,api_name 指定接口,其余为接口参数,每次请求必须带 skill_version
curl -X POST "https://i.weread.qq.com/api/agent/gateway" \
  -H "Authorization: Bearer $WEREAD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api_name": "/store/search", "keyword": "三体", "count": 10, "skill_version": "1.0.6"}'

请求 few-shot

正确:业务参数平铺在 body 顶层。

{"api_name":"/user/notebooks","count":100,"skill_version":"1.0.6"}

正确:下一页继续平铺 lastSort

{"api_name":"/user/notebooks","count":100,"lastSort":1516907353,"skill_version":"1.0.6"}

错误:不要把业务参数包在 params 内。

{"api_name":"/user/notebooks","params":{"count":100,"lastSort":1516907353},"skill_version":"1.0.6"}

上面的错误写法会导致 countlastSort 未被转发,后端按默认值返回第一页,看起来像分页失效。

响应格式

  • JSON,回包经过字段裁剪,只返回核心字段
  • errcode 非 0 时表示错误,给出中文提示
  • 发送 {"api_name": "/_list"} 可查看所有可用接口及参数定义

通用规则

  1. 版本上报:每次请求 body 必须包含 "skill_version": "1.0.6"(取本文件顶部 version 字段的值),用于服务端检查版本更新。如果回包中出现 upgrade_info 字段,必须立即暂停当前操作,按照 upgrade_info.message 中的指引完成升级,升级完成后再重新执行用户请求,不得忽略该字段
  2. 参数平铺:业务参数必须和 api_nameskill_version 放在同一层;不要包在 paramsdatabody 等对象里。只有接口文档明确声明的数组/对象字段(如 /book/readreviewsreviews)才允许作为业务字段传入。
  3. 能力文档预检:调用任何接口前,必须先根据「支持的能力」表阅读对应说明文件(如阅读统计先读 readdata.md,书架先读 shelf.md),确认接口参数、字段含义、单位、计数口径和工作流;禁止仅凭字段名或经验猜测含义。
  4. 字段解释优先级:解释接口回包时,以对应说明文件中的字段说明为准;如果回包字段名和直觉含义冲突,必须服从说明文件,不得直接翻译字段名。
  5. bookId 解析:用户输入书名时,先调 /store/search 获取 bookId,再执行后续操作
  6. 书架数量:使用 /shelf/sync 回答“书架有多少本书/多少条目”时,必须按 books.length + albums.length + (mp 非空 ? 1 : 0) 计算;albums[] 是专辑/有声书,也属于书架里的书,详细规则见 shelf.md
  7. 结果展示:列表用编号展示方便选择;搜索结果重点展示书名、作者、评分;展示接口回包信息时,字段禁止直接翻译,应该参考文件中的说明内容提供
  8. 上下文衔接:对话中记住已查询的 bookId,后续操作无需用户重复提供
  9. 深度链接:在展示划线、想法、章节等内容时,拼接对应的跳转链接方便用户直接在 App 中打开,具体格式见下方「深度链接(URL Schema)」章节
  10. 数据展示规范
  • 时间戳:所有 Unix 时间戳字段(如 updateTimecreateTimefinishTimereadUpdateTime 等),展示时须转为 YYYY-MM-DD 格式(如 1748563200 展示为"2025-05-30"),不得直接展示原始数字
  • 阅读时长:单位为秒,展示时转为"X小时Y分钟"格式

Read the full file on GitHub · 172 lines

Files

What ships with it

8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 172 lines · 36 tokens per session scan A 38d5a72c8ba9

Subscribe to this mod's changes

weread-skills is a skill published in the GitHub repository uvwt/agentdock-skills (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 36 tokens to every session and 2,400 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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