weread-mcp

书籍公开点评

list_book_reviews

Read-only

Retrieve public book reviews from WeChat Reading. Filter reviews by type, paginate through results, and view normalized star ratings and review excerpts.

Instructions

获取书籍的公开点评（/review/list）——其他读者的评价，不是个人笔记（个人笔记用 get_my_reviews）。

    结构注意：存在双层嵌套，点评内容在 `reviews[].review.review.content`、
    `...star`、`...author.name`、`...book.title`。

    评分换算：20=⭐，40=⭐⭐，60=⭐⭐⭐，80=⭐⭐⭐⭐，100=⭐⭐⭐⭐⭐。
    长点评截取前 200 字并提示可展开；`createTime` 转 `YYYY-MM-DD`。
    无结果回复：这本书暂时还没有公开点评哦~

Input Schema

TableJSON Schema

Name	Required	Description
`count`	No	每页数量，默认 20
`book_id`	Yes	书籍 ID
`max_idx`	No	翻页偏移：上一页最后一条的 idx
`synckey`	No	翻页游标，首次 0
`review_list_type`	No	筛选类型：0=全部（默认），1=推荐，2=不行/差评，3=最新，4=一般

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 23, 2026

TDQS

A4.7/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark this as read-only, and the description adds substantial behavioral details: nested response structure, star-rating conversion, truncation of long reviews, date formatting, and the exact no-result message. This goes well beyond what annotations alone convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose, followed by concise, useful behavioral notes. Every section adds distinct value, with no repetition or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only list tool with a fully documented schema and output schema present, the description covers the essential extras: response nesting, formatting transformations, truncation behavior, and fallback message. There are no meaningful gaps for an agent to call and interpret this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters including defaults, enums, and pagination semantics. The description adds no additional parameter-level meaning; it focuses on response behavior instead, which is fine but not above the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches public book reviews, explicitly distinguishes them from personal notes, and names the alternative get_my_reviews. The verb (获取) and resource (书籍公开点评) are specific and match the tool name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says this is for other readers' reviews, not personal notes, and points to get_my_reviews as the correct alternative for personal notes. This gives the agent a clear when-to-use and when-not-to-use rule.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.