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为你推荐

recommend_books
Read-only

Get personalized book recommendations based on your reading history, matching the WeChat Reading app's 'For You' feed. Each recommendation includes a reason, rating, and reader count.

Instructions

基于个人阅读记录的个性化推荐(/book/recommend), 与 App 首页「为你推荐」一致。

    每本书含 `reason`(推荐理由)、`newRating`(0-100)、`readingCount`(在读人数)。
    翻页用最后一条的 `searchIdx` 作为下次的 `max_idx`。
    无结果回复:暂时没有找到合适的推荐,换个关键词试试?
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo每页数量,默认 12
max_idxNo翻页偏移:上一页最后一条的 searchIdx

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description usefully discloses output fields (reason, newRating, readingCount), the pagination protocol (using the last item's searchIdx as the next max_idx), and the exact no-results response message. This gives the agent practical behavioral expectations not present in annotations alone.

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

Conciseness4/5

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

The description is concise and logically structured: purpose first, then output fields, then pagination, then empty-result message. Each segment earns its place, though the pagination detail partially duplicates the schema description.

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

Completeness4/5

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

With an output schema present, the description doesn't need to enumerate return values in full. It still provides the key behaviorally relevant fields, the pagination mechanism, and the no-results phrasing, which is sufficient for an agent to invoke and interpret the 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 coverage is 100% with both count and max_idx already described. The description's pagination line essentially restates the max_idx schema description ("上一页最后一条的 searchIdx") rather than adding new meaning, so it stays at the baseline 3.

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

Purpose4/5

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

The description clearly identifies the tool as a personalized recommendation based on personal reading records and explicitly ties it to the App home page feature, giving a specific verb+resource. It does not explicitly name sibling tools, but the purpose is distinct enough from search_books and similar_books that an agent can differentiate it without opening schemas.

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

Usage Guidelines3/5

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

The description implies when to use the tool (when a personalized recommendation based on reading history is needed) by stating it matches the App home page recommendation. However, it does not explicitly say when not to use it or mention alternatives like search_books or similar_books, leaving the choice to inference.

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