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maimemo_query_study_records

Read-onlyIdempotent

Query Maimemo study records to count total planned items or list words scheduled for a future study date, filtered by tags, word IDs, or spellings.

Instructions

查询学习记录(公测) 查询场景举例

  • 获取规划总量:as_count=true

  • 获取未来某天要背的单词数:next_study_date: {end: "2026-04-01T00:00:00+08:00"}, as_count=true

  • 获取未来某天要背的单词列表:next_study_date: {end: "2026-04-01T00:00:00+08:00"}

    \

公测期间不保证可用性和可能会随时调整,需要在 App 中开启自动同步

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes暂无文档

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish readOnlyHint, idempotentHint and non-destructive behavior, so the safety profile is covered. The description adds non-annotation value by disclosing beta status, no availability guarantee, possible changes, and the prerequisite that auto-sync must be enabled in the App.

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?

Purpose is front-loaded and the examples are dense and useful, but the trailing beta warning carries stray formatting (backslash, <b> tags) that adds noise without adding information beyond the warning itself.

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 no output schema, the description's examples implicitly communicate the two return shapes (aggregate count vs. record list) and the beta caveat warns about reliability, which is enough for an agent to call and interpret it. Pagination/limit behavior is left entirely to the schema.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3, but the worked examples show how parameters combine in practice (as_count with next_study_date.end to return a count vs. omitting as_count to return the list), which is meaning the schema alone does not convey. It does not explain limit or tag semantics beyond the schema.

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 opening line '查询学习记录' states a clear verb+resource, and the three scenario examples sharpen what 'study records' actually covers (planning totals, upcoming study counts, upcoming word lists). It does not explicitly contrast itself with the nearby sibling maimemo_get_study_progress, so it stops short of a 5.

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

Usage Guidelines4/5

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

Usage is conveyed through three concrete call scenarios rather than prose when/when-not rules: use as_count=true for totals, next_study_date.end for future-day counts or lists. That gives an agent clear selection context, but no exclusion or alternative-tool guidance is offered.

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