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hinoyayoi

japanese-learning-memory

by hinoyayoi

get_due_reviews

Fetch due reviews and new items from your Japanese learning memory, with filters for item type, review type, and date. A read-only query to plan spaced-repetition practice.

Instructions

Return due reviews and new learning items; this query never mutates data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofNo
limitNo
item_typeNo
review_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explicitly states 'never mutates data', which is a key non-mutating guarantee. This adds valuable context beyond the schema, though it omits other potential behaviors like pagination.

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?

Two sentences, front-loaded with the main purpose, followed by a behavior note. Every word earns its place with no unnecessary content.

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

Completeness2/5

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

For a tool with 4 optional parameters, no annotations, and zero parameter documentation, two sentences are inadequate. The output schema covers return structure, but parameter roles and usage context are missing, leaving the agent under-informed.

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

Parameters2/5

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

Schema description coverage is 0% and the description does not explain any of the four parameters (as_of, limit, item_type, review_type). The mention of 'new learning items' only vaguely hints at item_type/review_type filtering, insufficient for correct parameter use.

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 uses the specific verb 'return' and names the resource 'due reviews and new learning items', clearly distinguishing this read tool from the sibling mutation tools. The read-only note further clarifies its role.

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

Usage Guidelines2/5

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

No explicit when-to-use guidance or alternatives are provided. The statement 'this query never mutates data' implies safety but does not tell the agent when to choose this tool over search_items or others.

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

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