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Glama

get_reading_unit

Read-only

Retrieve a specific text segment from a reading unit by providing material ID and unit locator, with optional offset and character limits for targeted study access.

Instructions

Read a bounded text slice from one reading unit

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offsetNoCharacter offset; default 0
locatorYesOne-based unit locator
max_charsNoMaximum characters; max 24000
material_idYesReading material ID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes原始 DeepTutor 工具返回值;其具体字段由对应 DeepTutor API 决定。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful context about boundedness and the single-unit scope, but it does not disclose behaviors such as offset handling, locator semantics, or limits beyond what the schema already states.

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 a single front-loaded sentence with no wasted words. It conveys the essential operation and scope immediately, and every part of the sentence earns its place.

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?

The full parameter descriptions, read-only annotations, and presence of an output schema cover most of what an agent needs to call the tool correctly. The main gap is the lack of explicit guidance about when to use this tool versus reading-material and book-page alternatives, but the structured metadata compensates well.

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 every parameter is already documented. The description adds no parameter-specific meaning beyond what the input schema provides, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Read'), a clear resource ('one reading unit'), and a scope qualifier ('bounded text slice'). It is distinct enough from likely siblings like get_reading_material, but it does not explicitly name or contrast any sibling.

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 phrase 'bounded text slice' implies the tool is for reading a portion of a reading unit rather than the full material, so usage is inferable. However, it does not state when to prefer this over alternatives like get_reading_material or get_book_page, nor does it mention exclusions.

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