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Glama

get_exam_paper

Retrieve the complete exam paper for a specified year, exam, and subject, including all questions.

Instructions

取整份試卷(某年·某考試·某科目全部題目)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
subjectYes
exam_codeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It states the core behavior — retrieving all questions in a full exam paper — which implies a read-only fetch, but it does not mention any output limits, ordering, or whether secondary materials like answers are included. This is adequate for a simple getter but not rich.

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 efficient sentence with no filler. The main action is front-loaded and the parenthetical adds the necessary scoping. Every word contributes to the definition.

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?

Given a field of 28 sibling tools, this description does not situate the tool relative to question-level or search-level alternatives. It also lacks parameter semantics and usage guidance, so an agent has only the name and a one-line gloss to decide when this tool is appropriate.

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%, so the description must compensate for the three undocumented parameters. It only paraphrases them as '某年·某考試·某科目', adding minimal meaning beyond the property names year, exam_code, and subject. It does not explain acceptable formats, ranges, or how to discover valid codes.

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 ('取' / get) and a precise resource ('整份試卷' / entire exam paper), and clarifies the scope as all questions for a year, exam, and subject. It does not explicitly name a sibling tool, but the '全部題目' phrasing inherently distinguishes it from get_question.

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?

The description gives no guidance about when to use this tool versus alternatives like search_questions, get_question, or get_exam_map. There are no conditions, exclusions, or references to sibling tools, so the agent must infer usage from the tool name and general phrasing.

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