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get_topic_primer

Get a concise primer on a legal topic before answering exam questions, covering key statutes, important court rulings, doctrinal debates, and common traps.

Instructions

考點重點提示:做題前必讀的核心法條/常考判決釋字/學說對立/易錯陷阱。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topic_pointYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It describes the content (core statutes, judgments, doctrines, traps) but doesn't disclose behavioral traits such as whether it returns a summary, whether it requires prior progress, whether it's read-only, or what the output format is. For a tool that likely just returns study material, the lack of behavioral detail is a gap.

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 a single, concise sentence that front-loads the purpose ('考點重點提示') and lists the content categories. It is efficient and easy to parse, though it could benefit from a brief usage note.

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 the tool has one parameter, no output schema, and no annotations, the description should provide more context about how to invoke it correctly. It tells the agent what the primer contains but not how to specify the topic, what the return value looks like, or how this differs from get_issue_primer. The description is incomplete for an agent to use it confidently.

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 the parameter 'topic_point' at all. The parameter name suggests it's a topic identifier, but the description doesn't clarify what values are valid, how to format them, or how they relate to the tool's purpose. With zero schema coverage and no parameter explanation, the description fails to compensate.

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 states a specific purpose: providing key points (core statutes, common judgments/interpretations, doctrinal conflicts, common traps) before answering questions. It clearly identifies the resource (topic primer) and its content. However, it doesn't explicitly differentiate from the sibling get_issue_primer, which likely serves a similar role for issues rather than topics.

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 says '做題前必讀' (must-read before doing questions), which implies when to use it: before attempting practice questions. It doesn't explicitly state when not to use it or name alternatives like get_issue_primer. The usage context is implied but not fully explicit.

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