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StatPan

AssemblyMCP

by StatPan

get_committee_work_summary

Retrieve a committee's current work summary, including pending bills and related reports. Enter a committee name to view objective information mapped from legislative data.

Instructions

특정 위원회의 현재 활동 현황(계류 의안, 관련 보고서 등)을 한 번에 조회합니다. 엔티티 간의 연관 데이터를 매핑하여 객관적인 정보를 제공합니다.

Args: committee_name: 위원회명 (예: "법제사법위원회", "환경노동위원회").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
committee_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.6.6

TDQS

A3.7/5.0
Behavior3/5

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

There are no annotations, so the description carries the behavioral burden. It does add context by saying it maps related data between entities and provides objective information, and the verb '조회' implies a read-only query. But it does not state side effects, failure behavior, or what the mapping process entails beyond that brief phrase.

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 compact: two purpose sentences plus one parameter explanation. The main function is front-loaded, and there is no filler, repetition, or irrelevant detail.

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?

For a single-parameter query tool with an output schema, the description covers the core needs: what it returns, the input meaning, and the tool's general behavior. It omits edge-case or failure-mode guidance, but at this low complexity that is not a critical gap.

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 0%, so the description must compensate. It does: the Args section names committee_name, defines it as '위원회명', and gives concrete examples such as '법제사법위원회' and '환경노동위원회'. This adds real meaning beyond the bare string type, though it is not exhaustive about constraints.

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 clearly states a specific verb and resource: retrieving a specific committee's current activity status (pending bills, related reports, etc.). It is distinct from siblings like get_committee_info in function, but it does not explicitly name or contrast alternatives, 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 Guidelines3/5

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

The phrase 'current activity status... at a glance' implies a summary use case, so an agent can infer when to call it. However, there is no explicit when-to-use/when-not-to-use guidance and no reference to sibling tools such as get_committee_info or get_legislative_reports.

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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