Skip to main content
Glama

compare_by_party

Compare political parties' stances on any theme. Aggregates Japanese Diet statements by party, highlighting common points, differences, and source citations.

Instructions

指定テーマについて政党別の発言を集約・比較します。各政党のスタンス・主要論点の違い、共通点・相違点を出典付きで返します。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fromNo検索開始日 (YYYY-MM-DD)。省略可
modeNo出力粒度: brief(主要政党のみ・簡潔)/ standard(標準)/ detailed(詳細・コスト高)standard
queryYes比較対象テーマ(例: "生成AI", "財政政策")
untilNo検索終了日 (YYYY-MM-DD)。省略可
max_itemsNo最大対象発言件数(既定: 30)
nameOfMeetingNo特定会議に絞る場合に指定(例: "予算委員会")
include_differencesNo相違点を出力に含めるか
include_common_pointsNo共通点を出力に含めるか
Behavior3/5

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

The description discloses that output includes sources ('出典付きで返します'), which is useful. However, with no annotations provided, the description carries the full burden for behavioral traits. It doesn't mention read-only nature, potential cost implications of 'detailed' mode, or how time filters apply. It adds some value but lacks depth.

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, focused sentence that immediately states the tool's purpose and output. Every word contributes meaning: aggregate, compare by party, return differences/commonalities with sources. No wasted text.

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

Completeness3/5

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

With 8 parameters and no output schema, the description should clarify return structure and key behaviors. It does state the output includes stances, differences, commonalities, and sources, which is helpful. However, it omits mention of the 'mode' parameter (brief/standard/detailed), time filtering, or any limitations, leaving gaps for a complex comparison tool.

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 the baseline is 3 even without parameter details in the description. The description only refers to the specified theme (query), but the schema already documents each parameter and its purpose. No additional semantic value is added beyond the schema.

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 clearly states a specific verb and resource: 'aggregates and compares statements by political party on a specified theme.' It explicitly mentions returning stances, differences, commonalities with sources, which distinguishes it from sibling tools like compare_over_time that likely focus on temporal comparison.

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

Usage Guidelines4/5

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

The description provides clear context on when to use the tool: for aggregating and comparing party-specific discourse on a given theme. It does not explicitly exclude alternatives or mention siblings, but the 'by party' focus is explicit, giving clear usage context without needing further exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/harutomo51/kokkai-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server