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Æfact — Korean fact desk for AI agents

한 번에 찾기

lookup
Read-onlyIdempotent

질문에 나온 대상(법령·기관)과 지금 참인 사실을 한 번에 찾습니다. 처음엔 이 도구를 쓰세요. 띄어쓰기·가운뎃점은 무시합니다. 사실마다 freshness(낡음 여부)와 cite(답변에 붙일 인용 한 줄)가 있습니다. EN: One-call lookup of Korean entities (laws, agencies) and current verified facts (economic indicators, law effective dates). Each fact has freshness and a ready-to-paste citation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes예: 기준금리, 원달러 환율, 개인정보보호법, 국토교통부

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower, yet the description still adds behavior the annotations cannot: matching ignores whitespace and middle dots, and each returned fact carries freshness and a ready-to-paste citation. That normalization rule and return-shape context are genuinely useful beyond structured fields.

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?

Front-loaded with purpose, then the 'use first' routing cue, normalization note, and return-value note in a tight sequence. The Korean and English blocks are somewhat redundant but serve cross-lingual agents rather than being pure filler.

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?

There is no output schema, so the description correctly compensates by describing the freshness and cite fields that come back per fact, and annotations carry the safety profile. It is nearly complete, missing only how the `limit` behaves and what an empty/no-match result looks like.

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?

With only 50% schema coverage, the description should compensate, and it partly does: it explains that the query targets entities named in a question and that spacing/middle-dot punctuation is normalized, which clarifies the query param. However, the `limit` parameter is undocumented in both the schema and the description, leaving a real gap.

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 verb and resource: a one-call lookup of Korean entities (laws, agencies) and current verified facts (economic indicators, effective dates), narrowing the domain explicitly. It implicitly contrasts with the granular siblings (get_entity, get_fact, search_entities, search_facts) by declaring itself the one-call combined entry point, but it does not name any sibling outright.

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?

"처음엔 이 도구를 쓰세요" (use this tool first) gives explicit, actionable when-to-use guidance for an entry-point tool. It stops short of naming when NOT to use it or pointing to the specialized getters/search tools as alternatives for narrow lookups.

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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