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Æfact — Korean fact desk for AI agents

대상 하나 조회

get_entity
Read-onlyIdempotent

대상 하나의 속성(근거 출처 포함), 현재 사실, 연결된 대상을 줍니다. 법령이면 상위법·하위법(시행령·시행규칙)·소관부처, 기관이면 소관 법령 목록입니다. 연결은 원자료(법제처 법령 체계도·법령 목록)에서 확인된 것만 있습니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes대상 id. 예: law-011357, org-1790365, org-bok
relation_limitNo돌려줄 연결 수 상한

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds genuinely new behavioral context: connections are limited to those verified in the source material (법제처 법령 체계도/목록), and returned attributes carry source citations. It omits any note on how relation_limit paginates or what happens when the cap is hit.

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?

Three sentences, front-loaded with the return payload, then the entity-type breakdown, then a provenance caveat. Each earns its place, though the caveat sentence is somewhat tangential to selecting the tool.

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?

With no output schema present, the description correctly carries the return-value burden, naming attributes, facts, and connections and explaining relation semantics per entity type. It stops short of describing relation_limit behavior or total-result shaping, a modest gap for a read 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%: id format examples (law-011357, org-1790365, org-bok) and relation_limit's default/max/min are all documented in the schema. The description adds no parameter-level detail beyond that, so the baseline 3 applies.

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?

States a specific verb+resource: retrieve a single entity with its attributes (including source citations), current facts, and connections. The type-specific detail (laws → parent/subordinate statutes and ministry; organizations → managed statutes) pins down the domain. It does not, however, contrast itself against sibling search_entities or lookup, so an agent must infer the id-first nature from the schema.

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 is entirely about what is returned; it never states when to reach for this tool versus search_entities, lookup, or get_fact. There is no mention of prerequisites (needing a known id) or exclusions, leaving routing to be inferred from the name alone.

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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