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Æfact — Korean fact desk for AI agents

확인 요청

request_check
Idempotent

한국에 관한 사실 문장 하나의 확인을 Æfact에 요청합니다. 법령 시행일·한국은행 기준금리·월별 소비자물가 상승률·문장 안 증감률·비율·합계는 바로 원자료로 판정해 공개 결과 주소(url)와 인용 한 줄(cite)을 돌려줍니다. 그 밖의 문장은 접수(status=queued)되어 수요로 집계됩니다. 결과는 공개됩니다(개인정보·정치·수사·재판·의료·연예 사생활 문장은 받지 않음). 같은 문장은 같은 결과를 돌려줍니다. EN: Submit a Korean factual claim for verification. Decidable claims (law effective dates, BOK base rate, monthly CPI, in-sentence arithmetic) are judged immediately against primary data and published at a public URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYes확인할 문장 하나(원문 그대로). 예: 근로기준법 개정안은 12월 8일부터 시행된다 / 9월 소비자물가 상승률은 2.9%다
contextNo선택: 맥락(누가·언제 한 말인지 등)
source_urlNo선택: 문장이 나온 주소

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: it discloses the write side effect (claims are accepted with status=queued and aggregated as demand), the idempotency behavior ('같은 문장은 같은 결과'), the return payload (public url + one-line cite), and privacy restrictions. This is well beyond what readOnlyHint=false/idempotentHint=true already convey.

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 and the decision rule, and every sentence carries information. The bilingual Korean/English duplication adds length but serves a legitimate audience purpose rather than pure padding.

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

Completeness5/5

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

With no output schema, the description fully carries the return-value burden (public url, cite, status=queued) and also covers exclusions, idempotency, and the immediate-vs-queued branching. An agent has everything needed to call and interpret it.

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% and all three parameters are documented with examples in the schema itself. The description reinforces the claim types but adds no syntax or format detail beyond what the schema already provides, 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: submitting a single Korean factual claim for verification to Æfact, and enumerates the decidable claim types (law effective dates, BOK base rate, monthly CPI, in-sentence arithmetic). It does not explicitly distinguish itself from retrieval siblings like get_fact or get_request, so it falls 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 Guidelines4/5

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

Gives clear when-to-use context (decidable claims are judged immediately; others are queued) plus an explicit when-not exclusion list (personal info, politics, investigation, trial, medical, celebrity private life). It does not name an alternative sibling for non-submittable cases, so no explicit alternative routing.

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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