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get_registration_statement

Read-only

MyDART MCP의 get_registration_statement 도구는 증권신고서 주요정보 6종 — 모집·매출 조건, 인수인, 자금 사용목적, 합병·분할 조건을 정형 JSON 으로 조회합니다.

[Purpose]

  • Filed terms of a 증권신고서: 공모가액·인수인·자금의사용목적·합병비율·주식매수청구권.

  • Board decision: get_corporate_event / listing scan: search_disclosures(kind="issuance") / narrative (투자위험요소): download_document.

[Usage]

  1. "대한항공 유상증자 조건" → corp="대한항공", statement_type="equity"

[Response]

  • filings[] = one per 신고서(rcept_no), newest first. sections: general·securities·underwriters·fund_use·sellers·put_right·issued_securities·parties.

  • date = 접수일 (정정본: 정정 접수일, may fall outside window). Values are raw strings; '-'(해당없음) fields omitted.

[Rules]

  • Only latest 정정본 is returned once corrected — original terms not included (original rcept: search_disclosures → download_document).

  • Withdrawn filings are unmarked — confirm via 철회신고서·증권발행실적보고서.

  • No data ≠ not issued: 사모·일괄신고서·소액공모 out of scope. Per-type status in sections_meta.

  • fetch_failed/truncated_note types mean "unconfirmed", not "none" — re-query that type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo조회 종료일(YYYY-MM-DD / YYYYMMDD). 기본 오늘
corpYes회사명/종목코드/corp_code — DS006 은 corp_code 필수라 회사 없는 전수 조회는 불가
limitNo반환할 신고서 건수 상한(rcept_no 단위, 접수일 최신순 — 기본 10). 초과분은 잘리고 truncated=true·total_filings 로 표시된다. 인수인 그룹이 신고서당 수십 행이라 행이 아니라 신고서 단위로 자른다
startNo조회 시작일(YYYY-MM-DD / YYYYMMDD) — **신고서 최초접수일** 기준. 기본값은 데이터 하한인 2015-01-01(전기간)이며 생략 시 period.defaulted:true. 증권신고서는 드문 이벤트라 창을 좁히면 오히려 놓친다 — DS006 은 페이징이 없어 창을 넓혀도 호출 비용이 같다
statement_typeNo신고서 종류 — 단일 값 또는 배열, **미지정 시 6종 전부 병렬 조회**(DART 6콜 고정). equity=지분증권(유상증자·IPO) / debt=채무증권(회사채) / depositary=증권예탁증권(DR) / merger=합병 / stock_exchange=주식의포괄적교환·이전 / division=분할. 묶음 별칭 'offering'(공모 3종)·'restructuring'(구조조정 3종)과 한글명(회사채·합병·분할 등)도 수용

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/non-destructive, and the description adds substantial behavioral caveats beyond those: only the latest corrected filing is returned once corrected (originals must be fetched via search_disclosures → download_document), withdrawn filings carry no marker, empty data should not be read as 'not issued', and fetch_failed/truncated_note values mean 'unconfirmed' not 'none'. These are exactly the silent behaviors that would lead wrong conclusions.

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?

The description is well-structured into named sections (Purpose/Usage/Response/Rules) with the main purpose front-loaded in the first sentence. It is long, but each section earns its place — especially the Rules block, which contains four distinct hard-won operational warnings. It loses one point for a mild redundancy between the opening sentence and [Purpose] restating overlapping terms.

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?

Even without an output schema, the [Response] section defines the filings[] structure, the nine inner sections, ordering (newest first), date semantics (corrected filings can carry an amended date outside the requested window), and raw string values with '-' fields omitted. Combined with safety disclosures covered by annotations and a schema that documents every parameter, nothing predictable for the agent is missing.

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 the schema itself is unusually detailed (start date = original filing acceptance date, limit cut at filing level not row level, statement_type supports single/enum/array/alias/Korean names). The description adds marginal meaning beyond that: a concrete natural-language usage example ('대한항공 유상증자 조건' → corp='대한항공', statement_type='equity') and the note that widening the date window costs nothing. Baseline 3 is appropriate because the schema does the heavy lifting.

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 states a specific verb-resource pair: the tool retrieves 6 types of key information from securities registration statements (모집·매출 조건, 인수인, 자금 사용목적, 합병·분할 조건) as structured JSON. It also differentiates itself from siblings by naming get_corporate_event, search_disclosures(kind="issuance"), and download_document as the tools for adjacent needs, so an agent can distinguish it without opening schemas.

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

Usage Guidelines5/5

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

The [Purpose] section explicitly routes three alternative situations: board decision → get_corporate_event, listing scan → search_disclosures(kind="issuance"), narrative/investment-risk → download_document. The [Rules] section adds the other side, stating when results must not be trusted (withdrawn filings unmarked, 사모·일괄신고서·소액공모 out of scope), leaving no ambiguity about when this tool is the right one.

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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TDQS

A4.7/5.0
Disambiguation5/5

Every tool targets a distinct aspect of the DART disclosure domain: full text, attachments, financial figures, audit facts, audit narrative, ICFR, going concern, company profile, events, periodic report sections, XBRL, valuation, usage stats, and two search entry points. Overlaps are resolved by explicit cross-references and clear purpose statements (e.g., get_audit_profile vs get_audit_report vs get_internal_control). No ambiguity remains.

Naming Consistency5/5

All 16 tools follow a consistent snake_case verb_noun pattern, with get_ for data retrieval, search_ for list queries, find_ for ID resolution, and download_ for the one document fetch. There is no mixing of camelCase, action words, or stylistic inconsistency. The pattern is immediately predictable.

Tool Count5/5

16 tools is slightly above the typical 3–15 range but fully justified by the breadth of DART (Korea's electronic disclosure system) – covering company lookup, filings, financials, audit reports, internal control, going concern, events, periodic reports, attachments, XBRL, valuation, and usage stats. Each tool address a distinct functional need, and no tool feels redundant or extraneous. The scope is comprehensive yet not bloated.

Completeness5/5

The tool surface covers the full lifecycle of disclosure data access: finding entities (find_corp_code), locating filings (search_disclosures), retrieving financials (get_financials, get_xbrl), reading full text (download_document), fetching attachments (get_attachments), and drilling into audit-related details (get_audit_profile, get_audit_report, get_internal_control, get_going_concern). Periodic report sections (28 types) and corporate events cover governance and capital changes. No obvious dead ends or missing critical operations for a read-only disclosure access server.

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