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by kr.eocpa
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기준서·기준 원문 전문검색

search_standards
Read-onlyIdempotent

MyKIFRS MCP의 search_standards 도구는 기준서 문단과 감사인증·윤리기준·고시 원문을 한 목록으로 전문검색합니다.

[Purpose]

  • The 기준 grounding a treatment ("사용권자산 손상 is which 문단?"): 기준서 문단 (K-IFRS·일반기업·감사·내부회계· 중소·비영리) plus 감사인증·윤리기준 and 고시 원문 (공익법인·집합건물 회계처리기준 등).

[Usage]

  1. "사용권자산 손상 관련 기준" → query="사용권자산 손상"

  2. "일반기업회계기준에서 리스 분류" → query="리스 분류", category="kgaap"

  3. "1116호 안에서만 리스료 재측정" → query="리스료 재측정", std_num=1116

[Response]

  • { hits, results } by relevance; a matched assure·ext_std keeps ≥1 slot (limit ≥3).

  • kind "paragraph" {std_num, std_title, category, unique_key ("1116-33"·"1109-6.1.1"), snippet} → get_paragraph; kind "assure"·"ext_std" {material_key, category, date, title, snippet} → get_material.

  • Empty query → { error: "검색어가 비어 있음" }.

[Rules]

  • One 쟁점 differs by family (K-IFRS vs 일반기업회계기준 vs 중소기업) — confirm category·std_title fits the entity before citing; narrow with category.

  • Tokens ≥3 chars → FTS (AND, rank); 1~2 → LIKE. 제목 rows excluded.

  • snippet (⟦…⟧ marks) is a fragment — quote get_paragraph/get_material text.

Input Schema

NameRequiredDescriptionDefault
limitNo최대 결과 수 (기본 10, 문단·원문 합계)
queryYes검색 키워드 (공백 구분)
std_numNo특정 기준서로 한정 (예: 1116) — 주면 기준서 문단만
categoryNo기준 계열로 한정 (생략 시 전체) — kifrs(한국채택국제회계기준) · interpretation(해석서) · concept(재무보고를 위한 개념체계) · translation(번역본) · kgaap(일반기업회계기준) · special(특수분야) · audit(감사기준서) · icfr(내부회계관리제도) · sme(중소기업회계기준) · nonprofit(비영리조직회계기준) · other(기업회계기준 전문·적용의견서·회계감사실무지침·행동강령) · assure(감사인증·윤리기준(KICPA, 최신판 — 품질관리·검토·인증·윤리·가치평가서비스 수행기준 등)) · ext_std(외부 기관 기준·고시(공익법인·집합건물 회계처리기준, 분·반기 검토준칙, 공공감사기준 등))

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / category
      Added value: +{
+  "description": "기준 계열로 한정 (생략 시 전체) — kifrs(한국채택국제회계기준) · interpretation(해석서) · concept(재무보고를 위한 개념체계) · translation(번역본) · kgaap(일반기업회계기준) · special(특수분야) · audit(감사기준서) · icfr(내부회계관리제도) · sme(중소기업회계기준) · nonprofit(비영리조직회계기준) · other(기업회계기준 전문·적용의견서·회계감사실무지침·행동강령) · assure(감사인증·윤리기준(KICPA, 최신판 — 품질관리·검토·인증·윤리·가치평가서비스 수행기준 등)) · ext_std(외부 기관 기준·고시(공익법인·집합건물 회계처리기준, 분·반기 검토준칙, 공공감사기준 등))",
+  "enum": [
+    "kifrs",
+    "interpretation",
+    "concept",
+    "translation",
+    "kgaap",
+    "special",
+    "audit",
+    "icfr",
+    "sme",
+    "nonprofit",
+    "other",
+    "assure",
+    "ext_std"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / limit / description
      Previous value: -"최대 결과 수 (기본 10)"New value: +"최대 결과 수 (기본 10, 문단·원문 합계)"
    • changedInput schema / properties / std_num / description
      Previous value: -"특정 기준서로 한정 (예: 1116)"New value: +"특정 기준서로 한정 (예: 1116) — 주면 기준서 문단만"
  2. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare a safe read-only, idempotent search. The description adds substantial behavioral detail beyond that: relevance ranking, a reserved result slot for assure/ext_std when limit >= 3, empty-query error behavior, FTS vs LIKE token thresholds, title-row exclusion, and a warning that snippets are fragments to be quoted from source tools.

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 structured with clear Purpose/Usage/Response/Rules headings and is front-loaded with the core operation. It is somewhat long and repeats the tool name in the opening sentence, but most sentences carry actionable information.

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?

There is no output schema, so the description must explain return values, and it does: it describes the { hits, results } shape, result kinds, key fields, and routing to get_paragraph/get_material. It also covers empty queries, ranking, result slot behavior, and snippet limitations, leaving little relevant ambiguity for the calling agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description still adds meaning beyond the schema: category families are framed around entity reporting regimes, std_num is tied to returning only standard paragraphs, limit interacts with reserved assure/ext_std slots, and query token length affects FTS vs LIKE behavior.

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: full-text search across standards paragraphs and audit/ethics/external standards. It partially distinguishes from siblings by routing 'paragraph' results to get_paragraph and 'assure'/'ext_std' results to get_material, but it does not compare itself explicitly against search_materials, search_qnas, or list_standards.

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?

It gives concrete usage examples and explains when to narrow by category or std_num, including the warning to confirm category/std_title fits the entity. Alternatives are named only as follow-up retrieval tools, not as alternative search tools, so the when-not-to-use guidance is incomplete.

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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