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build_minutes_prompt

Read-onlyIdempotent

Builds a structured prompt combining meeting notes with standard templates, including optional line-number citations, to guide accurate meeting minute writing.

Instructions

회의 메모와 표준 템플릿을 결합한 회의록 작성 프롬프트를 반환합니다.

이 MCP는 LLM API를 호출하지 않습니다. 요약은 호스트(Claude/Codex)가 하고, 이 도구는 '무엇을 어떤 형식으로 쓸지'에 대한 지시문만 조립합니다.

Args: note_id: 메모 id. with_line_numbers: 원문 줄 번호 부착 및 인용 규칙 추가 여부 (기본 True).

Returns: PromptResponse: prompt에 규칙 + 템플릿 + 원문이 담긴 지시문.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
note_idYes메모 id
with_line_numbersNoTrue면 원문에 줄 번호를 붙이고, 근거 칸에 'L14' 형태로 인용하도록 규칙을 추가합니다.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
stageYes회의록 워크플로에서 지금 위치한 단계
promptYes
statusYes이 호출의 결과 상태
note_idYes
next_actionsNo이어서 호출하면 좋은 도구 목록
Behavior4/5

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

Annotations already convey readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds meaningful context on top: the tool makes no external API calls and performs pure instruction assembly. This is genuinely informative behavior disclosure beyond the structured hints, and it does not contradict the annotations.

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-organized into a functional summary, a behavioral note, and labeled Args/Returns sections. It is efficiently written with no redundant sentences, and the key behavioral fact (no LLM call) is front-loaded. Slightly more compact phrasing is possible, but the structure is clean and scannable.

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?

Given an output schema exists for PromptResponse, the return format is already documented externally. The description notes the prompt contains rules + template + original text. Both parameters are covered by the schema, and annotations carry the safety profile. Nothing an agent needs to invoke this correctly appears to be missing for a tool of this simplicity.

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%; both note_id and with_line_numbers are already well-described in the schema, including the 'L14' citation-format detail. The description only briefly restates the parameters without adding new meaning. With full schema coverage, the baseline of 3 applies — the description contributes little beyond what the schema provides.

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+resource: 'returns a minutes-writing prompt combining meeting notes and standard template'. It also clarifies the tool is not an LLM API caller, only an instruction assembler, which further sharpens the purpose. It doesn't explicitly name a sibling it is not, but the function is distinct enough among the listed siblings (all list/read/extract/validate/save operations).

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

Usage Guidelines3/5

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

The description explains the division of labor ('summarization is done by the host; this tool only assembles instructions'), which implies when it should be used — as a prompt-preparation step before host-side summarization. However, it never explicitly says 'use this instead of X' or 'do not use when Y', and it names no alternative. The usage context is implied rather than stated.

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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