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add_my_writing

Adds a user-written text sample to teach an AI the user's Korean writing style, optionally tagging its kind, title, or style set for later style guides and draft checks.

Instructions

사용자가 직접 쓴 글 한 편을 넣는다. 종류를 비우면 짐작하고, 확실하지 않으면 「종류 미정」 으로 둔다(전체 문체에는 늘 들어감).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo글 종류 아이디나 이름(list_writing_kinds). 예: blog-info, 후기, 공지, 이메일, 논문. 모르면 비워 두세요.
textYes사용자가 직접 쓴 글 본문(100자 이상). 남의 글은 넣지 않습니다.
styleNo문체 묶음 이름. 보통은 비워 두세요(「기본」). 회사용 · 개인 블로그용처럼 따로 둘 때만 씁니다. 글 종류(블로그 · 공지 …)는 style 이 아니라 kind 로 나눕니다.기본
titleNo글 제목(없으면 비움)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=false). The description adds one genuine behavioral fact not in the annotations or schema: an empty 'kind' triggers inference, falling back to a '종류 미정' bucket that is always folded into the overall style. It does not cover failure modes, deduplication, or what the write returns.

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?

Two short sentences, front-loaded with the core action and followed by the one non-obvious default rule. No filler, though the parenthetical about the overall style is slightly compressed and could be clearer.

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?

An output schema exists, so return values need no explanation, and all four parameters are fully documented in the schema. The description supplies the remaining non-obvious rule (kind inference fallback), leaving only minor gaps like duplicate handling.

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 already explains kind, style, and text thoroughly (including pointing at list_writing_kinds and the kind-vs-style distinction). The description only restates the kind default behavior, so it adds little beyond the structured field — baseline 3.

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 names a specific verb+resource ('사용자가 직접 쓴 글 한 편을 넣는다' — adds one self-written piece), which clearly separates it from read_my_writing/list_my_writings/remove_my_writing siblings. It stops short of explicitly naming any sibling, but the action is unambiguous.

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?

It gives useful in-the-moment guidance about the 'kind' field ('비우면 짐작하고, 확실하지 않으면 「종류 미정」') but never states when this tool should be chosen over alternatives such as import_my_naver_blog or set_writing_kind. Usage context is implied by the domain rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.