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텍스트 요약 AI

text_summary
Read-only

Summarize a long text (up to 100,000 characters) into a concise Korean summary. 입력 텍스트(최대 10만 자)의 핵심 내용을 간결하고 정확하게 요약합니다. 모델·파라미터는 서버가 고정하며 빠른 응답에 최적화되어 있습니다. 요청당 기본 100포인트이며, 사용량 금액(모델별 단가 기준)이 더 크면 그 금액이 차감됩니다. [호출당 100포인트]

Input Schema

NameRequiredDescriptionDefault
textYes요약할 원문 텍스트 (최대 100,000자)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations cover the read-only/non-open-world profile, and the description adds real context beyond them: the model and parameters are server-fixed, responses are optimized for speed, and each call costs a base of 100 points with usage-based billing if higher. That billing disclosure is genuinely useful for agent decision-making. It stops short of stating output format or truncation behavior at the length limit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core capability and limits are front-loaded, but the text is bilingual near-duplication and the pricing statement is repeated twice (base 100 points plus a bracketed '[호출당 100포인트]' tag), which costs space without adding information.

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?

For a single-parameter tool with no output schema, the description covers input limits, output language, server-fixed model config, and cost — the essentials an agent needs before calling. Only error/truncation behavior at the 100k boundary is unaddressed.

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?

With one parameter at 100% schema coverage, the schema already documents `text` and its 100,000-character cap. The description restates the limit and adds the Korean-output requirement, but supplies no new syntax or format meaning for the parameter itself.

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 and resource (summarize a long text) plus distinguishing constraints: a 100,000-character input cap and a Korean-language output. It does not explicitly contrast with near neighbors like text_polish or llm_chat, so the agent must infer the boundary.

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?

Usage is implied by the length ceiling and the 'long text' framing, and the pricing note hints this is a metered call, but there is no explicit when-to-use / when-not or named alternative (e.g., use text_polish to rewrite rather than condense).

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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