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Glama
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LINE WORKS AiNote (unofficial)

get_note_summary

Retrieve AI-generated summary and participant list for a meeting note. Use this to quickly grasp note contents when summaries exist; fall back to full transcript if summary is unavailable.

Instructions

ノートの AI 要約と参加者を取得する。文字起こし全文は含まない。

ノートの内容を知りたい場合はまずこれを使う。要約で足りない場合にのみ
get_note_transcript で全文を取得する。transcriptBlocks は文字起こしの
発言ブロック数で、全文を取る際の max_blocks の目安になる。

要約はノートの作成者が AiNote 上でテンプレートを選んで生成するもの。
summaries が空の場合は作成者が要約を生成していないので、内容を知るには
get_note_transcript で全文を読む。

Args:
    note_id: ノートID。list_notes または search_notes の結果から得る。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
note_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are present, so the description carries the full burden. It discloses that the tool returns only summary/participants, not the transcript, and that summaries may be empty depending on whether the creator generated them. It also explains transcriptBlocks as a hint for max_blocks. It doesn't mention idempotency or rate limits, but for a read-only lookup these are less critical. It adds meaningful behavioral context beyond the schema.

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 organized into short paragraphs: purpose, usage routing, caveat about empty summaries, and an Args block. Every sentence contributes to correct selection or invocation, with no fluff. It's slightly longer than average but justified by the routing and fallback logic.

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?

The tool has an output schema, so return fields are documented elsewhere. The description covers the essential contextual caveats: when summaries might be empty, when to switch to get_note_transcript, and how transcriptBlocks relates to the transcript tool. For a one-parameter get operation, this is sufficiently complete.

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?

The input schema gives no description for note_id (0% coverage), but the description compensates by stating that note_id is obtained from the results of list_notes or search_notes. This gives the agent a reliable source for the parameter value. It doesn't specify format, but the provenance hint is valuable and actionable.

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 begins with a specific verb and resource: 'get the AI summary and participants of a note.' It explicitly states what is not included (full transcript), distinguishing it from the sibling get_note_transcript. An agent can immediately tell this tool's purpose apart from its siblings.

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 description gives explicit routing: use this first to know note content, and only call get_note_transcript when the summary is insufficient. It also explains that if summaries is empty, the transcript is the fallback. This is textbook when-to-use/when-not-to-use guidance.

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