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Suggest emphasis

suggest_emphasis
Read-only

PROJECT-SCOPED: this call acts only on the explicit project_id and returns the project identity with its result. READ: candidate emphasis words from the REAL transcript — the most vocally stressed words (measured), words with digits, and rare/distinctive words — as a verbatim list to pass to add_captions / set_caption_style emphasis_words.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesRequired immutable scope for this call. Copy the id from list_projects/open_project/project_state; the active-project pointer is never used to guess.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds value by detailing the read behavior (returns project identity with result) and the types of words returned. It also explicitly states it reads from the REAL transcript, providing transparency beyond 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 a single sentence but packs essential information: scope, action, criteria, and output destination. It is front-loaded with 'PROJECT-SCOPED' and 'READ'. It is concise yet complete for the tool's simplicity.

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 tool with one parameter, no output schema, and annotations covering safety, the description sufficiently explains what the tool returns and how to use it. It even names the downstream tools, making it complete for an agent to invoke correctly.

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 parameter description already explains project_id as immutable scope and how to obtain it. The tool description reinforces this with 'PROJECT-SCOPED' but does not add new semantic meaning beyond what the schema provides. Baseline 3 is appropriate.

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 states a clear purpose: it reads candidate emphasis words from the transcript and returns them as a verbatim list. It specifies the resource (REAL transcript), the criteria (vocally stressed, digits, rare/distinctive), and the downstream use (add_captions/set_caption_style). This is specific and distinguishes it from other tools.

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?

The description implies when to use it: when you need emphasis words to pass to captioning tools. It does not explicitly mention alternatives or when not to use it, but the context is clear enough. It also notes project-scoping, which helps the agent avoid misuse.

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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