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cueprecise_register

Registers a YouTube video and executes the analysis pipeline, with optional stages to re-run specific steps.

Instructions

YouTube 영상을 등록하고 분석 파이프라인을 실행한다. stages 를 주면 일부 단계만 재실행한다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube URL 또는 video_id
stagesNo생략하면 기본(fetch, plan, transcribe, assemble, merge, chapters, visual, index). 전체는 ["all"]. 가능: fetch, plan, transcribe, assemble, merge, chapters, render, visual, index
languageNo쉼표 구분 BCP-47. 생략하면 자동 감지

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.5

TDQS

A3.6/5.0
Behavior3/5

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

There are no annotations provided, so the description must carry the full burden. It indicates a state-changing action ('registers' and 'runs pipeline') but does not detail side effects such as network calls, storage modifications, or potential destructive actions. It is moderately transparent but lacks explicit side-effect disclosure.

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

Conciseness5/5

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

The description is concise, consisting of two short sentences. It front-loads the primary purpose and then adds a note about the optional 'stages' parameter. Every word serves a purpose, with no redundancy or irrelevant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core action and the key parameter behavior, but it omits information about return values, error handling, or whether the analysis pipeline is synchronous or asynchronous. Given the absence of an output schema, this missing context could leave an agent unsure about what to expect after calling the tool.

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 schema provides 100% coverage and the description adds meaningful details. For 'stages', it explains the default list and the 'all' option. For 'language', it specifies the format (comma-separated BCP-47) and default behavior. This goes beyond simple labels, though the description doesn't elaborate on the exact meaning of each stage.

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 clearly states the tool's purpose: registering a YouTube video and running the analysis pipeline. It uses a specific verb ('registers') and resource ('YouTube video'), which distinguishes it from siblings like 'cueprecise_status' or 'cueprecise_excerpt', though it does not explicitly name alternatives.

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 mentions that providing 'stages' allows re-running only some steps, which gives a hint about the optional parameter. However, it does not explicitly state when to use this tool versus other sibling tools, nor does it describe any prerequisites or scenarios where this tool is preferred.

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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