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LingoDew

Find learning videos

find_videos
Read-only

Find real YouTube videos on LingoDew for learning Japanese or English, filtered by difficulty level (JLPT N5–N1 for Japanese, CEFR A1–C2 for English), topic and keywords. Returns titles, channels, levels and links to LingoDew video pages with tappable subtitles.

Input Schema

NameRequiredDescriptionDefault
levelNoJLPT level (N5, N4, N3, N2, N1) for Japanese, CEFR level (A1–C2) for English.
limitNo
queryNoWords to match in the video title or channel name.
topicNoTopic name, e.g. "Food", "Travel", "Daily Life".
languageYesThe language being learned.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, non-destructive and openWorldHint=false; the description usefully reinforces the closed-world nature by saying videos are 'on LingoDew' rather than a live web search, and it discloses the return shape (titles, channels, levels, links, tappable subtitles). It omits any mention of result-count limits or empty-result behavior, keeping it short of a 5.

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?

Two compact sentences with zero filler: filters first, return contents second. Every clause (language, level scale, topic, keywords, return fields) carries information an agent can act on.

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?

With no output schema, the description does the job of explaining return values and covers all filter dimensions, so an agent can call it correctly. The only gap is the limit parameter (default 10, max 25) and pagination/truncation behavior, which is invisible in the description.

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 80%, so level/query/topic/language are already documented in the schema, and the description mostly restates the same level-to-framework mapping (JLPT N5–N1, CEFR A1–C2). The 3-parameter baseline applies; nothing new about limit or matching semantics is added.

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?

States a specific verb ('Find') and resource ('real YouTube videos on LingoDew') with the exact filter dimensions (level, topic, keywords). It is clear about what the tool returns, though it never explicitly differentiates itself from siblings like word_in_videos or channel_stats — the distinction is only implied by the resource.

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 described filters (level/topic/keywords for a language-learning search), but there is no explicit statement of when to prefer this over word_in_videos or channel_stats, and no mention of prerequisites or when not to use it.

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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