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kaiding-ucb

podcast-summarizer-mcp

by kaiding-ucb

search_youtube_channels

Find YouTube channels matching a free-text query. Returns ranked candidates with channel IDs and confidence scores for channel identification.

Instructions

Search YouTube for channels matching a free-text query.

Use this when the user names a channel ("Forward Guidance", "All-In podcast") or describes one ("a good macro investing channel") and you need to identify candidate channels before adding to the registry.

No YouTube API key required — uses yt-dlp scraping under the hood.

Args: query: Free-text search term, e.g. "Forward Guidance" or "macro investing". max_results: How many distinct channels to return, ranked by relevance (default 5).

Returns: { "candidates": [ { "channel_id", "name", "channel_url", "hit_count", "confidence_score" }, ... ] } Empty list if nothing matches. Subscriber count + recent videos are NOT populated here — call get_channel_metadata(channel_id) for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_resultsNo
Behavior5/5

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

Discloses that no YouTube API key is required, uses yt-dlp scraping, and specifies what data is not populated in the results.

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?

Well-structured, concise paragraphs with Args section; every sentence adds unique value without redundancy.

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

Completeness5/5

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

Includes return format with field names, empty list case, and references get_channel_metadata for missing data, compensating for lack of output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Adds meaningful context to both parameters: query with example values, max_results with description of ranking and default, despite schema having 0% coverage.

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?

Description clearly states 'Search YouTube for channels matching a free-text query' with specific examples of use cases, and distinguishes from sibling tools like get_channel_metadata.

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?

Explicitly says when to use (when user names or describes a channel before adding to registry) and what not to expect (subscriber count, recent videos) with pointer to sibling tool.

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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