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rank_channels_by_topic

Find which channels talk about something the most, ranked by mentions, with how many of their videos mention it. Use it to find who covers a topic: creators to follow, experts, or partners. Same library, caption quirks and dates as search_spoken_words.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "rank_channels_by_topic"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many channels. Default 10.
queryYesA word or short phrase (up to 8 words).
sinceNoOnly captions captured on or after this date, YYYY-MM-DD.
untilNoOnly captions captured on or before this date, YYYY-MM-DD.
also_matchNoOther spellings or mis-hearings to count as the same thing. Up to 5.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior3/5

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

No annotations, so the description carries the burden. It discloses the ranking axis and the per-channel video counts, plus that the corpus/date behavior matches search_spoken_words — but that context is a cross-reference the agent must resolve, and it says nothing about whether results are truncated, cached, or how ties are resolved.

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?

Two short sentences, front-loaded with the ranking semantics and result shape. The trailing 'same library, caption quirks and dates as search_spoken_words' is terse to the point of being cryptic but occupies little space.

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 convey what comes back (channels ranked by mentions with video counts). What is missing is the nature of the underlying corpus (spoken captions), which is only implied through the sibling reference.

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% with all five parameters documented, so baseline is 3. The description adds only an indirect nod to date filtering ('dates as search_spoken_words') and nothing about query phrasing or also_match beyond what the schema already says.

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?

States a specific verb and resource ('find which channels talk about something the most, ranked by mentions') and clarifies the output unit ('how many of their videos mention it'). This is clearly separable from search_spoken_words and rank_videos_by_topic even though only one sibling is named.

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?

Gives explicit positive usage framing: 'Use it to find who covers a topic: creators to follow, experts, or partners.' It does not state when NOT to use it (e.g., use rank_videos_by_topic for per-video ranking), so alternative routing is only implied.

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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