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Trending

trending
Read-onlyIdempotent

Get trending podcasts across the open podcast database, ranked by recent activity. Optionally filter by language or category. Returns podcast title, author, categories, artwork, and trend score. Example: trending({ max: 10, lang: "en", cat: "Technology" })

Input Schema

NameRequiredDescriptionDefault
catNoOptional category filter, e.g. "Technology", "News"
maxNoMaximum number of trending podcasts to return (default 10, max 40)
langNoOptional language filter, e.g. "en", "es"
_apiKeyNoOptional — your own Podcast Index credentials as KEY:SECRET for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "_apiKey": "your-podcastindex-api-key",
      -    "cat": "Technology",
      -    "lang": "en",
      -    "max": 10
      -  },
      -  {
      -    "_apiKey": "your-podcastindex-api-key",
      -    "max": 20
      -  }
      -]New value: +[
      +  {
      +    "cat": "Technology",
      +    "lang": "en",
      +    "max": 10
      +  },
      +  {
      +    "max": 20
      +  }
      +]
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "_apiKey": "your-podcastindex-api-key",
      +    "cat": "Technology",
      +    "lang": "en",
      +    "max": 10
      +  },
      +  {
      +    "_apiKey": "your-podcastindex-api-key",
      +    "max": 20
      +  }
      +]
  3. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered before the description says anything. The description adds genuine value by naming the ranking signal ('recent activity') and enumerating returned fields, but it says nothing about rate limits, pagination, empty-result behavior, or the credential/limit implications of _apiKey beyond what the schema documents.

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?

Four short sentences, front-loaded with the purpose and ranking basis, then filters, then return shape, then an example. Zero filler, though the example sentence is largely redundant given the schema's examples array and could be dropped.

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?

There is no output schema, so the description's listing of return fields (title, author, categories, artwork, trend score) is doing necessary work an agent otherwise could not know. Defaults, bounds and credential handling live in the schema. The only real gap is the absence of routing guidance against the many podcast-related siblings.

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%, so every parameter already carries its own description including the default 10 / max 40 bound and the KEY:SECRET form of _apiKey. The description's filter restatement and inline example duplicate the schema's own examples, adding no new meaning (it does not clarify category matching semantics or accepted language codes).

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 opens with a concrete verb-and-resource pair ('Get trending podcasts') and adds the ranking basis ('ranked by recent activity'), which is the property that separates this from search_podcasts or episodes. An agent can tell this is a browse/rank operation rather than a query operation without opening the schema.

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?

It states the optional filters ('Optionally filter by language or category') but never says when to choose this over search_podcasts or pipeworx_trending, nor any exclusion or prerequisite. Usage is implied by the word 'trending' rather than stated, so the agent must infer the routing decision.

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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