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get_show

Retrieve detailed information about a specific podcast show using its Spotify ID, including metadata such as name, publisher, and episode count. Supports optional market and response format parameters to tailor the output.

Instructions

Get full details for a podcast show

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesSpotify show ID
marketNoISO 3166-1 alpha-2 country code
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.26.1
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / market / pattern
      Added value: +"^[A-Za-z]{2}$"
    • addedInput schema / properties / response_format
      Added value: +{
      +  "default": "concise",
      +  "description": "'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API object",
      +  "enum": [
      +    "concise",
      +    "detailed",
      +    "json"
      +  ],
      +  "type": "string"
      +}
  2. First observedv1.0.1

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only promises 'full details' without explaining what fields are included, how market affects results, error behavior, or the shape of the returned data. The response_format parameter is documented in the schema, but the description adds no behavioral context.

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 a single focused sentence with no filler. It front-loads the action and resource, making it easy to parse quickly.

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 tool is a simple lookup with three parameters, and the schema covers all parameter semantics. However, with no output schema and no behavioral detail, 'full details' is vague and the agent cannot fully anticipate the return structure or how response_format changes the result. It is minimally viable but has clear gaps.

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?

All three parameters have complete schema descriptions, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides, but it does not need to compensate for missing schema coverage.

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 states a specific verb and resource: 'Get full details for a podcast show.' It clearly identifies the tool's purpose, though it does not explicitly distinguish itself from closely named siblings like get_show_details or get_show_episodes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives. The description does not mention related tools such as get_show_details, get_show_episodes, or list_show_episodes, leaving the agent to infer the correct choice from the name alone.

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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