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search_service

Search for music or content within a specified streaming service on a player.

Instructions

Search within a streaming service configured on the player, e.g. search_service(player, "TIDAL", "Miles Davis"). service is matched (case-insensitive, partial) against the top-level source names from browse(). Results carry a play_url (pass to play_item()) or a browse_key (pass to browse(), e.g. to see an album's tracks) depending on the item type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
playerYes
serviceYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description must disclose behavior. It does so by explaining that service matching is case-insensitive and partial, and that results carry either a play_url or browse_key depending on item type. It does not mention error cases (e.g., service not configured) or confirm read-only nature, but the provided details cover key usage behaviors.

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?

The description is concise, using two sentences to convey purpose, example, matching behavior, and result handling. It is front-loaded with the primary action and includes a practical example, avoiding unnecessary fluff. The structure is efficient and easy to parse.

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?

For a search tool with three parameters and an output schema, the description covers essential aspects: what to do with results, how service is matched, and a reference to browse() for available services. It does not explicitly mention the source of the player parameter or error handling, but it provides enough for correct invocation in most scenarios. The existence of an output schema reduces the need to describe return values in detail.

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 coverage is 0%, so the description must explain all parameters. The example search_service(player, "TIDAL", "Miles Davis") clarifies the order and gives a sense of each parameter, and service matching is explained. However, it does not explain how to obtain a valid player identifier (e.g., from list_players) or what format the query should take, leaving some ambiguity.

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 clearly states the tool searches within a streaming service on a player, provides a concrete example, and differentiates itself from browse() and play_item() by explaining how results are used. The verb 'search' and resource 'service' are specific, making the purpose unambiguous.

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?

It gives a clear use case with an example and explains how to handle results (pass to play_item or browse). It implies the service names come from browse(), which suggests a workflow, but does not explicitly state when to use this tool versus alternatives like browse. Still, the context is strong enough for an agent to decide correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.