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Identify a song from an audio URL

recognize_song_from_url

Use this when the user wants to know which song is in an audio or video file at a public URL (a direct link to the file, such as an .mp3). Only the first 12 seconds of the audio are analyzed, so it returns at most one song. Returns the artist, title, album, release date, label and a song link, plus optional links to the track on Apple Music, Spotify, Deezer or MusicBrainz. Each call counts against the account's request quota, like a direct API call, and a retry counts again; on paid plans, requests beyond the plan's included allowance are billed at the plan's rate at the end of the billing period. Do not use for lyrics or to find several songs in a long recording.

Input Schema

NameRequiredDescriptionDefault
urlYesPublic http(s) URL of the audio or video file
marketNoOptional two-letter country code for Apple Music and Spotify results (default us)
returnNoOptional services to include links for

Output Schema

NameRequiredDescriptionDefault
songYes
matchedYesfalse when the audio was processed but no song matched

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only provide generic hints (readOnlyHint=false, openWorldHint=true). The description adds substantial non-obvious behavior: only the first 12 seconds are analyzed, at most one song is returned, each call consumes quota, retries count again, and overage is billed on paid plans. This goes well beyond the structured fields.

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 front-loaded with the primary use case, then constraints, then billing implications, then exclusions. Every sentence carries distinct decision-relevant information with no filler.

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?

For a single-shot recognition tool with full schema coverage, an output schema, and rich annotation context, the description covers when to use it, the analysis limit, quota/billing behavior, and the output contents. Nothing an agent needs to invoke it correctly is missing.

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 the schema already documents url, market, and return (including the default 'us' and the enum of services). The description restates the public-URL requirement and the service links but adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 states a specific verb and resource ('which song is in an audio or video file at a public URL') and clearly distinguishes this from the sibling tools, which are all account/stream/billing management. An agent can identify the function 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 Guidelines5/5

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

It gives explicit positive guidance ('Use this when the user wants to know which song is in an audio or video file at a public URL') and explicit exclusions ('Do not use for lyrics or to find several songs in a long recording'). Both the trigger condition and the anti-patterns are named.

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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