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Songbrain

Analyse a song from a URL

analyze_song

Start the analysis of a song at a public audio URL (MP3, WAV, FLAC, M4A, AAC, OGG or AIFF; 30 s to 10 min). Needs an API key on the MCP connection. Returns a song_id; poll get_song until status is 'done' (typically 60–90 seconds, up to ~2 minutes when busy). Uses one free song or 25 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNo
artistNo
lyricsNoOptional: the song's lyrics as plain text. Used for the exact words (timings still come from the audio).
audio_urlYesPublic http(s) URL of the audio file

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / lyrics
      Added value: +{
      +  "description": "Optional: the song's lyrics as plain text. Used for the exact words (timings still come from the audio).",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=false and openWorldHint=true; the description goes well beyond them by disclosing the API-key requirement on the connection, the async song_id return, the 60–90 s (up to ~2 min) completion window, and the cost model (one free song or 25 credits). These are the behavioral facts an agent needs to plan and to warn a user about billing, none of which are in 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?

A single dense passage, front-loaded with the action and the required input, followed by format/length constraints, then auth, then the async follow-up and cost. No sentence is redundant and nothing is buried.

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?

There is no output schema, so the description carries the return contract itself — a song_id plus the polling instruction and status lifecycle — and it also covers auth and cost. For a 4-parameter async job-start tool, an agent has everything needed to call it and handle the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% and the schema describes audio_url only as 'Public http(s) URL'. The description adds real meaning to that required parameter: accepted formats (MP3, WAV, FLAC, M4A, AAC, OGG, AIFF) and a 30 s–10 min duration bound. Title/artist remain undocumented in both places, which keeps it below a 5.

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 ('Start the analysis of a song at a public audio URL') and immediately distinguishes itself from the sibling get_song by framing itself as the initiator and get_song as the poller. An agent can tell what it does and where it sits in the workflow without opening a schema.

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?

Explicitly routes the agent forward: 'Returns a song_id; poll get_song until status is done', and clarifies the async nature and expected wait. It doesn't mention when NOT to use it or any alternative analysis path (e.g., the example-analysis siblings), so it stops short of full when/when-not guidance.

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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