Skip to main content
Glama

Analyze a track

analyze_track
Read-only

Measure integrated loudness, sample peak, duration, sample rate, and stereo correlation of an audio file to select the appropriate mastering preset. Get quick technical stats before processing.

Instructions

Measure integrated LUFS, sample peak, duration, sample rate and stereo correlation without processing. Free, a couple of seconds. Run this before choosing a preset. Note: true peak and loudness range are NOT part of this fast pass — they are measured on the result and come back from get_job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_urlYesPublic https URL of the audio file (wav/mp3/flac/m4a).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
lufsNo
channelsNo
peak_dbfsNo
sample_rateNo
duration_secNo
true_peak_dbNonull in the fast pass; see get_job for the measured value
genre_suggestionNo
stereo_correlationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces the 'without processing' behavior. It also adds valuable context: the tool is free, takes only a couple of seconds, and does not measure true peak and loudness range. While annotations cover safety, the description adds nuance about scope and latency, though it doesn't detail output format beyond the output schema.

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?

Three sentences with zero wasted words. The tool's purpose and key behavioral scoping are front-loaded, and the caveat about true peak/loudness range is efficiently placed at the end.

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 simple, read-only, single-parameter tool with an output schema, the description covers purpose, usage timing, scoping limits, and cost/speed. The note about get_job also routes the agent to the correct sibling for missing measurements. Nothing essential 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 coverage is 100% and the single parameter is fully documented in the schema ('Public https URL of the audio file (wav/mp3/flac/m4a)'). The description doesn't add parameter-level details beyond what the schema provides, so baseline 3 is appropriate.

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+resource combination: 'Measure integrated LUFS, sample peak, duration, sample rate and stereo correlation without processing.' It clearly distinguishes analyze_track from master_track by explicitly noting it does not process the audio.

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?

The description explicitly instructs when to use this tool ('Run this before choosing a preset') and provides an exclusion by noting what is NOT measured in this fast pass and that those metrics come from get_job. This gives clear context for selecting analyze_track versus alternatives.

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