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DropTrack Create Audio Analysis Upload

droptrack_create_audio_analysis_upload

Create an authenticated short-lived S3 upload URL for a WAV, MP3, AIF, or AIFF file, enforcing track/version plan limits before upload.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trackIdNoExisting DropTrack track ID when the upload will become a new track version
fileNameYesOriginal audio filename, such as song.wav or demo.aiff
contentTypeNoAudio MIME type, such as audio/wav, audio/mpeg, or audio/aiff
fileSizeBytesNoOptional client-side file size for validation

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoStructured DropTrack result returned by this tool

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Beyond the annotations, the description adds valuable behavioral context: the URL is authenticated and short-lived, plan limits are enforced before upload, and allowed file formats are specified. It also clarifies that the tool creates a URL rather than performing the actual upload. No contradictions with annotations.

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 sentence, front-loaded with the core action, followed by key constraints. Every phrase carries meaning; there is no filler or redundancy.

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?

The description is complete enough for calling the tool: it states the purpose, accepted file types, and key constraints, and an output schema exists to document return values. Minor gaps remain around the specifics of plan-limit enforcement and the exact lifetime of the URL, but these are not required to make the call.

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 fully documents the parameters. The description adds contextual framing around audio file upload and plan-limit enforcement, but it does not add per-parameter meaning beyond what the schema already provides. 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 action ('Create'), a specific resource ('authenticated short-lived S3 upload URL'), and a precise scope (WAV, MP3, AIF, or AIFF files). It clearly distinguishes itself from analysis or download siblings by focusing on creating an upload URL rather than performing analysis or retrieval.

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

Usage Guidelines3/5

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

The description implies when to use this tool: when an audio file needs an S3 upload URL before analysis/upload. It names no alternatives, exclusions, or explicit conditions for choosing a sibling tool, leaving some inference to the agent.

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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TDQS

B3.4/5.0
Disambiguation3/5

Most tools target distinct resources and actions, but several clusters are easy to confuse: get_track_analysis vs get_track_analytics vs get_track_tags, plus analyze_audio/request_track_tagging/auto_tag_tracks overlap in the audio-analysis/tagging space. The descriptions do help separate them, so careful agents can disambiguate, but the naming alone creates real misselection risk.

Naming Consistency4/5

All tools share the droptrack_ prefix, use snake_case, and follow a verb-first noun pattern, with list for collections and get for single items. Minor inconsistencies exist—add_contact vs create_contact_list, browse vs list, auto_tag_tracks—but the overall convention is predictable and readable.

Tool Count2/5

At 55 tools this is far beyond the recommended 3-15 range and well over the 25+ threshold. Many tools are near variants of each other, especially company-level vs label-level ads, analytics, and wallet tools, inflating the surface area and making selection harder.

Completeness3/5

The set covers many domains and some workflows are complete, such as album art generation/polling/acceptance/deletion and track tagging request/poll/apply. However, core lifecycle gaps remain: no update or delete for campaigns, contacts, or contact lists, no playlist mutation tools, and AI press-release/bio workflows end at polling without a save or publish step.