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martin-gomola

Spotify MCP Server

compareTrackAnalysis

Read-onlyIdempotent

Compare exact Spotify track IDs across audio-analysis providers to identify missing data, half/double-time conflicts, and provider failures, including field-level provenance, without altering Spotify.

Instructions

Compare exact Spotify track IDs across available audio-analysis providers. Reports field-level provenance, missing providers, half/double-time-aware conflicts, and provider failures without changing Spotify.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trackIdsYes
providersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tracksYes
warningsYes
requestedTrackIdsYes
requestedProvidersYes
Behavior5/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, and the description reinforces this with 'without changing Spotify.' It adds valuable behavioral details beyond annotations: field-level provenance, missing providers, half/double-time-aware conflicts, and provider failures. No contradiction exists.

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 a single, front-loaded sentence that wastes no words. It states the action, the resource, the output highlights, and the safety guarantee all in one compact sentence.

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?

Given the rich annotations, an output schema, and a simple two-parameter input, the description covers the core purpose and important behavioral nuances (provenance, missing providers, conflicts, failures). It lacks explicit usage prerequisites or alternative-tool guidance, but these are minor gaps because the schema and annotations already convey structural and safety information.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the two parameters. It only says 'track IDs' and 'audio-analysis providers' at a high level, omitting parameter names, required status, array constraints, provider enum values, and defaults. The agent gets little semantic help beyond the schema's property names and types.

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 begins with a specific verb and object: 'Compare exact Spotify track IDs across available audio-analysis providers.' It clearly distinguishes this tool from siblings like getTrackAudioFeatures or analyzeDjPlaylist by focusing on cross-provider comparison and reporting provenance/conflicts.

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?

The description makes obvious that this tool is for comparing the same track IDs across multiple audio-analysis providers, and the phrase 'without changing Spotify' signals a safe read-only context. It does not explicitly name alternatives or when not to use it, but the intended use case is clear enough.

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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