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explicit_content_ratio

Analyze your saved Spotify tracks to reveal the percentage flagged explicit and list top explicit artists.

Instructions

Share of your saved tracks flagged explicit, with the top explicit artists. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scan_capNoMax saved items to walk per paginated source (default: SPOTIFY_MCP_FETCH_ALL_CAP)
max_resultsNoMax items to return (default: SPOTIFY_MCP_MAX_ITEMS env or 50)
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
Behavior3/5

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

No annotations are present, so the description carries the full burden of safety and side-effect disclosure. It does state 'Read-only,' which is a meaningful behavioral claim. However, it does not disclose that computing the ratio may walk a large number of saved tracks (relevant given scan_cap), how the explicit flag is determined, or whether the share is based on the entire library or just the scanned subset.

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 extremely concise: a single sentence plus the read-only note. It is front-loaded with the core metric and source, and every word earns its place. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives a decent high-level picture and the schema covers parameters, but there is no output schema and the description does not clarify key semantic details: whether the ratio denominator is all saved tracks or only those scanned, how 'top explicit artists' is ranked, or how response_format affects the output. These gaps could lead to incorrect interpretation of the result.

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%; all three parameters (scan_cap, max_results, response_format) already have meaningful descriptions in the schema. The tool description adds no parameter-level information beyond what the schema provides, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's function: computing the share of a user's saved tracks flagged explicit and surfacing the top explicit artists. It names the data source ('your saved tracks') and the kind of output. It is specific enough to distinguish from many siblings, though it doesn't explicitly differentiate itself from other library-analytics tools.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like listening_report, library_genre_report, or other saved-track analytics. The only additional note is 'Read-only,' which is a safety signal rather than usage direction. There is no mention of prerequisites, library size considerations, or cases where another tool would be better.

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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