Your Spotify MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool returns (artist's position and percentile ranking) but doesn't mention important behavioral aspects like whether it requires authentication, rate limits, data freshness, or how it handles artists not in the listening history. The example queries add some context but leave gaps in operational transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly structured and concise. The first two sentences clearly state the purpose and what information is returned. The three example queries are highly relevant and illustrative without being redundant. Every sentence earns its place and the information is front-loaded effectively.

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

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

For a read-only ranking tool with no output schema, the description provides good context about what information is returned (position and percentile). However, without annotations and with no output schema, it could benefit from more detail about the return format (e.g., numeric position, percentile as percentage, possible error cases). The examples help but don't fully compensate for the lack of structured output documentation.

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

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

Schema description coverage is 100%, with all parameters well-documented in the schema itself. The description doesn't add any parameter-specific information beyond what's in the schema (artist_id as Spotify ID/URI, date formats). It mentions 'listening history' which aligns with the date parameters but doesn't provide additional semantic context. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description clearly states the tool's purpose with specific verbs ('find where', 'shows') and resources ('artist', 'listening history', 'position among all artists', 'percentile ranking'). It distinguishes from siblings like get_artist_stats (which likely provides different metrics) and get_top_artists (which lists top artists rather than ranking a specific one).

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

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

The description provides clear context through example queries that show when to use this tool ('Where does Radiohead rank in my listening?', 'Is Taylor Swift in my top 10?', 'What's my percentile for The Beatles?'). However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools, though the examples imply it's for ranking individual artists rather than getting lists or other analyses.

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