Last.fm MCP Server

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

No annotations are provided, so the description carries full burden. It mentions the tool 'Returns: Formatted list of similar tracks' but lacks critical behavioral details: what 'similar' means (e.g., based on audio features, user listening patterns), whether it requires authentication (unclear from context), rate limits, or error handling. The description is minimal beyond basic input-output.

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 well-structured and concise: a one-sentence purpose statement followed by clearly labeled 'Args' and 'Returns' sections. Every sentence earns its place by providing essential information without redundancy. It's front-loaded with the core functionality.

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?

Given no annotations and an output schema (implied by 'Returns'), the description is moderately complete. It covers parameters well but lacks behavioral context (e.g., how similarity is determined, authentication needs). The output schema existence means the description needn't detail return values, but for a recommendation tool with no annotations, more operational guidance would be helpful.

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 0%, so the description must compensate. It provides clear semantics for all 5 parameters in the 'Args' section, explaining what each parameter represents (e.g., 'mbid: Optional MBID (MusicBrainz ID) of the track', 'limit: Maximum number of similar tracks to return (1-30, default: 10)'). This adds significant value beyond the bare schema, though it doesn't detail format constraints (e.g., MBID format).

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: 'Find tracks similar to a given track' - a specific verb ('Find') and resource ('tracks similar to a given track'). It distinguishes from siblings like get_track_info (which retrieves info about a single track) or search_tracks (which searches by query). However, it doesn't explicitly contrast with all similar siblings (e.g., get_artist_top_tracks might also yield related tracks).

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 no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate (e.g., for music recommendation based on a specific track) or when other tools might be better (e.g., get_artist_top_tracks for artist-based recommendations). There's only implicit usage context from the purpose statement.

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