get_recommendations

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds behavioral context about the scoring algorithm (analyzes genres, directors, actors) and conditional Trakt rating profile usage, which goes beyond what annotations provide.

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 composed of four short sentences, each adding substantive detail about the tool's purpose, algorithm, per-user capability, and Trakt integration. It is front-loaded with the core purpose and contains no filler, though it is slightly more verbose than the minimal two-sentence ideal.

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 recommendation tool, the description covers what it does, how it works, and when user-specific behavior applies. It omits explicit return format details, but that is not critical given the simple list output implied by 'recommendations' and the absence of an output schema.

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 coverage is 100% with each parameter individually described, so the description adds minimal parameter-specific meaning. The 'per-user' mention aligns with the userId parameter but doesn't offer new syntax or formatting details beyond the schema.

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 function: retrieving personalized movie recommendations from the user's Plex library. It distinguishes itself from siblings like search_media or get_recently_watched by specifying the recommendation logic (watch history, genres, directors, actors) and per-user support.

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 implies usage for personalized recommendation requests, referencing watch history and optional Trakt integration for rating refinement. It does not explicitly name alternatives or exclusion criteria, but the context is unambiguous and no conflicting use cases are suggested.

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