lidarr_profiles_formats

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

With no annotations, the description carries the full burden and does well: it labels DESTRUCTIVE operations ('this deletes data') and WRITE operations ('this modifies your Lidarr instance'). It also clarifies what the body parameter should contain (e.g., 'body carries custom format ids'). It does not cover auth, rate limits, pagination, or error handling, but for a dispatcher tool, it gives essential safety information for each action.

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 long but efficiently structured as a bulleted list. The initial instruction is front-loaded, and each operation is described in a single, dense line. No wasted words: the details (e.g., DESTRUCTIVE/WRITE flags, parameter names) are relevant and precisely formatted. The length is proportionate to the 26 operations being documented.

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 multi-operation dispatcher, the description is highly complete: it documents every operation, marks read vs. write vs. destructive behavior, and lists parameters. It does not describe return values or error handling, but the presence of an output schema (as indicated in context) reduces the need to explain return formats. Overall, it gives an agent enough context to select and invoke any listed operation correctly.

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?

The schema only defines 'operation' (enum) and a generic 'arguments' dict, offering minimal guidance. The description compensates by providing per-operation Python-style signatures (e.g., 'lidarr_delete_customformat(id)', 'lidarr_update_customformat(id, body={})') and explaining what body should carry (list of resources, ids, etc.). This adds significant meaning beyond the raw schema, making parameter usage clear for every operation.

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 that this tool performs 'profiles formats operations on Lidarr' and enumerates all supported operations (e.g., lidarr_create_customformat, lidarr_delete_qualityprofile). It makes the dispatcher nature explicit with 'Pass operation and an arguments dict'. While it doesn't explicitly contrast with sibling tools, the operation list distinctively scopes it to profiles/formats management, which is clear enough.

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 a clear usage pattern ('Pass operation and an arguments dict matching that operation's parameters') and each operation lists its parameters. However, it does not explicitly state when to prefer this tool over the sibling tools (e.g., for config, tags, etc.). The intended usage is implied by the operation names, but there is no direct exclusion or alternative guidance.

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