lidarr_queue

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 clearly marks destructive operations with 'DESTRUCTIVE: this deletes data' and write operations with 'WRITE: this modifies your Lidarr instance.' It also provides behavioral nuances such as 'Full download queue with all detail, unpaged' versus 'Paged download queue.' This gives substantial insight into side effects and behavior, though it stops short of discussing error handling or rate limits.

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 appropriately structured as a bulleted list of sub-operations. Each line is concise and action-focused, earning its place. A minor improvement would be grouping read vs write operations, but the current structure is scannable and not verbose.

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 the tool's complexity (9 sub-operations, many parameters) and sparse annotation/schema, the description is remarkably complete. It covers all operations, their parameters, side effects, and query params. An output schema exists (per context signals), which presumably documents return values, so the description does not need to explain those. The description gives an agent enough to select and invoke the correct operation.

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 input schema only defines `operation` and a generic `arguments` dict, so the description is the sole source of parameter details. It lists every sub-operation's parameters with defaults and type hints, and adds meaning by noting which are query params ('Query params: blocklist, skip_redownload') and that `body` carries queue item IDs. This fully compensates for the 0% schema coverage.

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 opens with 'lidarr queue operations on Lidarr' and then enumerates nine distinct sub-operations with descriptive names like 'lidarr_get_queue_details' and 'lidarr_delete_queue'. Each operation has a clear verb and resource, and the overall tool is clearly scoped to queue management. This fully distinguishes it from sibling tools covering different Lidarr domains.

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 explains how to use the tool ('Pass `operation` and an `arguments` dict') and lists all operation names, implying when each sub-operation would be used. However, it does not explicitly state when to use this tool versus alternative sibling tools, nor does it provide exclusions or 'if you need X, use Y' guidance. Usage is implied but not fully explicit.

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