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SavageCore

lidarr-mcp

by SavageCore

lidarr_wanted

Read-only

Retrieve wanted albums from Lidarr: list or fetch missing and cutoff-unmet albums using pagination and filters.

Instructions

lidarr wanted operations on Lidarr. Pass operation and an arguments dict matching that operation's parameters.

  • lidarr_get_wanted_cutoff(id) — Fetch a single cutoff-unmet album by id.

  • lidarr_get_wanted_missing(id) — Fetch a single missing album by id.

  • lidarr_list_wanted_cutoff(page=1, page_size=10, sort_key='', sort_direction='', include_artist=False, monitored=False) — Cutoff-unmet albums page. Query params: page, page_size, sort_key, sort_direction, include_artist, monitored.

  • lidarr_list_wanted_missing(page=1, page_size=10, sort_key='', sort_direction='', include_artist=False, monitored=False) — Missing albums page. Query params: page, page_size, sort_key, sort_direction, include_artist, monitored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNo
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral context: single-item fetch vs paginated lists, cutoff/missing distinctions, pagination defaults, and the monitored filter. It does not contradict annotations and provides meaningful detail beyond the structured fields.

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

Conciseness5/5

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

The description is well-structured with a one-line summary followed by a compact bullet list of operations. Each line earns its place, providing signatures and defaults without unnecessary prose.

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

Completeness4/5

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

Since an output schema exists, return-value details are not needed. The description covers all operations, parameters, and defaults, and read-only behavior is annotated. A concrete example of the arguments dict or explicit error/return notes would add marginal value, but the description is sufficiently complete for a dispatcher-style tool.

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

Parameters4/5

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

Schema description coverage is 0%, but the description compensates by listing all operation-specific parameters with defaults in the function signatures and identifying query params. Some semantics (e.g., sort_key values, meaning of monitored) are implicit from names, but the dispatch structure is clarified well.

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

Purpose5/5

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

The description clearly states it covers Lidarr 'wanted' operations and enumerates four specific sub-operations with distinct verbs and resources (get/list, cutoff/missing). This distinguishes the tool from sibling domains and makes the exact purpose unambiguous.

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

Usage Guidelines4/5

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

The description explains how to invoke the tool ('Pass operation and an arguments dict matching that operation's parameters') and lists all operations with their parameters. It does not explicitly state when to prefer this over siblings, but the domain is distinct and sibling tools are non-overlapping.

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

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