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lidarr_get_tags

Retrieve all organizational tags from Lidarr to categorize and filter music content effectively.

Instructions

Get all tags defined in Lidarr (Music). Tags can be used to organize and filter content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/index.ts:154-161 (registration)
    Registration of the 'lidarr_get_tags' tool (dynamically named via `${serviceName}_get_tags` where serviceName='lidarr') including input schema (no parameters). Called via addConfigTools('lidarr') at line 177.
      name: `${serviceName}_get_tags`,
      description: `Get all tags defined in ${displayName}. Tags can be used to organize and filter content.`,
      inputSchema: {
        type: "object" as const,
        properties: {},
        required: [],
      },
    },
  • Input schema for lidarr_get_tags: empty object (no input parameters required). Output is JSON of tags list.
    inputSchema: {
      type: "object" as const,
      properties: {},
      required: [],
    },
  • MCP tool handler for lidarr_get_tags: parses service name, retrieves LidarrClient instance, calls getTags(), returns formatted JSON response with tag count and list.
    case "sonarr_get_tags":
    case "radarr_get_tags":
    case "lidarr_get_tags":
    case "readarr_get_tags": {
      const serviceName = name.split('_')[0] as keyof typeof clients;
      const client = clients[serviceName];
      if (!client) throw new Error(`${serviceName} not configured`);
      const tags = await client.getTags();
      return {
        content: [{
          type: "text",
          text: JSON.stringify({
            count: tags.length,
            tags: tags.map(t => ({ id: t.id, label: t.label })),
          }, null, 2),
        }],
      };
    }
  • Core implementation of getTags() in ArrClient base class (used by LidarrClient): makes API request to '/tag' endpoint to fetch all tags.
    /**
     * Get all tags
     */
    async getTags(): Promise<Tag[]> {
      return this.request<Tag[]>('/tag');
    }
  • LidarrClient class definition, extends ArrClient (inherits getTags()), uses API v1, instantiated in index.ts for lidarr_get_tags handler.
    export class LidarrClient extends ArrClient {
      constructor(config: ArrConfig) {
        super('lidarr', config);
        this.apiVersion = 'v1';
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a 'Get' operation, implying read-only behavior, but doesn't clarify if it requires authentication, has rate limits, returns paginated results, or what the output format might be. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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 two concise sentences that efficiently convey the core purpose and utility of the tool. The first sentence states what it does, and the second adds helpful context about tag usage. There's no redundant or unnecessary information, making it well-structured and front-loaded.

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

Completeness3/5

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

Given the tool has 0 parameters, no output schema, and no annotations, the description is minimally adequate. It explains what the tool does but lacks details on behavioral aspects like authentication needs, rate limits, or output format. For a simple read operation, this might suffice, but it doesn't provide complete context for reliable agent use without additional assumptions.

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?

The tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter documentation in the description. The baseline for this scenario is 4, as the description appropriately doesn't waste space on non-existent parameters. It focuses on the tool's purpose instead.

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

Purpose4/5

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

The description clearly states the verb 'Get' and resource 'all tags defined in Lidarr (Music)', making the purpose specific. It adds context about tags being used 'to organize and filter content', which is helpful. However, it doesn't explicitly distinguish this from sibling tools like 'radarr_get_tags' or 'sonarr_get_tags', which have similar naming patterns but for different media types.

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

Usage Guidelines2/5

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 mentions tags can be used 'to organize and filter content', which implies a use case but doesn't specify when this tool is appropriate compared to other tag-related operations or other Lidarr tools. There's no mention of prerequisites, timing, or explicit alternatives.

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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