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Backlog MCP Server

get_watching_list_count

Count how many items a user is watching in Backlog to track their monitoring workload and prioritize notifications.

Instructions

Returns count of watching items for a user

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userIdYesUser ID

Implementation Reference

  • The primary handler implementation for the 'get_watching_list_count' tool. It defines the tool including name, description, input/output schemas, and the async handler that calls backlog.getWatchingListCount(userId).
    export const getWatchingListCountTool = (
      backlog: Backlog,
      { t }: TranslationHelper
    ): ToolDefinition<
      ReturnType<typeof getWatchingListCountSchema>,
      (typeof WatchingListCountSchema)['shape']
    > => {
      return {
        name: 'get_watching_list_count',
        description: t(
          'TOOL_GET_WATCHING_LIST_COUNT_DESCRIPTION',
          'Returns count of watching items for a user'
        ),
        schema: z.object(getWatchingListCountSchema(t)),
        outputSchema: WatchingListCountSchema,
        handler: async ({ userId }) => backlog.getWatchingListCount(userId),
      };
    };
  • Input schema for the tool, defining the 'userId' parameter as a number.
    const getWatchingListCountSchema = buildToolSchema((t) => ({
      userId: z
        .number()
        .describe(t('TOOL_GET_WATCHING_LIST_COUNT_USER_ID', 'User ID')),
    }));
  • Output schema for the tool response, defining a 'count' number field.
    export const WatchingListCountSchema = z.object({
      count: z.number(),
    });
  • Registration of the getWatchingListCountTool into the 'issue' toolset group in the allTools function.
    getWatchingListCountTool(backlog, helper),
  • Import of the getWatchingListCountTool for use in toolset registration.
    import { getWatchingListCountTool } from './getWatchingListCount.js';
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 the tool returns a count, but doesn't cover aspects like whether it requires authentication, handles errors, has rate limits, or what the output format is (e.g., integer, JSON). This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the key action and resource, making it easy to parse quickly. There's no wasted verbiage, adhering perfectly to conciseness standards.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete for effective use. It doesn't explain the return value format, error handling, or authentication needs, which are critical for a tool that likely interacts with user data. While the purpose is clear, the missing behavioral and output details hinder full contextual understanding.

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

Parameters3/5

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

The input schema has 100% description coverage, with 'userId' clearly documented as 'User ID'. The description adds no additional parameter details beyond what the schema provides, such as format constraints or examples. Given the high schema coverage, a baseline score of 3 is appropriate as the schema adequately handles parameter semantics.

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 action ('Returns count') and resource ('watching items for a user'), making the purpose specific and understandable. However, it doesn't explicitly distinguish itself from sibling tools like 'get_watching_list_items' or 'count_notifications', which could provide similar counting functionality in different contexts, leaving room for minor ambiguity.

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. For example, it doesn't mention if this is preferred over 'get_watching_list_items' for just counts or how it relates to 'count_notifications'. Without such context, users must infer usage from the tool name alone.

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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