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Backlog MCP Server

get_watching_list_items

Retrieve a user's list of watched items from Backlog project management to track issues, projects, and resources requiring attention.

Instructions

Returns list of watching items for a user

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userIdYesUser ID

Implementation Reference

  • The tool definition including the handler function that executes the tool logic by delegating to the Backlog SDK's getWatchingListItems method with the provided userId.
    export const getWatchingListItemsTool = (
      backlog: Backlog,
      { t }: TranslationHelper
    ): ToolDefinition<
      ReturnType<typeof getWatchingListItemsSchema>,
      (typeof WatchingListItemSchema)['shape']
    > => {
      return {
        name: 'get_watching_list_items',
        description: t(
          'TOOL_GET_WATCHING_LIST_ITEMS_DESCRIPTION',
          'Returns list of watching items for a user'
        ),
        schema: z.object(getWatchingListItemsSchema(t)),
        outputSchema: WatchingListItemSchema,
        handler: async ({ userId }) => backlog.getWatchingListItems(userId),
      };
    };
  • Input schema definition for the tool, specifying userId as a required number field.
    const getWatchingListItemsSchema = buildToolSchema((t) => ({
      userId: z
        .number()
        .describe(t('TOOL_GET_WATCHING_LIST_ITEMS_USER_ID', 'User ID')),
    }));
  • Import of the getWatchingListItemsTool.
    import { getWatchingListItemsTool } from './getWatchingListItems.js';
  • Registration of the tool in the 'issue' toolset within allTools function.
    getWatchingListItemsTool(backlog, helper),
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 mentions returning a list but does not specify details like pagination, sorting, error handling, authentication needs, or rate limits. For a read operation with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.

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 function without unnecessary words. It is front-loaded with the core action, making it easy to parse and understand quickly, which is ideal for conciseness.

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. It does not cover behavioral aspects like response format, error cases, or performance considerations. For a tool that returns a list, more context on what the list contains and how to handle it would be beneficial, making this inadequate for full 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 the 'userId' parameter clearly documented. The description does not add any additional meaning beyond the schema, such as explaining what constitutes a valid user ID or how it relates to watching items. Given the high schema coverage, a baseline score of 3 is appropriate.

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 tool's purpose with a specific verb ('Returns') and resource ('list of watching items for a user'), making it easy to understand what the tool does. However, it does not explicitly differentiate from sibling tools like 'get_watching_list_count' or 'get_watching', which might offer related functionality, preventing a perfect score.

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, such as 'get_watching_list_count' for counts or other 'get_watching' tools. It lacks context on prerequisites, exclusions, or typical use cases, leaving the agent to 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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