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Backlog MCP Server

count_notifications

Count unread notifications in Backlog to track project updates and manage workflow visibility.

Instructions

Returns count of notifications

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alreadyReadYesWhether to include already read notifications
resourceAlreadyReadYesWhether to include notifications for already read resources

Implementation Reference

  • Exports the getNotificationsCountTool function which defines the 'count_notifications' tool, including name, description, input schema, output schema reference, and handler that delegates to backlog.getNotificationsCount(params).
    export const getNotificationsCountTool = (
      backlog: Backlog,
      { t }: TranslationHelper
    ): ToolDefinition<
      ReturnType<typeof getNotificationsCountSchema>,
      (typeof NotificationCountSchema)['shape']
    > => {
      return {
        name: 'count_notifications',
        description: t(
          'TOOL_COUNT_NOTIFICATIONS_DESCRIPTION',
          'Returns count of notifications'
        ),
        schema: z.object(getNotificationsCountSchema(t)),
        outputSchema: NotificationCountSchema,
        handler: async (params) => backlog.getNotificationsCount(params),
      };
    };
  • Registers the count_notifications tool (via getNotificationsCountTool) as part of the 'notifications' toolset in the allTools export.
    {
      name: 'notifications',
      description: 'Tools for managing user notifications.',
      enabled: false,
      tools: [
        getNotificationsTool(backlog, helper),
        getNotificationsCountTool(backlog, helper),
        resetUnreadNotificationCountTool(backlog, helper),
        markNotificationAsReadTool(backlog, helper),
      ],
    },
  • Defines the input schema for the count_notifications tool with optional boolean parameters alreadyRead and resourceAlreadyRead.
    const getNotificationsCountSchema = buildToolSchema((t) => ({
      alreadyRead: z
        .boolean()
        .describe(
          t(
            'TOOL_GET_NOTIFICATIONS_COUNT_ALREADY_READ',
            'Whether to include already read notifications'
          )
        ),
      resourceAlreadyRead: z
        .boolean()
        .describe(
          t(
            'TOOL_GET_NOTIFICATIONS_COUNT_RESOURCE_ALREADY_READ',
            'Whether to include notifications for already read resources'
          )
        ),
    }));
  • Defines the Zod output schema for the notification count response, an object containing a 'count' number field.
    export const NotificationCountSchema = z.object({
      count: z.number(),
    });
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 read operation ('returns'), which implies it's non-destructive, but doesn't mention any behavioral traits like whether it requires authentication, has rate limits, returns a simple integer or structured count, or if it's paginated. 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 extremely concise with just three words ('Returns count of notifications'), front-loaded with the core purpose. Every word earns its place, and there's no wasted text. It's appropriately sized for a simple counting tool.

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 no annotations, no output schema, and 2 required parameters, the description is incomplete. It doesn't explain what the return value looks like (e.g., a number, object with count), any prerequisites like authentication, or error conditions. For a tool with parameters and no structured output documentation, more context is needed to be fully useful to an AI agent.

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?

Schema description coverage is 100%, with both parameters ('alreadyRead' and 'resourceAlreadyRead') fully documented in the input schema. The description adds no parameter information beyond what the schema provides. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.

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

Purpose3/5

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

The description 'Returns count of notifications' clearly states the verb ('returns count') and resource ('notifications'), making the basic purpose understandable. However, it doesn't differentiate from sibling tools like 'get_notifications' or 'get_watching_list_count', which might provide similar counting functionality for different resources. The purpose is clear but lacks sibling differentiation.

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. There's no mention of why one would choose 'count_notifications' over 'get_notifications' or other sibling tools that might return notification data. No context, exclusions, or alternatives are specified.

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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