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fluentcrm_dashboard_stats

Retrieve dashboard statistics to monitor marketing automation performance and track key metrics within FluentCRM.

Instructions

Pobiera statystyki dashboarda

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler that executes the tool by calling client.getDashboardStats() and formats the response as MCP content.
    case 'fluentcrm_dashboard_stats':
      return { content: [{ type: 'text', text: JSON.stringify(await client.getDashboardStats(), null, 2) }] };
  • Registers the tool with MCP server including name, description, and input schema.
      name: 'fluentcrm_dashboard_stats',
      description: 'Pobiera statystyki dashboarda',
      inputSchema: {
        type: 'object',
        properties: {},
      },
    },
  • Input schema definition for the tool (no required parameters).
    inputSchema: {
      type: 'object',
      properties: {},
    },
  • Core implementation that fetches dashboard statistics from the FluentCRM API.
    async getDashboardStats() {
      const response = await this.apiClient.get('/reports/dashboard-stats');
      return response.data;
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action ('retrieves') without details on permissions needed, rate limits, data freshness, or response format. This leaves significant gaps for a tool that likely provides aggregated data.

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

Conciseness4/5

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

The description is a single, efficient sentence in Polish, front-loading the core purpose without unnecessary words. However, it could be slightly more informative without losing 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 complexity of a dashboard stats tool (likely involving aggregated data), no annotations, and no output schema, the description is incomplete. It lacks details on what statistics are returned, their format, or any behavioral traits, making it inadequate for effective use by an AI agent.

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 the schema description coverage is 100% (empty schema). The description doesn't need to add parameter details, so a baseline of 4 is appropriate, as it doesn't contradict or omit any parameter information.

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 'Pobiera statystyki dashboarda' (Polish for 'Retrieves dashboard statistics') states a clear verb ('retrieves') and resource ('dashboard statistics'), but it's vague about what specific statistics are included. It doesn't differentiate from sibling tools like 'fluentcrm_list_campaigns' or 'fluentcrm_list_contacts' beyond the general 'dashboard' focus.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention any context, prerequisites, or exclusions, such as whether it's for high-level overviews versus detailed reports available in other tools.

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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