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get_active_users_all_apps

Retrieve active user statistics (DAU/WAU/MAU) across all applications in a single query to monitor platform engagement and usage patterns.

Instructions

Get active user counts across all apps at once. Queries each app's DAU/WAU/MAU stats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoTime period: 24h (DAU), 7d (WAU), 30d (MAU). Default: 24h

Implementation Reference

  • The handler logic for the 'get_active_users_all_apps' tool, which fetches all apps and then retrieves active user stats for each.
    case "get_active_users_all_apps": {
      const apps = await apiRequest("GET", "/v1/apps");
      const appList = apps.apps || apps;
      const period = args?.period || "24h";
      const stats = await Promise.all(
        appList.map(async (app) => {
          try {
            return await apiRequest("GET", "/v1/activity/stats", {
              query: { app_id: app.app_id, period },
            });
          } catch {
            return { app_id: app.app_id, period, active_users: 0, error: "Failed to fetch stats" };
          }
        })
      );
      result = stats;
      break;
    }
    
    case "get_sentiment_insights": {
  • index.js:293-298 (registration)
    The MCP tool registration for 'get_active_users_all_apps'.
    {
      name: "get_active_users_all_apps",
      description:
        "Get active user counts across all apps at once. Queries each app's DAU/WAU/MAU stats.",
      inputSchema: {
        type: "object",
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 queries stats, implying a read-only operation, but does not mention permissions, rate limits, error handling, or output format. For a tool with no annotations, this leaves significant gaps in understanding its behavior, scoring a 2.

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 concise and front-loaded, with two sentences that directly state the tool's purpose and scope. There is no wasted text, and it efficiently communicates key information. However, it could be slightly more structured by explicitly separating purpose from behavioral details, but it's still highly efficient, scoring a 4.

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 tool's complexity (aggregating data across apps), lack of annotations, and no output schema, the description is incomplete. It does not explain the return format, error conditions, or dependencies. For a tool that queries multiple apps' stats, more context is needed to understand its full behavior, resulting in a score of 2.

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 schema description coverage is 100%, with the parameter 'period' fully documented in the input schema. The description adds no additional parameter semantics beyond what the schema provides, such as format details or examples. According to the rules, with high schema coverage, the baseline is 3, which is appropriate here.

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: 'Get active user counts across all apps at once' specifies the verb ('get'), resource ('active user counts'), and scope ('across all apps'). It distinguishes from the sibling 'get_active_users' by emphasizing the 'all apps at once' scope, though it doesn't explicitly name the sibling. This is clear but lacks explicit sibling differentiation, warranting a 4.

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 'Queries each app's DAU/WAU/MAU stats,' which implies usage for aggregated metrics, but does not specify contexts, exclusions, or compare to other tools like 'get_active_users' or 'get_app'. Without explicit when/when-not instructions, it scores a 2.

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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