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nks-hub

rybbit-mcp

by nks-hub

Overview Time Series

rybbit_get_overview_timeseries
Read-onlyIdempotent

Retrieve time-series analytics data with configurable time buckets for charting trends and monitoring website performance metrics.

Instructions

Get overview metrics as time-series data with configurable time buckets (minute, hour, day, week, month). Returns arrays of data points for charting trends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteIdYesSite ID (numeric ID or domain identifier)
startDateNoStart date in ISO format (YYYY-MM-DD)
endDateNoEnd date in ISO format (YYYY-MM-DD)
timeZoneNoIANA timezone (e.g., Europe/Prague). Default: UTC
filtersNoArray of filters. Example: [{parameter:'browser',type:'equals',value:['Chrome']},{parameter:'country',type:'equals',value:['US','DE']}]
pastMinutesStartNoAlternative to dates: minutes ago start (e.g., 60 = last hour)
pastMinutesEndNoAlternative to dates: minutes ago end (default 0 = now)
bucketNoTime bucket granularity (default: day). Use 'hour' for last 24h, 'week'/'month' for long ranges

Implementation Reference

  • Registration and implementation of the 'rybbit_get_overview_timeseries' tool.
    server.registerTool(
      "rybbit_get_overview_timeseries",
      {
        title: "Overview Time Series",
        description:
          "Get overview metrics as time-series data with configurable time buckets (minute, hour, day, week, month). Returns arrays of data points for charting trends.",
        inputSchema: {
          ...analyticsInputSchema,
          bucket: bucketSchema,
        },
        annotations: {
          readOnlyHint: true,
          destructiveHint: false,
          idempotentHint: true,
          openWorldHint: true,
        },
      },
      async (args) => {
        try {
          const params = client.buildAnalyticsParams({
            startDate: args.startDate,
            endDate: args.endDate,
            timeZone: args.timeZone,
            filters: args.filters,
            pastMinutesStart: args.pastMinutesStart,
            pastMinutesEnd: args.pastMinutesEnd,
            bucket: args.bucket,
          });
    
          const data = await client.get<TimeseriesDataPoint[]>(
            `/sites/${args.siteId}/overview-bucketed`,
            params
          );
    
          return {
            content: [
              {
                type: "text" as const,
                text: truncateResponse(data),
              },
            ],
          };
        } catch (err) {
          const message = err instanceof Error ? err.message : String(err);
          return {
            content: [{ type: "text" as const, text: `Error: ${message}` }],
            isError: true,
          };
        }
      }
    );
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral context by specifying the return format ('arrays of data points'), which compensates partially for the missing output schema. It does not contradict annotations, though it misses rate limits or pagination details.

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 consists of two efficient sentences with zero waste. It is front-loaded with the core action ('Get overview metrics...') and immediately follows with return value information, making it easy for an agent to parse quickly.

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

Completeness4/5

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

Given the rich schema (100% coverage) and comprehensive annotations, the description appropriately focuses on high-level purpose and return format rather than repeating parameter details. It adequately covers what the tool does and what it returns despite lacking an output schema.

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?

With 100% schema description coverage, the structured documentation already comprehensively defines all 8 parameters including examples. The description mentions 'configurable time buckets' which aligns with but does not extend beyond the schema's enum documentation, warranting the baseline score of 3.

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 retrieves 'overview metrics as time-series data' with specific verb and resource. It effectively distinguishes from sibling 'rybbit_get_overview' by emphasizing time-series functionality and 'charting trends', helping the agent select the correct variant for temporal analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides implied usage context ('for charting trends') suggesting when to use this tool, but lacks explicit guidance on when to prefer this over 'rybbit_get_overview' or other timeseries siblings like 'rybbit_get_performance_timeseries'. No exclusions or prerequisites are mentioned.

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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