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nks-hub

rybbit-mcp

by nks-hub

Overview Time Series

rybbit_get_overview_timeseries
Read-onlyIdempotent

Retrieve overview metrics as time-series data with configurable time buckets. Returns arrays of data points for charting trends over any date range.

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
Behavior3/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint, covering safety. The description adds output format context (arrays for charting) but does not disclose any additional behavioral traits like rate limits or result size bounds. With annotations present, the description adds marginal value.

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, well-structured sentence of 20 words. It front-loads the core action and resource, includes key differentiators (time buckets, data format), and contains no extraneous information.

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 tool has 8 parameters, no output schema, and rich annotations, the description is complete enough to convey the core purpose and return type. It could mention the specific metrics included in 'overview' or clarify data point structure, but the context is sufficient for a read-only, well-annotated tool.

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%, so the schema already documents all parameters thoroughly. The description only mentions configurable buckets and return format, adding no new parameter-specific semantics beyond what the schema provides. Baseline 3 is appropriate.

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

Purpose5/5

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

The description clearly states the verb 'Get', the resource 'overview metrics as time-series data', and notes configurable time buckets and return format (arrays for charting). It distinguishes from siblings like rybbit_get_overview (snapshot) and rybbit_get_metric (single metric), providing a specific and actionable purpose.

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?

The description mentions configurable time buckets but does not explicitly instruct when to use this tool versus alternatives like rybbit_get_overview. The schema includes hints on bucket selection (e.g., 'Use hour for last 24h'), but no direct comparisons or exclusions are given.

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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