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analytics_aggregated_data

Read-onlyIdempotent

This endpoint retrieves aggregated data of the given metrics.

Input Schema

NameRequiredDescriptionDefault
filtersNoGet aggregations for metrics with multiple filters, `value` should be an exact match
aggregateNoAggregate multiple metrics at the same time
timeframeNoThe timeframe to get the data for. The maximum range between start_at and end_at is 60 days.
workspace_idNoThe unique identifier of the Gumlet workspace ID available on the Video Workspaces.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / timeframe / description
      Previous value: -"The timeframe to get the data for. Currently we only support maximum difference between `start_at` and `end_at` to be *60 days*"New value: +"The timeframe to get the data for. The maximum range between start_at and end_at is 60 days."
    • changedInput schema / properties / timeframe / properties / end_at / description
      Previous value: -"Use <b>yyyy-MM-dd</b> format"New value: +"Date in yyyy-MM-dd format"
    • changedInput schema / properties / timeframe / properties / start_at / description
      Previous value: -"Use <b>yyyy-MM-dd</b> format"New value: +"Date in yyyy-MM-dd format"
    • addedInput schema / properties / timeframe / required
      Added value: +[
      +  "start_at",
      +  "end_at"
      +]
  2. First observed

TDQS

C2.6/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds nothing beyond that: it says nothing about rate limits, pagination, the 60-day constraint (left to the schema), or what the response contains. With annotations doing the work, this is only minimally acceptable.

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

Conciseness3/5

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

A single front-loaded sentence with no filler, so nothing needs trimming. But the brevity here reflects under-specification rather than efficiency; the sentence does not earn much for the agent.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and annotations cover the safety profile. What remains missing is differentiation from the analytics/insights siblings and any hint of how the nested aggregate/filter structures are meant to be combined, which matters for a complex multi-part query 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 nested filters, aggregate, timeframe, and workspace_id fields are all documented in the schema itself. The description restates only 'the given metrics' and adds no semantics about how filters, aggregate functions, and timeframe combine. Baseline 3 applies when the schema carries full parameter burden.

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?

States a specific verb (retrieves) and resource (aggregated data of given metrics), which is more than a tautology. However, it does not distinguish this tool from close siblings such as insights_aggregated_data, analytics_breakdown_data, analytics_chart_data, or retrieve_analytics, all of which plausibly read analytics data. An agent cannot tell which of these to pick from the description alone.

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?

There is no when-to-use guidance, no mention of prerequisites (e.g., fetching a workspace_id first), and no reference to alternative analytics tools. The agent must infer the routing decision entirely from the name and the large sibling list.

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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