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asset_analytics

Read-onlyIdempotent

Get video analytics for a single asset.

Input Schema

NameRequiredDescriptionDefault
metricsNoList of metrics to return in response.
asset_idYesGumlet asset ID
group_byNoGroup the data by this period.
page_sizeNoNumber of items to return per page
date_rangeNo
page_numberNoPage number to fetch. Starting at 1

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / date_range / properties / end_at / description
      Previous value: -"ISO 8601 end timestamp"New value: +"Date in yyyy-MM-dd format"
    • changedInput schema / properties / date_range / properties / start_at / description
      Previous value: -"ISO 8601 start timestamp"New value: +"Date in yyyy-MM-dd format"
  2. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond them — no note on pagination behavior despite page_size/page_number params, no latency/rate-limit context, no explanation of what the aggregation grouping does.

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?

A single front-loaded sentence with zero padding. It is efficient, though the brevity is a symptom of under-specification rather than disciplined concision.

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?

With 6 parameters, a nested date_range object, a metrics enum and over a dozen analytics siblings, an output schema does relieve the need to explain return values, but the description still leaves the agent without routing guidance or any behavioral detail needed to call this correctly against alternatives.

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 83%, so the schema already documents asset_id, group_by, pagination and the date_range object. The description adds no meaning on top of that, making the baseline 3 correct.

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?

States a specific verb+resource ("Get video analytics") and a scoping qualifier ("for a single asset") that separates it from org-wide siblings like analytics_aggregated_data or retrieve_analytics. However it never names those alternatives, so an agent must infer the boundary itself.

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 prerequisites, and no mention of which sibling analytics tool to pick instead. The crowded analytics family (aggregated/breakdown/chart/insights/retrieve variants) makes this omission costly.

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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