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Datadog MCP Server

by brukhabtu

EstimateMetricsOutputSeries

Calculate estimated metric cardinality for specific tags, percentiles, and aggregation configurations using Metrics without Limits™ on Datadog MCP Server's observability platform.

Instructions

Returns the estimated cardinality for a metric with a given tag, percentile and number of aggregations configuration using Metrics without Limits™.

Path Parameters:

  • metric_name (Required): The name of the metric.

Query Parameters:

  • filter[groups]: Filtered tag keys that the metric is configured to query with.

  • filter[hours_ago]: The number of hours of look back (from now) to estimate cardinality with. If unspecified, it defaults to 0 hours.

  • filter[num_aggregations]: Deprecated. Number of aggregations has no impact on volume.

  • filter[pct]: A boolean, for distribution metrics only, to estimate cardinality if the metric includes additional percentile aggregators.

  • filter[timespan_h]: A window, in hours, from the look back to estimate cardinality with. The minimum and default is 1 hour.

Responses:

  • 200 (Success): Success

    • Content-Type: application/json

    • Response Properties:

    • Example:

{
  "data": "unknown_type"
}
  • 400: API error response.

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 403: API error response.

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 404: API error response.

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 429: Too Many Requests

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filter[groups]NoFiltered tag keys that the metric is configured to query with.
filter[hours_ago]NoThe number of hours of look back (from now) to estimate cardinality with. If unspecified, it defaults to 0 hours.
filter[num_aggregations]NoDeprecated. Number of aggregations has no impact on volume.
filter[pct]NoA boolean, for distribution metrics only, to estimate cardinality if the metric includes additional percentile aggregators.
filter[timespan_h]NoA window, in hours, from the look back to estimate cardinality with. The minimum and default is 1 hour.
metric_nameYesThe name of the metric.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions the tool uses 'Metrics without Limits™' and includes error responses (e.g., 429 for rate limits), but lacks details on permissions, side effects, rate limits beyond the 429 hint, or what 'estimated cardinality' entails in practice. The description adds some context but is insufficient for a mutation-like estimation tool with no annotation coverage.

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?

The description is structured with sections for parameters and responses, but it is overly verbose, including detailed HTTP response examples and error codes that could be inferred from annotations or output schema. The core purpose is stated upfront, but extraneous details reduce efficiency, making it less concise than ideal.

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?

Given the tool's complexity (6 parameters, no annotations, but with output schema), the description covers the basic purpose and parameters but lacks usage guidelines and detailed behavioral context. The output schema exists, so return values need not be explained, but the description does not fully address the tool's operational context, leaving gaps in completeness.

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%, with all parameters well-documented in the input schema. The description lists parameters in a 'Path Parameters' and 'Query Parameters' section, but this largely repeats schema information without adding significant meaning (e.g., explaining interactions between parameters). Given high schema coverage, the baseline score of 3 is appropriate as the description does not compensate beyond the schema.

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: 'Returns the estimated cardinality for a metric with a given tag, percentile and number of aggregations configuration using Metrics without Limits™.' It specifies the verb ('Returns'), resource ('estimated cardinality'), and key parameters, but does not explicitly differentiate from sibling tools, which are mostly 'Get' or 'List' operations for various resources, making this tool's focus on estimation distinct but not directly contrasted.

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 the tool's function but does not specify prerequisites, typical use cases, or comparisons with sibling tools like 'ListVolumesByMetricName' or 'ListTagConfigurationByName', which might be related. This leaves the agent without context for selection.

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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