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datadog-mcp-server

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aggregate-ci-pipelines

Aggregate CI/CD pipeline metrics using statistical functions like count, average, sum, min, max, and percentiles, with optional grouping by pipeline name or status.

Instructions

Aggregate CI/CD pipeline data with statistical computations and grouping

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoCI pipeline search query for aggregation*
fromYesStart time (ISO 8601 or relative)
toYesEnd time (ISO 8601 or relative)
aggregationYesAggregation type
metricNoMetric to aggregate on (required for avg/sum/min/max/percentiles). Example: @duration
groupByNoField to group results by. Example: @ci.pipeline.name, @ci.status
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states 'aggregate' without confirming it is read-only or mentioning any side effects, permissions, or constraints.

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?

The description is a single, concise sentence. It is not verbose, but it could be more structured to front-load key information. Still, it earns its place.

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?

Given 6 parameters, no output schema, and no annotations, the description is insufficient. It does not explain return values, pagination, or any operational details, leaving the agent underinformed.

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 coverage is 100%, so parameters are documented. The description adds nothing beyond the schema, merely restating the concept. Baseline 3 is appropriate.

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 it aggregates CI/CD pipeline data with statistical computations and grouping, distinguishing it from sibling tools like aggregate-ci-tests. However, it could be more specific about the types of aggregation.

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?

No guidance on when to use this tool versus alternatives like aggregate-ci-tests or other aggregate tools. The description does not provide 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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