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datadog-mcp-server

aggregate-ci-pipelines

Aggregate CI pipeline data with statistical computations like count, average, percentiles, and group results 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?

With no annotations, the description carries full burden but does not disclose behavioral traits like read-only nature, permission requirements, or output format. 'Aggregate' implies read access but is not explicit.

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 that is efficient. However, it could be slightly expanded to include scope without losing conciseness.

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 six parameters and no output schema, the description is incomplete. It does not explain the return structure, pagination, or any limitations of the aggregation, leaving significant gaps for the agent.

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% with individual parameter descriptions. The tool description adds minimal value beyond schema; it only mentions 'statistical computations and grouping,' which aligns with aggregation and groupBy params.

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?

Clearly states it aggregates CI/CD pipeline data with statistics and grouping, distinguishing it from sibling tools like aggregate-ci-tests (for tests) and aggregate-logs. However, it lacks specificity about the exact resource (pipeline events).

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?

Provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions or prerequisites, leaving the agent to infer context.

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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