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datadog-mcp-server

create-spans-metric

Create a count or distribution metric from APM spans, filtered and grouped by specified fields.

Instructions

Create a metric based on APM span data (count or distribution, with filters and group-by)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe name of the span-based metric. Example: spans.request_duration
aggregationTypeYesAggregation type. 'count' counts span events, 'distribution' creates a distribution metric
pathNoPath to the metric value. Required for distribution metrics. Example: @duration
includePercentilesNoWhether to include percentile aggregations. Only for distribution metrics
filterQueryNoAPM search query to filter spans. Example: service:web-app resource_name:GET_/api/users
groupByNoFields to group the metric by
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not disclose whether the operation is destructive (e.g., overwriting an existing metric), idempotent, or requires any prerequisites (e.g., existing APM data). It omits side effects.

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

Conciseness5/5

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

The description is a single, front-loaded sentence with no wasted words. It efficiently conveys core purpose and key features.

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?

Without an output schema or annotations, the description lacks detail on return value, permissions, and conditional parameter requirements (e.g., path needed for distribution but not count). It is insufficient for a creation tool with 6 parameters.

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?

All parameters are described in the schema (100% coverage), so the description adds minimal value beyond summarizing the metric type. Baseline 3 applies as the schema already does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Create a metric based on APM span data' with specific methods (count/distribution, filters, group-by). It distinguishes from sibling tools like create-logs-metric (logs) and create-rum-metric (RUM) by specifying the data source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly conveys usage for APM span metrics but lacks explicit guidance on when not to use or alternatives. Given the many sibling tools, it's clear from context but no exclusions are stated.

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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