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datadog-mcp-server

create-rum-retention-filter

Create a RUM retention filter to keep specific events based on event type, sample rate, and search query.

Instructions

Create a RUM retention filter with event type, sample rate, and query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appIdYesRUM application ID
nameYesName of the retention filter. Example: Keep all errors
eventTypeYesRUM event type to filter on. Example: error
sampleRateYesSample rate between 0 and 100. Example: 100
queryNoRUM search query to filter events. Example: @error.source:network
enabledNoWhether the filter is enabled. Default: true
Behavior2/5

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

Annotations already indicate write operation (readOnlyHint: false) and open-world side effects. The description adds no extra behavioral details, such as permissions required, idempotency, or immediate application of the filter. It does not disclose any traits beyond the basic action.

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, front-loaded with the core purpose. It is efficient, but could include slightly more context without becoming verbose, such as mentioning the return value or the purpose of retention filters.

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?

Despite having 6 parameters and no output schema, the description does not explain what the tool returns or how the creation affects the system. It lacks information about retention filter semantics, error conditions, or confirmation of success. More detail is needed for full contextual 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 coverage is 100%, with each parameter described in the input schema. The tool description only mentions three parameters (event type, sample rate, query) and does not add meaning beyond the schema. It neither clarifies relationships nor constraints, so it meets the baseline for high coverage but does not exceed it.

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 RUM retention filter', specifying the verb (create) and the resource (RUM retention filter). It distinguishes itself from sibling tools like 'create-apm-retention-filter' and other create tools for different resources, making it unambiguous.

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, such as when to create vs. update a filter, or any prerequisites. There are no contextual hints for usage decisions.

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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