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dreamiurg

Datadog MCP Server

by dreamiurg

get-dbm-samples

Retrieve database query samples with execution time, affected rows, and context to diagnose slow queries and performance issues.

Instructions

Get Database Monitoring query samples. Use for 'slow database queries', 'what queries are running on postgres', 'DB performance issues'. Returns query samples with execution time, affected rows, and database context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startNoStart timestamp (Unix seconds)
endNoEnd timestamp (Unix seconds)
sourceNoDatabase type (e.g., 'postgresql', 'mysql')
dbHostNoDatabase hostname filter
dbNameNoDatabase name filter
limitNoMax results to return
Behavior3/5

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

No annotations are provided, so the description must disclose behavior. It states it returns query samples with execution time, affected rows, and database context, implying a read-only operation. However, it omits details like authentication requirements, rate limits, or potential 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 concise with two sentences. The first sentence states the action and resource, and the second provides use cases and return types. No extraneous information.

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?

The description covers the tool's purpose and return fields but lacks details on default behavior when optional parameters are omitted, pagination, result ordering, or limits on time range. With no output schema, more context on return structure would be beneficial.

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?

The input schema already describes all six parameters, so the baseline is 3. The description adds no additional parameter-specific meaning; it only mentions return fields (execution time, rows, context), which are not in the schema.

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 the tool retrieves Database Monitoring query samples, with specific verb 'Get' and resource. It also provides concrete use cases like 'slow database queries' and 'DB performance issues', making the purpose unambiguous.

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 gives clear example scenarios for when to use this tool, such as investigating slow queries or monitoring current query activity. However, it does not explicitly mention when not to use it or differentiate from sibling tools like 'get_dbm_query_metrics'.

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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