datadog_query_metrics

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds no behavioral context beyond that: no mention of auth requirements, rate limits, or return shape, so it's a minimal contribution.

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

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

It's a single front-loaded sentence with no wasted words. However, it's arguably too terse to function optimally for a 5-parameter tool with required credentials.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool requiring api_key/app_key and a Datadog query string, the description omits key context: it doesn't explain the required authentication, what time-series response format to expect, or how pagination/limits work. With no output schema, this leaves gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (all 5 parameters documented, including query format example and time defaults), so the schema does the heavy lifting. The description adds no parameter-level meaning beyond what's already provided.

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

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

The description states a specific verb+resource: 'Query Datadog metrics time-series data.' The resource 'metrics' distinguishes it from sibling datadog tools (datadog_get_monitor, datadog_list_dashboards, datadog_list_events), but it doesn't explicitly call out the differentiation.

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

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 vs alternatives, no prerequisites, and no exclusions. An agent has to infer usage purely from the name and schema.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.