datadog_metrics_query

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

The description discloses the return format (YAML matching CLI output with status, from_date, to_date, series), which is useful. However, with no annotations provided, it does not explicitly state that the tool is read-only or has no side effects, nor does it mention rate limits, authentication requirements, or potential latency. The description partially covers behavioral traits but leaves gaps.

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?

The description consists of two concise sentences. The first clearly states the core action, and the second adds valuable context about CLI mirroring and output format. No redundant or extraneous information, achieving high efficiency.

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?

Given the tool has only 3 parameters, no output schema, and no annotations, the description provides adequate context: it explains the output structure and references a CLI command for familiarity. It lacks mention of error scenarios, pagination, or rate limits, but for a simple point-in-time query, the description is reasonably complete.

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?

The input schema provides 100% description coverage for all three parameters (from, query, to). The tool description adds no additional parameter-level details beyond what the schema already offers. According to calibration, baseline 3 is appropriate when schema coverage is high and the description does not enhance semantics.

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 clearly states the tool executes a Datadog metrics timeseries query, using a specific verb and resource. It distinguishes from other Datadog sibling tools (like datadog_dashboard_get or datadog_logs_search) by focusing on metrics queries. The mention of mirroring a CLI command further clarifies the tool's exact purpose.

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 implies usage by stating it mirrors a CLI command, but does not explicitly guide when to use this tool vs alternatives (e.g., datadog_metrics_catalog_list for listing metrics, or datadog_events_list for events). No 'when-not-to-use' or alternative tool mentions are provided.

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