get_metrics

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'execute[s] metric queries' which implies a read operation, but doesn't disclose important behavioral traits like whether it requires specific authentication, has rate limits, returns paginated results, or what happens on errors. The description mentions building and executing the query but lacks operational context needed for safe and effective use.

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 is appropriately concise with two sentences that efficiently convey the core functionality. The first sentence states the purpose, the second provides basic parameter guidance. No wasted words, though it could be slightly more front-loaded with key behavioral information given the lack of annotations.

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's complexity (6 parameters including nested objects), lack of annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (metrics data in various formats), doesn't mention authentication requirements, rate limits, or error handling. For a query tool with this parameter complexity and no structured safety/behavior annotations, the description should provide more operational context.

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%, so the schema already documents all 6 parameters thoroughly with descriptions, enums, defaults, and examples. The description adds minimal value beyond the schema - it mentions 'metric name and optional filters/aggregations' which is already clear from the schema. The baseline of 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'Execute metric queries on Datadog' with specific verb ('execute') and resource ('metric queries'). It distinguishes from some siblings like 'list_metrics' (which likely lists available metrics rather than querying them) but doesn't explicitly differentiate from 'get_metric_fields' or 'get_metric_field_values' which are related to metric metadata.

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 implied usage guidance by mentioning 'Specify the metric name and optional filters/aggregations' which suggests when to use this tool (for querying metrics with specific parameters). However, it doesn't explicitly state when to use this vs. alternatives like 'list_metrics' (for listing available metrics) or 'get_metric_fields' (for discovering queryable fields). No explicit exclusions or prerequisites are mentioned.

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