get_app_metrics

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

No annotations were provided, and the description does not disclose behavioral traits such as required permissions, rate limits, or what happens if the metric is unavailable. For a tool with no annotations, this is insufficient.

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 somewhat verbose, using a Python docstring style with parameter listings. It could be more concise, but the information is well-structured and front-loaded.

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?

The tool has an output schema, so return values are covered. However, it lacks context on prerequisites, authentication, or limitations. Given the complexity and sibling tools, this description is minimally adequate but not 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?

With schema description coverage at 0%, the description adds significant meaning by explaining each parameter: app_id, metric, from_, and to. It specifies that from_ and to should be in ISO 8601 format, which is valuable beyond the schema.

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 'Get individual metric data for a specific application,' specifying both the action and resource. It effectively distinguishes from sibling tools like get_app_endpoints and get_app_insights by focusing on metric data.

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 does not explicitly guide when to use this tool versus alternatives like get_endpoint_metrics or get_job_metrics. The purpose is implied but lacks explicit when-to-use or when-not-to-use instructions.

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