get_endpoint_metrics

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing about permissions, rate limits, metric granularity/resolution, behavior on unknown endpoints or invalid metric names, or empty-result handling. Only 'timeseries' hints at the shape of the data, and the output schema would cover the return contract — the operational behavior is left unstated.

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 purpose sentence is front-loaded and the Args block is tight, one line per parameter with no filler. The format is a standard docstring-style listing — efficient, though slightly formulaic rather than deliberately structured for an agent.

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?

With an output schema present, the return contract need not be described, and all five required parameters are explained. What is missing for a 5-parameter, zero-annotation analytics query tool is guidance on time range constraints, metric validity, and how this differs from the app-level and job-level metric siblings.

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 coverage is 0% (bare titles only), so the description must compensate, and it largely does: it explains app_id as the Scout APM application ID, gives concrete endpoint path examples ('/users', '/orders'), gives metric examples ('response_time', 'throughput'), and specifies ISO 8601 for both from_ and to. It does not enumerate the valid metric names or state whether endpoint must be an exact path match, which keeps it from a 5.

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 first sentence names a specific verb and resource ('Get a single timeseries metric') scoped to 'a specific endpoint in an application', which is enough to tell it apart from get_app_metrics or get_job_metrics on subject matter alone. It stops short of explicitly naming a sibling or stating the boundary condition, so it is clear but not fully differentiating.

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?

There is no when-to-use section, no prerequisites, and no mention of the sibling tools (get_app_metrics, get_job_metrics, get_app_endpoint_traces) that cover adjacent scopes. The agent must infer that endpoint-level timeseries is the right choice here purely from the tool name and purpose sentence.

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