metrics_levels

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

With no annotations, the description must carry the full behavioral burden. It usefully states the returned breakdown and diagnostic purpose, but it omits that the query is scoped by the minutes window/default 60 and does not explicitly state that it is a read-only metrics read.

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?

Two sentences, front-loaded with the output definition and followed by the use case. There is no wasted text and the structure is easy to scan.

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?

No output schema exists, but the description explains the output distribution well enough. The fully described two-parameter schema covers the inputs, though the description could be more complete by mentioning time-window scoping and read-only behavior.

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 project_id and minutes. The description adds no parameter semantics beyond listing the log levels returned, which is the expected baseline when the schema is complete.

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 operation and resource: distribution of log levels with counts and percentages for debug, info, warn, error, and fatal. It is clear what the tool computes, though it does not explicitly distinguish itself from sibling metrics tools such as metrics_distributions or metrics_overview.

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?

It gives an explicit use case: understanding the severity profile of logs and checking whether error rates are elevated. It does not provide when-not conditions or direct alternatives, so it falls short of full sibling routing guidance.

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