logs_facets

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

No annotations are supplied, so the description carries the burden. "Count" adequately implies a read-only, non-destructive aggregation, but it says nothing about the default time window when `from`/`to` are omitted (a meaningful behavioral default for an 8-param, all-optional tool), nor about facet cardinality or result-size limits.

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?

A single sentence that front-loads the core verb and resource, then appends the grouping dimensions and the workflow motivation. Dense but waste-free; the facet list is slightly crammed into one clause rather than being broken out.

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 description conveys the aggregation axes and the intent, partially compensating for the absent output schema. However, for a tool with no annotations and no output schema, it omits the shape of the result (bucket/value/count triples) and the default time range, both of which an agent needs to interpret counts correctly.

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 100%, so the baseline is 3, but the description earns more by revealing the output grouping dimensions. Notably, "codebase" and "extension instance" appear nowhere in the input schema, so the description is the only place an agent learns these aggregation axes exist.

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?

"Count the log lines matching a filter" is a specific verb+resource, and the description enumerates the grouping dimensions (level, service, function, codebase, extension instance, kind), which separates it from a plain search. It does not name `logs_search` explicitly, so sibling differentiation is implied via "before reading them" rather than stated.

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?

"to see where errors and warnings come from before reading them" establishes a clear place in the workflow: aggregate first, read individual lines afterwards. It stops short of naming `logs_search` as the follow-up tool or saying when not to use this one (e.g., when you need message text), so it is clear context without explicit alternatives.

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