Log Summary

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

No annotations exist, so the description carries the full burden. "Count logs" implies a read-only aggregation, and the date-bounds requirement is real operational context, but it says nothing about return format, pagination, or the sampling/limit behavior implied by the 35-parameter schema. It adds some value without covering the behavior an agent needs.

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?

Three short sentences, purpose front-loaded, with each sentence carrying distinct information (what it does, when to call it, a precondition). It is tight and waste-free, though slightly terse for a tool of this complexity.

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?

For a 35-parameter tool with no annotations and no output schema, three sentences are inadequate. Key behaviors (grouping output shape, sampling, range caps implied by allowLongRange, exclusion filters) are left unexplained, and the "requires date/time bounds" claim sits oddly against a schema with zero required parameters.

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 57%, so the schema documents roughly half the parameters. The description adds the group-by semantics (counting by level, namespace, pod, container) that map to loglevel/namespace/pod/container, which is useful, but it gives no syntax or meaning for the other ~30 parameters such as sample, window, allowLongRange, or exclusion filters.

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?

States a specific verb (count) and resource (logs) plus the aggregation dimensions (level, namespace, pod, container), which clearly separates it from raw-line siblings like dynatrace_search_logs or dynatrace_pod_logs. It stops short of naming any sibling explicitly, so it is clear but not maximally differentiated.

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?

"Call this before fetching raw lines" gives concrete workflow positioning relative to line-fetching alternatives, and "Requires date/time bounds" states a precondition. There is no explicit when-not-to-use guidance, but the sequencing guidance is genuinely actionable.

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