Counter distribution

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

With no annotations to lean on, the description does real work: it discloses the aggregation rule (each case contributes only its final counter value, so results are not summed events) and warns that both counters are derived from the activity sequence rather than raw columns. It omits that the operation is read-only and says nothing about cost or limits, which is the remaining gap.

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 sentences, each carrying distinct information: what is distributed, how rows are composed, and the data-provenance caveat. The key constraint is front-loaded and there is no filler.

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?

Purpose, aggregation semantics and output shape are adequately covered, and an output schema exists so return values need not be detailed. However, for a six-parameter tool with zero schema description coverage and no annotations, leaving five filter parameters entirely undescribed is a material gap.

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 0% across six parameters, so the description must compensate and mostly does not. It usefully enumerates the two legal values for the required 'metric' parameter, but priority, issue_type, report_channel, timestamp_from and timestamp_to are never mentioned, leaving their semantics and combination behavior to guesses from their names.

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 analysis (value distribution) over specific named metrics (reassignment_count, reopen_count) scoped to cases. It is distinguishable from the analytics sibling case_processing_duration by the resource it operates on, though it never names that sibling explicitly.

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?

Usage is only implied: an agent can infer this is the tool for counter histograms rather than duration analysis, but there is no explicit when-to-use, no when-not, and no named alternative. Nothing misleads, but routing between this and case_processing_duration is left to inference.

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