stats

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

With no annotations, the description carries full behavioral transparency and does an excellent job. It discloses that source buckets freeze the reporter at first report (BT-4), that tag/meta groupings cross-tabulate cards into multiple rows causing totals to exceed finding counts, that auxiliary rows like 'population' and 'ungrouped_rows' appear on every axis, and that certain meta keys are refused (CB-167). These are non-obvious behaviors beyond the schema.

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 description is front-loaded with a one-line summary and every subsequent clause adds meaningful behavior. It is dense and somewhat run-on, making parsing more difficult than ideal, but no sentence is wasted.

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 tool with only one optional parameter and an output schema present, the description covers the parameter's allowed values, edge-case counting behavior, special output-row semantics, and an error condition. Nothing essential is missing for an agent to invoke it 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 0%, so the description must compensate for the undocumented group_by parameter. It lists all valid values, explains special semantics for source, tag, and meta:<key>, and documents the quoting restriction for meta keys. This is far more than the schema alone provides.

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 opens with 'Aggregated cross-tabulated counts', which names the output as counts and signals a multi-dimensional grouping operation. The group_by list (severity, category, status, file, source, tag, meta:<key>) makes the resource and dimension explicit. It is clear, though it does not explicitly distinguish itself from sibling tools like summary or categories.

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 implied: an agent can infer this tool is for retrieving aggregated counts over specified grouping dimensions. However, the description never explicitly says when to choose this tool over alternatives, and the sibling list contains several potentially overlapping reporting tools. There are no exclusions or alternative routing hints.

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