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

With no annotations, the description bears the full burden. It reveals that the tool shows a formatted table, but does not disclose whether it is read-only, if it modifies data, or any authentication or rate limit requirements. The behavioral traits beyond output format are unclear.

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 brief and to the point. It starts with the core action, provides examples, and includes specific usage notes, all in a few sentences with no wasted words.

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?

Given 13 parameters, no schema descriptions, no output schema, and no annotations, the description is insufficient. It only addresses a few parameters and does not cover the full range of inputs, outputs, or behaviors needed to use the tool confidently.

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%, so the description must compensate. It explains scenarios (including alias requirement) and implies dimensions and metrics, but 9 out of 13 parameters (scale, layout, target, filters, etc.) receive no explanation, leaving significant gaps for correct invocation.

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 clearly states what the tool does: breaking metrics down by a dimension with examples like revenue by project or utilisation by employee. It uses a specific verb-resource pair and distinguishes from sibling tools like run_metric_data and run_statement by focusing on dimensioned metric analysis.

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?

The description provides clear guidance on when to use the tool and gives specific instructions for passing scenarios with aliases. However, it does not explicitly state when not to use it or contrast with alternative sibling tools, missing some usage boundaries.

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