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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so safety is covered. The description adds real behavioral context beyond that: result shape (rows=dimension, columns=metrics×scenarios), returned artifacts (raw figures plus a `data_ref`), and the constraint that it renders no user-facing table.

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?

Dense but front-loaded: purpose first, then result shape, then the scenarios/alias instruction, then the data_ref handoff. Nearly every sentence carries information, though the scenarios instruction and return-value notes make it longer than strictly necessary.

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 covers return values and the chart handoff, which partly compensates for the absent output schema. However, for an 8-parameter tool at 0% schema coverage with no output schema, the majority of inputs remain unexplained, so it is only minimally adequate.

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 8 parameters, so the description carries the full documentation burden. It clarifies only `scenarios` (pass explicitly, give each a concise user-facing `alias`) while scale, decimals, filters, dimensions, period_start/period_end, and metrics are entirely undocumented.

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+resource ('break one or more metrics down by a dimension') with concrete examples (revenue by project, utilisation by employee). It also implicitly distinguishes itself from the sibling run_metric by noting it 'does not show the user a table' and returns raw figures instead.

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?

Tells the agent when to reach for it (own analysis, or to build a chart) and names the downstream alternative by instructing the agent to pass `[data_ref]` as `data_refs` to eval_chart_transform. No explicit 'do not use when' clause, but the usage path is clear.

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