Create summary table

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

Annotations already declare destructiveHint=true, readOnlyHint=false, and idempotentHint=false, so the safety profile is covered. The description adds genuinely useful behavior beyond that: the output is static and does not update when the source changes, only numeric values are summed/averaged/compared, count counts non-empty cells, and formula cells are not evaluated. It does not state that existing content at target_cell/target_sheet is overwritten, which is the one behavioral 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, front-loaded with the core operation, then the static/non-updating caveat, then the aggregation semantics. No filler and every sentence carries distinct information.

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?

An output schema exists, so return values need no explanation, and the description covers the aggregation behavior and the staleness trait thoroughly. It is slightly short of complete because it omits what happens to pre-existing content at the target location and any required conditions on the source range.

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 100%, so the baseline is 3; the schema already documents path, sheet, source_range, target_cell, target_sheet, group_by and values. The description nevertheless adds real meaning about the 'values' aggregation semantics — which aggregation functions apply to numeric vs non-empty cells and that formulas are ignored — clarifying behavior the enum alone does not convey.

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 and resource ('Group rows and aggregate columns... writing the result as cells') with an analog ('like a pivot table') that makes the operation immediately graspable. It clearly distinguishes the tool from siblings such as create_table and create_chart by specifying that it produces a static aggregated result rather than a table object or a visual.

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 implies the use case (grouping and aggregating into a summary) and clarifies it is not an Excel PivotTable, which hints at when to prefer it. However, it never states when to use this versus create_table, write_range, or a live pivot, nor does it mention prerequisites such as existing source data. Usage is inferable but not spelled out.

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