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

Goes well beyond the annotations: it declares the tool is deterministic ('does not invent numbers or reasons'), that highlights are derived only from computed changes, that rates are recomputed from totals (CTR = clicks / impressions), and that inputs must be supplied rather than fetched. That is substantive behavioral disclosure that readOnlyHint/openWorldHint alone cannot convey.

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 first sentence is front-loaded with triggers and inputs, and the negative-constraint sentence is short and high-value. However the opening sentence is a long run-on enumerating many cases, and the dense prose could be more clearly segmented into discrete sentences.

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 16-parameter tool with nested objects and all-optional inputs, the description covers when to use it, what inputs are acceptable, what it computes, and what it returns. With an output schema present and 100% parameter coverage, nothing an agent needs in order to call it correctly is missing.

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 already 100%, so 3 is the floor; the description still adds routing value by explaining what forms 'metrics' can take and by naming the concrete export sources that map onto the data/file parameters. It adds context rather than restating the schema, though per-parameter mechanics (date_order, pair_order, paper) are left to the schema.

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?

Names a specific verb+resource ('generate a client report') and immediately scopes the accepted inputs (typed metric pairs, pasted table, uploaded CSV/Excel from GA, Search Console, Meta Ads, Shopify) and the artifacts produced (PDF, Excel, CSV). An agent can tell this is a report-builder, not a metrics-analysis utility, without opening the schema.

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?

Strong when-to-use framing ('Use this when the user wants a weekly or monthly client report...') and explicit exclusions ('Does not connect to analytics or ad accounts... is not for forecasts'), which pre-empts a common misroute. It does not name the sibling summarize_metric_changes or state the boundary between the two, so the alternative is left implicit.

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