List campaigns

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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: it distinguishes `call` vs `recommended_call`, explains what backs the recommendation, and warns that quantile-named fields are null unless a calibrated component supplied them. That is substantive behavioral context, short only of return format/pagination detail.

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?

Front-loads the purpose and is dense but nearly every sentence carries field-semantics value; the trailing 'spend, retention, and payback' clause is somewhat tacked on but still informative. Jargon density (envelope_lower, marginal_endpoint_sum_no_joint_coverage) is heavy but tied to real field names.

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?

With no output schema, the description must explain return values, and it does so thoroughly for the headline profit/envelope fields and their caveats. It omits broader response shape and pagination behavior, which the schema partially covers, so it is strong but not exhaustive.

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 all six parameters (from/to/period/limit/cursor/app_id) are already documented in the schema, including mutual-exclusion of period vs from/to. The description adds nothing about parameters, so baseline 3 applies.

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 ('List ad campaigns') plus a distinctive scope ('honest profit surface'), which is more than a tautology. It does not, however, differentiate itself from siblings like list_ads or get_campaign_decision, so the agent must infer the boundary.

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?

Offers real guidance on interpreting the return (read aggregation_basis before quoting the low end; describe as a scenario when marginal_endpoint_sum_no_joint_coverage), but gives no explicit when-to-use versus alternatives and no selection criteria against sibling listing/decision tools.

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