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

Beyond the annotations (which already declare readOnly/idempotent/non-destructive/openWorld), the description discloses the authorization scope, the pagination contract via nextOffset, how pending requests are dated, and the critical labeling caveat that API probes are not consumer ChatGPT evidence. These are non-obvious behavioral facts an agent could not get from structured fields.

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-loaded with the resource and scope, then prerequisites and caveats, then the endpoint. It is dense and semicolon-chained, and the trailing caveats compete with the core purpose, but no sentence is filler.

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 five-parameter, nested-object read tool with no output schema, the definition covers authorization, date semantics, pagination, and explicit non-goals, which is what an agent needs to call it correctly and interpret the results honestly.

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 carry parameter meaning. It explains dateBasis semantics (observed_at default vs created_at) and that dateRange is inclusive UTC, but leaves limit, offset mechanics, and sourceKind values implicit or unaddressed beyond enum labels in 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?

States a specific verb ("Read") and precise resources: tenant-bound historical API probes plus separately labeled user-supplied ChatGPT observations. The negative scope ("no population visibility score or inferred enquiries/revenue") implicitly separates it from summary-style siblings, but no sibling is named, so an 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?

Gives clear operating context: requires marketing:read, follow nextOffset for pagination, and use dateBasis=created_at when recording dates are wanted. It also states what the tool does not deliver, which steers agents away from misusing it as a scorecard. It stops short of naming the alternative tool to use for those aggregates.

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