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

Annotations already declare a safe read operation (readOnlyHint true, destructiveHint false), so the description's real contribution is data-quality behavior: figures are approximate, lag 12–24 hours, omit small values, and may not reconcile with account totals. That reconciliation warning is exactly the kind of context an agent needs before reporting numbers, though it does not mention result size or row limits when detail=full.

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 with zero waste: purpose and dimension list first, scope second, data caveat last. Nothing needs to be re-read or unpacked.

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 9-parameter read tool with no output schema, the description covers the core purpose, dimension options, campaign scoping, and caveats. It stops short of saying what metrics come back or what 'summary vs full' costs, leaving the shape of the result partly unspecified.

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 78%, so the baseline is 3. The description adds modest value by clarifying that campaign scoping is optional and by naming the dimension choices, but folder, account, language, and date handling are left entirely 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?

A specific verb ('break performance down') plus a specific resource (LinkedIn professional-audience demographics), with the five supported dimensions spelled out. It is clearly distinguishable from linkedin_performance or linkedin_campaigns, though it never names those siblings explicitly to route the agent.

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?

'Optionally for one campaign' gives scoping guidance, and the dimension list implies when this tool is the right one. But there is no explicit when-to-use versus linkedin_performance or when-not, so usage must be inferred from the tool name and dimension list.

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