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

The readOnly and destructive annotations already cover safety, and the description adds meaningful behavioral context: Instagram/Facebook/Threads return follower breakdowns while LinkedIn returns lifetime demographics with different fields. This goes beyond annotations without contradicting them.

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?

Two concise sentences, front-loaded with the primary purpose, and the second sentence adds valuable platform distinctions without repetition. Every sentence earns its place.

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?

The description gives platform-specific return expectations, but lacks full context for correct invocation: no explanation of the 'breakdown' enum meaning, the 'locale' parameter, or whether LinkedIn's seniority/industry are returned regardless of breakdown. With no output schema, more detail would be warranted.

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 compensate for parameter meaning, but it does not explain 'breakdown', 'locale', or 'accountId' explicitly. It only hints at 'platform' by naming platforms. This leaves key parameters under-specified.

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?

The description uses a specific verb ('Return') and resource ('audience demographics for a connected social account'), immediately distinguishing it from post-level analytics siblings. It further clarifies platform-specific outputs, making the tool's scope unambiguous.

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 when to use the tool—when follower demographics are needed—and provides platform-specific expectations. However, it does not explicitly state when not to use it or mention alternatives like get_account_analytics.

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