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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the description's real contribution is the interpretive caveats: 'Prices are not orders; claims are unaudited.' That tells the agent how to treat the numbers, which structured fields do not convey. It stops short of noting any staleness, coverage limits, or empty-result behavior.

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?

Leads with the returned data, then the optional parameter, then the two caveat clauses — front-loaded and free of filler. The first sentence is a dense parenthetical list that takes effort to parse, but every element 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?

With an output schema present and full annotation coverage, the description does not need to explain return shapes; it still helpfully categorizes them and flags the trust caveats. The remaining shortfall is the missing account_id semantics and the absent routing guidance against sibling monetization/analysis tools.

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 the parameter; it only says 'Optional account_id' without stating whose account identifier it is, its expected format, or what the response looks like when it is omitted. Optionality is already implied by the schema's empty required list, so this adds little beyond a restatement.

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 resource and enumerates exactly what is returned (offers, localized presentment observations, seller counters, revenue claims/observations, counts by offer type) for AI monk accounts. That is far more specific than the title alone and clearly separates it from get_ai_monk/search_ai_monks, though it never names a sibling to reinforce the distinction.

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?

There is no statement of when to call this versus get_ai_monk, ai_monk_index_stats, or winning_playbooks, and no guidance on what changes when account_id is supplied versus omitted. The audience must infer the intended use (per-account or aggregate monetization view) entirely from the tool name.

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