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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and a closed world, so the safety profile is covered. The description adds genuinely new behavioral context on top of that: the response content varies by subscription tier, with certain metrics and a wider top-N list appearing only on Pro. That plan-dependent variability is exactly the kind of thing annotations cannot express. It stops short of 5 because it says nothing about rate limits, caching, or freshness of the 24h figures.

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?

It is a single sentence with the head noun 'Totals' front-loaded, and each semicolon-delimited clause adds a distinct output group rather than padding. The density is high but the clause-per-metric structure is slightly hard to parse at a glance compared with a short bulleted list.

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 input schema properties and no output schema, the description bears the full burden of explaining what comes back, and it does so metric by metric, including the tier-dependent differences. Minor gaps remain: terms like 'kind', 'underlying quote', and 'median absolute premium' are used without definition, so an agent must infer them.

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?

The tool takes zero parameters, so the schema carries no parameter semantics to miss and the baseline of 4 applies. The description correctly does not invent parameters, and instead spends its words on return content.

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 names a specific resource (tokenized equities) and enumerates exactly what the tool aggregates: token count, market cap, 24h volume, issuer/kind breakdowns, top underlyings, and premium statistics. That enumeration alone separates it from siblings like list_tokenized_equities and get_tokenized_equity, which return individual assets rather than computed totals.

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?

Usage is implied: this is the aggregate-overview call, contrasted implicitly with the per-asset list/get tools. It also discloses useful tier gating (top 5 on Free, top 10 on Pro; premium metrics Pro-only), which tells the agent what it will actually receive. However, it never states when to prefer this over list_tokenized_equities or rwa_market_summary, so the guidance remains inferential.

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