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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that the data is 'preloaded' (static, not live-queried), implying no pagination or freshness concerns, but it never states that the call is read-only, whether the list is bounded in size, or when the preloaded set was last updated.

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 short sentences with zero filler. The 'what it returns' statement is front-loaded, followed immediately by the actionable chaining instruction.

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 output schema, the description must sketch return contents, and it does (address and chain per whale). It is nearly sufficient for a zero-param list tool; only the absence of any statement about the list's static nature or size leaves a small gap.

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 there are no argument semantics to explain; baseline 4 applies. The description correctly implies a no-argument enumeration rather than suggesting filters that do not exist.

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 (Lists) and resource (known whales), then enumerates the entity categories covered (exchanges, funds, public figures, governments) and the returned fields (address, chain). An agent can distinguish this from get_whale_activity, which it explicitly routes to as a downstream consumer.

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?

Explicitly tells the agent how to use the output: 'Use the addresses as input to get_whale_activity,' which names the alternative/next tool and the condition for calling it. It does not state when this tool should be skipped or what to do if a whale of interest is absent, so it stops short of full when/when-not guidance.

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