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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, so safety is covered. The description adds value the annotations cannot: that the result is whole-market public data rather than user-scoped data, which prevents a class of misinterpretation. It does not mention result limits, pagination, or whether an empty list means 'no tracked KOLs' versus 'untracked token', so it is not fully complete.

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 short sentences with the core definition front-loaded, followed by the sibling relationship and the data-scope caveat. The final get_my_ sentence is slightly tutorial-ish but earns its place as a broad disambiguation rule across a large sibling set. No filler.

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?

An output schema exists, so return-shape explanation is correctly omitted, and annotations cover the safety profile. For a two-parameter read-only lookup, the description supplies everything needed to decide to call it and interpret the result as market-wide rather than personal.

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 carries the full burden, and it barely does. 'This token' only obliquely implies the required token_address parameter, giving no format or network expectations, and the network parameter (const 'solana') is never mentioned at all. An agent learns nothing beyond the name of the concept being queried.

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+resource ('Tracked KOLs holding this token') and immediately defines the ambiguous term KOL as 'named public traders/influencers'. It also positions itself against siblings by calling itself 'the KOL-only slice of get_token_key_holders', so an agent can distinguish it from get_token_key_holders, get_whale_holders, and get_top_held without opening any schema.

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 gives a clear selection rule via the negative case: it is 'NOT about the user's own wallet or holdings', and get_my_* tools are the ones for personal data. That is a real disambiguation across a sibling list full of get_my_* tools. It stops short of explicit when-to-use framing such as 'use this when you need KOL conviction vs. all holders', leaving the choice against get_token_key_holders partly inferential.

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