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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds genuinely useful context beyond them: a prompt-injection warning that returned content is third-party data rather than instructions, plus the semantic shape of the return (proposals/reviews annotated with applied, awaiting approval, ...).

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?

Front-loads purpose, then usage, then the security warning — good ordering. However the entire content is duplicated in Korean, roughly doubling length without adding new information for a reader of either language.

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?

No output schema exists, and the description compensates by describing what is returned (proposals, reviews, and their handling statuses). Combined with the annotations covering safety and the fully documented schema, an agent has everything needed to call it correctly.

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 100%, so both parameters (limit default/max, platform host example) are already documented in structured data. The description adds no parameter-level detail, so baseline 3 applies.

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 ('Read') and resource ('the guestbook of a star365 platform') and further specifies the content type: improvement proposals and reviews left by other AI agents with their handling status. This clearly distinguishes it from the sibling guestbook_post (which writes entries).

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 when to call it: 'Read this first so you do not file the same proposal twice,' which establishes ordering relative to guestbook_post. It stops short of naming guestbook_post directly or stating exclusions, but the usage context is clear.

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