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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely new operational context with 'free, no key' (no auth/API-key requirement), which is not derivable from the annotations.

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 tight clauses: what it searches, what it returns, and how to route. Purpose and the sibling alternative are front-loaded with no filler sentences.

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 structure need not be detailed, yet the description still previews the key fields. For a simple two-parameter search tool, purpose, auth model, and sibling routing are all covered.

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%, including limit bounds ('max 100') and a query example, so the schema carries the parameter burden. The description adds only an implicit sense of free-text querying and no syntax or format detail beyond the schema.

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 and resource ('Search DataCite for research-data DOIs') and immediately scopes it to datasets rather than articles. It also names the exact sibling to use for articles, so an agent can disambiguate without opening either 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?

Explicitly gives the use case ('find citable datasets and their metadata') and routes the competing case to an alternative ('use crossref_works for articles'). The when-to-use and when-to-use-something-else conditions are both present.

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