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

Annotations already declare readOnlyHint=true, openWorldHint=false, and idempotentHint=true. The description adds a meaningful behavioral caveat: 'Peer review records are self-reported or imported by participating publishers — coverage varies by researcher.' This discloses potential data incompleteness, which is not captured in annotations and is important for interpreting results. No contradiction with annotations exists.

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?

The description is three concise sentences with zero redundancy. The first sentence front-loads the core purpose and field list, the second states the use case, and the third provides an essential data-quality caveat. Every sentence adds value, and the structure is tight and scannable.

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?

For a simple getter with one fully-documented parameter and an existing output schema (which obviates the need to explain return values), the description covers all essential context: what the tool retrieves, when to use it, and a critical caveat about data coverage. Nothing an agent needs to decide whether and how to call it is missing.

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%; the single parameter orcid_id is fully documented in the schema (format, bare URI, pattern). The description does not add additional parameter semantics beyond what the schema already provides. Since the schema carries the full burden, the baseline of 3 is appropriate.

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 states a specific verb ('Fetch') and resource ('peer review activity for an ORCID researcher') and enumerates the exact data points returned (convening organizations, reviewer role, review type, completion dates, ISSN-keyed group identifiers). This clearly distinguishes it from sibling getters like orcid_get_works or orcid_get_affiliations, which target different record types. The scope is unambiguous.

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 provides a clear use case: 'Use to assess editorial activity, journal affiliations, and the scope of a researcher's peer review contributions.' This tells an agent when to invoke the tool, but it does not explicitly contrast with alternatives (e.g., 'use this instead of works for review data'). Given the sibling names are self-explanatory, the lack of explicit exclusions is minor but still leaves the when-not-to-use guidance implicit.

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