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

Annotations declare openWorldHint=false, meaning absence of a value implies absence in the real world (closed-world). The description explicitly states the opposite: 'Absence of funding records does not imply absence of funding' — the open-world position. This directly contradicts the annotation, giving the agent conflicting guidance on how to interpret missing data.

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?

Five sentences, each earning its place: purpose, return fields, the self-reporting caveat, the absence implication, and the value statement. Purpose is front-loaded and the caveat is placed before the value claim for logical flow. 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?

For a single-parameter read-only tool with a full output schema, this is complete. It states what it returns, warns about data incompleteness, and explains when the results are valuable — an agent can invoke it and interpret the response 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% for the single orcid_id parameter, including the pattern and accepted formats (bare or full URI). The description adds no further parameter details, so it neither raises nor lowers the baseline of 3.

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 ('Fetch funding records for an ORCID researcher') with enumerated record types (grants, contracts, awards, salary awards) and the returned fields (funder names, org identifiers, grant numbers, funding periods). The funding focus clearly differentiates it from siblings like orcid_get_works and orcid_get_affiliations.

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?

Provides clear interpretive context: funding data is 'entirely self-reported' and 'high-value for grant tracking and funder analysis'. It tells the agent when results are meaningful, though it does not explicitly contrast with sibling tools or state when to prefer an alternative.

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