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

With no annotations, the description does the heavy lifting: it discloses partial/case-insensitive matching, defines the director pool, explains the cited_case_matches semantics, and gives concrete example values. This is rich behavioral context that goes well beyond the bare schema.

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 fairly long but well organized: purpose, domain context, use cases, examples, then Args. All content contributes, with only a minor redundancy in the publication-type enumerations keeping it from being perfectly tight.

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 tool with no required parameters and an output schema, the definition covers the core invocation needs thoroughly. The one material gap is the ambiguous set of accepted publication_type values; otherwise an agent can call this tool correctly from the description alone.

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 coverage is 0%, so the description must explain each parameter, and it largely does: matching rules, examples, and allowed type names. The only blemish is that the publication_type argument lists four categories while the prose earlier had mentioned five, leaving it unclear whether Reports and Briefs & Testimony are valid filter values.

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 clear verb and resource: 'List publications from the Engelberg Center on Innovation Law & Policy at NYU Law,' and enumerates the three filter dimensions. This immediately distinguishes it from the sibling tools (search, fetch, fetch_document), which are not listing tools.

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?

It explicitly says to use this tool to browse available sources before searching, to find all work by an author, or to find publications discussing a case. This covers most selection situations, though it never names the search/fetch siblings or says when NOT to use this tool.

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