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

With no annotations, the description carries the full burden, and it does disclose useful behavior: results are ordered 'newest filings first' and come from specific filing types. However, it says nothing about pagination, the 50-record cap interacting with paging, authentication needs, or the shape of returned records.

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 front-loaded with source and scope, followed by a necessary dataset list that compensates for the absence of an enum in the schema. The list is long but each entry earns its place; only the closing sort note could be tightened.

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 5-parameter, no-annotation, no-output-schema retrieval tool, the description covers sources and valid datasets but omits what each dataset actually returns, how ticker and date filters combine, and any result-shape expectations. Adequate but with clear gaps.

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 100%, so the baseline is 3, but the description adds real value by enumerating the valid dataset paths that the schema only illustrates with a single example ('e.g. board-oversight'). It does not clarify ticker-vs-CIK handling or date-range semantics beyond what the schema states.

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 the resource (structured governance data) and its provenance (proxy statements, auditor's reports, SEC enforcement releases) plus the full list of datasets, which lets an agent distinguish it from siblings like executive_compensation or audit_report_text. It lacks an explicit verb such as 'retrieve/list', so the action is inferred rather than stated.

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 dataset enumeration hints at what can be queried, but there is no statement of when to use this tool versus the numerous siblings (directors, executive_compensation, audit_report_text, enforcement) that overlap heavily. No prerequisites or exclusions are given.

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