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

With no annotations provided, the description carries the full burden. It discloses that each row contains 'proof bytes and a citable page', which is valuable behavioral detail about the output. It also states the covered states (CO, CT, NY, TX). While it doesn't mention read-only status or performance characteristics, the tool is clearly a query tool, and the description adds meaningful context beyond just the function name.

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 sentences with a clear flow: purpose first, then interpretive guidance, then filter and output details. It's front-loaded with the core intent and avoids redundancy. Every sentence adds new information, making it both concise and well-structured.

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?

Given there is no output schema and no annotations, the description does a good job covering essential aspects: purpose, filters, field semantics, output content, and state coverage. It omits some details like default sorting or pagination, but those are likely minor for a query tool. The description is sufficient for an agent to invoke it correctly in most cases.

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%, so parameters are documented. The description adds value by explaining the semantic significance of fields (e.g., agent change signals a sale), which helps the agent choose the right field parameter. It also explicitly lists the allowed field values and the date filter format, reinforcing the schema. This goes beyond the baseline 3 for high coverage.

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 clearly states the tool finds companies that changed recently across a state or field, contrasting with single-company lookup. It gives concrete examples of change types and their business meaning, making the purpose specific. However, it doesn't explicitly distinguish itself from the sibling 'private_what_changed', which might be similar, so it lacks direct differentiation.

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 says it's for finding corporate events 'rather than looking one company up', which provides a general usage context. It implies use cases like spotting sales or dissolved companies via changes. However, it doesn't name any specific sibling tools or state when NOT to use it, leaving the agent to infer alternatives from the sibling list.

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