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

Annotations already cover the read-only and non-destructive nature of the tool. The description adds valuable behavioral details: it returns rule text, penalty notes where available, and official source URLs; it also states that the tool will not guess a date if formationDate is missing, instead prompting the user. This goes beyond standard annotations and is useful.

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 composed of three efficient sentences, front-loaded with the purpose and followed by usage conditions and a key behavioral constraint. It is well-structured and contains no unnecessary filler, though it could be slightly more concise by combining some phrases.

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 the tool's complexity (computation + data retrieval), annotations (read-only), and the absence of an output schema, the description is largely complete for an agent to invoke it correctly. It explains the outputs and the conditional parameter requirement, but lacks details on the format of the returned rule text or amount (e.g., currency) – minor 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 schema already defines the parameters. The description adds meaningful context about formationDate: it is required for anniversary- and quarter-based states, and the tool will indicate its absence without guessing. This extra information helps the agent understand when and why to supply the parameter.

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 specifies the exact calculation performed (next annual report or franchise tax due), the input scope (given state), and the additional outputs (amount owed, rule text, late-filing consequences, source URLs). It clearly distinguishes this tool from siblings like get_llc_fees or check_llc_name, which serve different purposes.

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 explicit usage triggers: when the user asks when the annual report is due, how often it is filed, or what happens if it is late. It does not explicitly name alternative tools, but the context is clear enough that an agent can infer this is the right tool for deadline-related queries.

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