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

The description transparently discloses that the tool advances internal state: the fingerprint slides forward for company watches and the registration-date cutoff slides forward for CAEN watches. It also notes persistence across restarts and the first-time baseline effect, fully revealing side effects.

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 well-organized into two paragraphs but contains slight redundancy in explaining the baseline for both company and CAEN watches. It could be tightened without losing clarity, but it remains efficient.

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?

The description explains the conceptual content of the changeset (updated entries with changed fields, new firms) but does not describe the exact return format or structure. Since there is no output schema, the description should provide more detail on the shape of the response, and it also omits potential error conditions.

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?

The tool has no parameters, and the schema is empty. Since there are no parameters to clarify, the description fully covers all relevant input aspects by omission.

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 polls all watches for the calling customer and returns a changeset. It distinguishes between company and CAEN watch behaviors, making the purpose specific and unambiguous.

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 explains the polling mechanism and the baseline behavior, which implicitly indicates when to use this tool (to retrieve updates after a watch is set). However, it does not explicitly contrast with sibling tools like watch_company or watch_caen, which would clarify when not to use it.

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