List content improvements

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

The description adds substantial behavioral detail beyond the annotations: ordering by priority, inclusion of open and completed items, default preference for open items, interpretation of empty results, formatting of enum labels for humans, and the setup-guidance fallback when no website exists. This goes far beyond the read-only and idempotent hints, providing comprehensive behavior for edge cases.

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 relatively long but every sentence adds value: it covers purpose, ordering, statuses, default behavior, empty results, formatting, and the setup fallback. It is front-loaded with the core purpose and maintains a logical flow. While not minimal, the length is justified by the range of behavioral nuances it conveys.

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 has no parameters, an output schema exists, and annotations declare safety, the description is complete. It explains what the tool returns, how to interpret results, special cases (empty list, no website), and formatting guidelines. Nothing an agent needs to call it correctly is missing.

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 zero parameters, so the description does not need to explain parameter meaning. The schema coverage is 100% (vacuously). The description adds context about output fields like status and impact, but since there are no parameters, the baseline of 4 applies without further enhancement needed.

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 a specific verb ('List') and resource ('content improvements for the account website'), with additional detail on ordering by product priority. This distinguishes it from sibling tools like list_topics or list_competitors, as it targets improvement recommendations rather than generic content lists.

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 clear usage guidance: 'Prefer open items unless the user asks for completed work' and 'When the user asks what to improve, lead with these product recommendations before any extra strategy.' It does not explicitly name alternatives, but the context is sufficient for an agent to decide when to invoke it, especially given the distinct purpose.

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