list

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

With no annotations, the description carries the full behavioral burden, and it succeeds: it reveals the return type, sort order, optional `head*` fields, and their meaning. It adds actionable warnings about reading `headNote` and building from `latestLeaf` before making changes.

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 compact but information-dense, front-loading the core list function before diving into field semantics and usage caveats. Every sentence adds value: return shape, sort order, head-field interpretation, and routing guidance.

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?

Despite the lack of an output schema, the description documents the return object fields and their significance. It also covers when to use the tool and warns about destructive follow-up behavior, leaving no critical gap for an agent to call or act on this tool safely.

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 there is no schema detail to explain; the baseline for 0-parameter tools is 4. The description instead enriches the call semantics by explaining what the returned fields mean.

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 opens with a specific verb and resource: 'List designs in the workspace,' immediately establishing the tool's core function. It also defines the returned shape and ordering, and distinguishes the purpose from sibling mutation tools like `edit`.

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?

It explicitly states when to use the tool ('when the user asks what designs exist or wants to resume earlier work'). It also gives targeted guidance about what not to do—seeing a design is not a reason to continue it—and directs new-design requests to `edit` with `parent: null`.

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