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

The annotations already declare a safe read (readOnlyHint=true, destructiveHint=false). Beyond that, the description discloses the return structure (can_write, url, glyph, sharing) and the edge case that a model-scoped key returns only its bound model — real context not present in annotations.

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?

A single dense paragraph, front-loaded with the purpose and then the filter and edge-case details. Every sentence carries information, with no filler, though the packing of field names is slightly dense.

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?

With no output schema, the description usefully spells out the returned entry fields and the scoped-key caveat, and annotations cover the safety profile. Pagination, ordering, and total-count behavior are unaddressed but are minor for this read tool.

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 documents both parameters, establishing a baseline of 3. The description adds value by noting that a model-scoped key ignores the filters and returns only the bound model, refining the semantics of `q` and `writable` beyond the schema.

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 states a specific verb and resource ('Lists the models') plus scope ('the authenticated user can access'), and enumerates the entry fields. It never explicitly names a sibling like layerz_get_model to contrast single-vs-list retrieval, so it is clear but not sibling-differentiating.

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?

Filtering behavior is explained (`q` for name, `writable: true` for owner/editor), which implicitly guides usage, and the model-scoped-key note is a useful conditional. However, there is no explicit when-to-use-this-vs-alternatives guidance relative to get_model or the other list_* siblings.

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