list_looks

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

With no annotations, the description carries the full disclosure burden and discloses almost nothing: it does not say whether the call is read-only, what it returns, how many looks exist, or whether IDs are needed downstream. Only the weak implication that it feeds apply_look adds any behavioral context.

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?

Six words, front-loaded, zero filler or repetition of the tool name. It is efficiently sized, though the terseness borders on under-specification rather than pure conciseness.

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 and no annotations, the description should at least convey the return shape (e.g. that it yields identifiers consumable by apply_look). That critical link between the two tools is left entirely implicit for a tool whose only purpose is to supply that input.

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 schema has zero parameters, so the baseline is 4; there is nothing the description needs to disambiguate. It correctly mentions no args.

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 names the resource (ready-made looks) and links it to the sibling apply_look, which is the main thing an agent needs to place it. But it is a noun phrase with no explicit verb, so the 'list' action is only inferable from the tool name.

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?

Mentioning apply_look implies this is a prerequisite/enumeration step before applying a look, but it never states when to call it, when not to, or what to do with the results. No explicit sequencing or exclusions are given.

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