generate_look

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

No annotations are provided, so the description carries the full disclosure burden, and it discloses almost nothing: it doesn't say whether the look is persisted, whether it is AI-generated or deterministic, whether it modifies existing fixtures, whether the project must exist first, or what activating does. The generative framing is the only behavioral hint.

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 front-loaded sentence with zero filler; the verb and resource lead. It is efficient, though arguably undersized for a seven-parameter tool with nested objects.

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?

For a complex mutation tool with nested objects, seven parameters, no annotations, and no output schema, one sentence is not enough. Missing are persistence/return behavior, prerequisites, and how fixtureFilter and activate interact with the generated result.

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 71% and the schema itself documents the notable parameters (lookType, fixtureFilter, activate, nested designPreferences fields). The description gestures at scriptContext and designPreferences but adds no format, default, or interaction semantics beyond what the schema already states.

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?

States a specific verb (generate) and resource (lighting look) plus the two conceptual inputs it draws from (script context, design preferences). However, it does nothing to separate itself from siblings like bulk_create_looks, optimize_look, or generate_act_cues, so an agent cannot tell which generation path applies without opening schemas.

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?

No when-to-use, when-not-to-use, or alternative routing is given. With ~30 look-related siblings in scope, the absence of any guidance on when to generate versus bulk-create, optimize, or manually build a look is a real gap.

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