Landscape & garden design (Landscape AI)

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

Annotations already cover the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true). The description adds the non-obvious fact that each call costs 1 credit, which is real operational context an agent needs before invoking. It stops short of explaining result retrieval or latency.

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?

Two sentences, zero filler, with the core action front-loaded and the cost constraint placed last. Nothing is redundant with the title.

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 an 8-parameter generative tool with no output schema, the description covers the core action and cost but says nothing about how the result is obtained — notable here because the sibling set includes luw_get_result, implying asynchronous job handling the agent must know about.

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 description coverage is 100%, so all 8 parameters are already documented, and the description's mention of 'climate and sun exposure' only loosely maps to city/sun_exposure. Baseline 3 is appropriate since the schema does the heavy lifting.

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 and resource: designing a garden/yard/outdoor area inside a masked region of a photo, with plants selected for climate and sun exposure. This is more precise than a generic 'edit image' sibling, but it never names or differentiates itself from luw_exterior_design or luw_render, which an agent might reasonably confuse it with.

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?

Usage is implied by the requirement that the work happen 'inside a masked region of a photo', which tells the agent the mask_image prerequisite. However, there is no explicit when-to-use versus siblings (e.g. exterior_design vs landscape_design) and no guidance on when a plain edit_image would suffice.

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