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

Annotations provide no safety hints (all false), so the description carries the behavioral burden. It adds a rate limit, a separate ordering step, and the output shape. It does not fully describe side effects (e.g., whether the design is persisted and retrievable via get_design), but the workflow hint ('before you order') helps clarify that this tool does not place an order or plant a tree.

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?

Four short sentences with zero filler: purpose, output, rate limit, and workflow instruction each earn their place. The main purpose is front-loaded, followed by concrete constraints an agent needs to call the tool correctly.

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 compensates by naming the return values (design_id and tree genome). It covers rate limiting and the required user-facing step. It could mention persistence or error cases, but for a single-parameter tool with full schema coverage, this is largely complete.

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%, and the schema already describes the wish parameter, its length range, and the 'no brands, logos or text' constraint. The description's example ('a silver birch with lanterns') adds a helpful illustration, but this is marginal value beyond the schema; the baseline of 3 is appropriate.

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 ('Turns') and resource ('a short wish... into a custom tree design'), then specifies the output ('design_id and the tree genome'). This clearly distinguishes it from sibling tools like get_design, plant_tree, and start_sponsorship, so an agent can immediately tell what this tool does and how it differs.

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?

The description gives actionable workflow guidance: 'Show the result to the user before you order,' which implies this tool is for the design phase, not ordering or planting. It also adds a rate limit ('Max 3 designs per caller per day'). It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to infer when to use it.

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