Generate Design Description

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

With no annotations, the description carries full burden. It discloses that results are randomized and that 'compatibility' controls chaos, but does not mention side effects (e.g., mutation), permissions, rate limits, or return value details beyond 'Markdown design direction'.

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 compact sentences. First sentence states core action, second provides critical usage condition. No superfluous words, front-loads the essential purpose.

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?

Given no output schema and no annotations, the description should clarify the return value (does it return the Markdown string or a reference?). It partially covers parameter usage but omits output structure and any behavioral constraints (e.g., rate limits, idempotency).

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 description explains the semantics of 'compatibility' and states that 'audience', 'priority', and 'productType' should be inferred and passed in English. However, it does not specify allowed values or formats for these string parameters, and the schema has 0% coverage, leaving ambiguity.

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 clearly states the tool generates a randomized frontend design direction in English Markdown. It specifies the output format and distinguishes itself from the sibling tool 'get_version' which has a completely different purpose.

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 specific guidance on when to set 'compatibility' to false (only on explicit user request for chaotic combinations) and explains that optional fields are inferred from context. While it does not explicitly list alternative tools, the sibling context makes the usage clear.

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