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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds that the output is prompt text to be pasted elsewhere, which is useful framing, but it says nothing about the non-idempotent behavior hinted at by idempotentHint=false or about whether repeated calls yield different prompts. With annotations doing most of the work, this is adequate but not rich.

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 with no waste: the transformation and its outcome come first, followed by the return value. Every clause carries information an agent would use.

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 a full schema and an output schema, the description need only justify the tool's role, which it does. The one gap is the unaddressed relationship to the sibling improve_prompt, which matters for correct tool selection in a two-tool family.

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%, so the baseline is 3. The description conveys the meaning of 'idea' through its examples, but adds no detail on how 'kind', 'framework' or 'written_for' affect the generated prompt beyond what the schema descriptions already state.

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 a specific transformation (rough idea into a detailed, structured prompt) with a concrete outcome ('ready to paste into an AI tool') and two illustrative inputs. It does not distinguish itself from the sibling improve_prompt, so an agent must infer the boundary from the tool names alone.

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 examples of idea inputs and by 'ready to paste into an AI tool', making the intended context understandable. However, there is no explicit guidance on when to pick this over improve_prompt, nor any exclusion stating that this tool creates a prompt from scratch rather than refining an existing one.

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