optimize-prompt

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

With no annotations provided, the description carries the behavioral burden. It discloses the transformation process, mentions token awareness, and states the output includes tool sequence and savings estimates. However, it does not explicitly state whether the operation is non-mutating, whether it has side effects, or any limitations.

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?

The description is well-structured: a clear one-sentence definition, a brief process explanation, and a concrete example. It is appropriately sized and front-loaded, though the phrase 'for better Design System integration' adds little functional value.

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?

Even without an output schema, the description tells the agent what the tool returns: an optimized prompt with tool sequence, token savings estimates, and clear steps. It positions the tool clearly relative to the sibling set, but lacks explicit guidance on language handling or edge cases.

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 schema already documents the userPrompt parameter with 100% coverage, so the baseline is 3. The description adds an example and explains that the parameter should be a raw user prompt, but it does not add significant new meaning beyond what the schema 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?

The description uses a specific verb and resource: 'Transform raw user prompt into MCP-optimized prompt'. It also clarifies the tool's role as an orchestrator that guides Claude to use the right MCP tools, which visibly distinguishes it from the sibling component/documentation tools like list-components or generate-code.

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 context is implied: this is for taking a raw user prompt and converting it into a structured, tool-sequenced prompt. The example illustrates a concrete input, but there is no explicit statement about when to choose this tool over alternatives or when not to use it.

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