Optimize Prompt

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe, repeatable operation. The description adds valuable context about the tool's behavior: it returns a scaffold with score metrics, detected issues, and applied techniques, which goes beyond the safe-read nature. It does not describe any side effects, but the annotations cover that, and the output details provide transparency about what the tool produces.

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 two sentences, front-loaded with the primary action and followed by a concise summary of the return value. Every word earns its place; there is no fluff or repetition. It is highly efficient and well-structured.

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?

The tool has 4 parameters and no output schema, so the description must explain return values clearly to compensate. It does so by stating the optimized prompt scaffold includes score metrics, detected issues, and applied techniques. This is sufficient for a moderate-complexity tool with no siblings and no side effects. However, it could elaborate on how the target environment or techniques influence the output, leaving a minor gap.

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 input schema has 100% parameter description coverage, with each parameter (intent, prompt, target, techniques) carrying a clear description. The tool description does not add any parameter-specific semantics beyond what the schema already provides, so the baseline of 3 is appropriate. The schema itself is well-defined, making the description's lack of parameter detail acceptable.

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 analyzes and optimizes prompts using Anthropic best practices, which is a specific verb-resource pairing. It also distinguishes the tool's output by mentioning the optimized prompt scaffold with score metrics, detected issues, and applied techniques, leaving no ambiguity about its function.

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 conveys a clear context: use this tool when you want to optimize a prompt. It does not explicitly state when not to use it or mention alternatives, but since there are no sibling tools, the context is sufficient. The phrase 'using Anthropic best practices' implies a specific methodology, but it could benefit from more explicit usage guidance.

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