analyze-request

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

No annotations are provided, and the description does not disclose behavioral traits such as side effects, rate limits, or read-only nature. It only describes the analysis output without mentioning boundaries or constraints.

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 moderately concise and uses bullet points for clarity. However, it redundantly lists the insights after stating them, slightly reducing efficiency.

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 input schema covers all parameters. Without an output schema, the description partially compensates by listing the types of insights (complexity, intent, strategies), but it lacks precise format or field details, making it incomplete for agents needing exact return structure.

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%, with both parameters (request, domain) described in the schema. The description repeats the schema's descriptions without adding significant new meaning, so it meets the baseline but does not exceed it.

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 user requests to provide insights on complexity, intent, and optimization recommendations. It lists specific outputs and distinguishes itself from sibling tools (betterprompt, quick-enhance) by focusing on analysis rather than enhancement, as indicated by the mention of understanding how BetterPrompt would optimize.

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 implies use for analyzing requests before optimization, stating it helps understand how BetterPrompt would approach a request. However, it does not explicitly exclude alternative use cases or provide when-not-to-use guidance.

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