humanizer_compare_before_after

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

Annotations already declare readOnlyHint, idempotentHint, etc. The description adds detail on what metrics are shown (burstiness, vocabulary tells, structure, risk scores), which goes beyond annotations.

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?

Very concise with purposeful sentences. Front-loaded with purpose, followed by usage guidance, then structured parameter and return descriptions. No wasted words.

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 annotations and output schema present, the description covers purpose, usage, parameters, and return type. Could mention that the rewritten text should be from humanizer_humanize_text, but it's implied by context.

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?

Input schema has 0% description coverage, but the 'Args:' section in the description provides clear, human-readable explanations for both parameters, compensating well for the missing schema descriptions.

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 compares detection metrics between original and rewritten text. It distinguishes itself from siblings like humanizer_humanize_text and humanizer_analyze_ai_tells by focusing on side-by-side comparison.

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?

Explicitly says 'Use after humanizing to verify improvement', providing clear when-to-use context. Does not specify when not to use or alternatives, but sibling tools provide implicit differentiation.

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