generate_policies

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

Annotations already declare readOnlyHint=true and destructiveHint=false, establishing the tool as non-destructive. The description adds that the tool returns Markdown and tailors documents to markets, providing behavioral context beyond annotations. No contradictions are present.

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 long: the first defines the core purpose, and the second adds a critical usage hint. Every sentence earns its place, with no wasted words. It is front-loaded and immediately informative.

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 description explains the output format (Markdown) and the workflow dependency (answers from scan_project), but lacks details about the structure of the returned Markdown or the semantics of parameters like locales and markets. Given 6 parameters and no output schema, more completeness would be beneficial.

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 description coverage is only 33% (2 of 6 parameters have descriptions). The description adds value by explaining the 'answers' parameter's role (passing suggestions from scan_project) and listing recognized keys, compensating for the schema gap. However, no additional meaning is provided for other parameters like 'locales' or 'markets' despite their importance.

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 generates legal documents (privacy policy, terms of service, AI disclosure) localized to target markets. It specifies the verb 'Generate', the resource 'legal documents', and includes details about localization and return format (Markdown). This is unique among siblings, none of which generate documents.

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 provides explicit context by mentioning to pass scan_project's suggestedAnswers as the 'answers' parameter, indicating a recommended workflow. It does not explicitly state when not to use the tool or list alternatives, but the guidance is clear enough for an agent to understand the typical usage scenario.

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