recommend

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool does (returns recommendations in four categories), provides context about recommendation types, and explains how to interpret results. It doesn't mention rate limits, authentication needs, or error handling, but covers the core behavior well for a read-only recommendation tool.

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 with clear sections (Usage, Recommendation Types, When to Use, Finding New Features, Result Interpretation) and uses bullet points effectively. It's appropriately sized for the tool's complexity, though some sections could be more concise. Every sentence adds value, with no redundant information.

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?

Given the tool's moderate complexity, no annotations, but with an output schema (implied by 'Returns' section), the description is complete. It explains what the tool does, when to use it, how recommendations are categorized, how to interpret results, and includes practical examples. The output schema handles return value documentation, so the description appropriately focuses on usage 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?

Schema description coverage is 100%, so the schema already documents the single 'url' parameter. The description adds minimal value beyond the schema, only mentioning the parameter in the 'Args' section without additional context. The baseline score of 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'Get content recommendations for an AWS documentation page' and 'provides recommendations for related AWS documentation pages based on a given URL.' It distinguishes itself from sibling tools (read_documentation, search_documentation) by focusing on recommendations rather than direct content retrieval or search.

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 guidance on when to use this tool with a dedicated 'When to Use' section listing five specific scenarios, including 'After reading a documentation page to find related content' and 'To find newly released information.' It also includes a 'Finding New Features' subsection with step-by-step instructions, clearly differentiating use cases from alternatives.

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