ai-furniture-hub

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

With no annotations provided, the description carries the full burden. It describes what the tool returns (curated set information with product IDs) and suggests follow-up actions, but lacks details on behavioral traits like rate limits, authentication needs, error handling, or response format. It doesn't contradict annotations, but could provide more operational context.

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 efficiently structured in two sentences: the first explains the purpose with concrete examples and types, the second provides actionable follow-up guidance. Every sentence adds value with zero wasted words, making it easy to parse and understand quickly.

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 no annotations and no output schema, the description adequately covers the tool's purpose and basic usage but lacks details on behavioral traits, response structure, or error handling. For a tool with 6 parameters and no structured output documentation, it provides a functional overview but leaves gaps in operational context that could hinder effective use by an AI agent.

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 all parameters thoroughly. The description adds minimal value beyond the schema by mentioning examples like 'new life essentials' (relating to intent/occasion) and listing the four types (matching the enum), but doesn't provide additional syntax, format details, or usage examples for parameters beyond what's in the schema.

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 returns curated set proposals for specific scenarios like 'new life essentials' or 'YouTuber desk tour products', explicitly listing the four types (bundle, room preset, influencer pick, hack set). It distinguishes from siblings like get_product_detail or search_rakuten_products by focusing on curated sets rather than individual product details or general searches.

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 clear context for when to use this tool (to get curated set proposals) and mentions calling get_product_detail or search_rakuten_products for detailed product information and purchase links, implying alternatives for different needs. However, it doesn't explicitly state when not to use it or compare directly with all sibling tools like suggest_by_space or get_popular_products.

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