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 of behavioral disclosure. It describes key behaviors: returns a comparison table, includes additional catalog-matched data (internal dimensions, compatible storage, buy_guide), incorporates decision_hint into recommendations, and requires affiliate_url presentation. However, it doesn't mention error handling, rate limits, authentication needs, or what happens when products can't be compared.

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 appropriately sized and front-loaded, starting with the primary use case and core functionality. All sentences contribute value, though the final sentence about affiliate_urls could be integrated more smoothly. There's no redundant information or unnecessary elaboration.

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?

For a comparison tool with 3 parameters and no output schema, the description adequately covers the core functionality but lacks details about the comparison table structure, error cases, or how catalog matching works. With no annotations and no output schema, the description should ideally provide more behavioral context about what the tool returns and its limitations.

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 three parameters. The description doesn't add significant semantic information beyond what's in the schema descriptions, though it implies the keywords parameter should contain product names or identifiers rather than generic search terms. The baseline 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: compare 2-5 products across price, size, reviews, and load capacity, returning a parallel comparison table. It specifies the exact resources (products) and verb (compare), distinguishing it from sibling tools like get_product_detail or search_products by focusing on multi-product comparison rather than single-product lookup or general 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 explicitly states when to use this tool: 'when comparing 2-5 products' and provides a concrete example ('NクリックとKALLAXどっちがいい？'). It also implicitly distinguishes from alternatives by specifying the comparison table output format, unlike sibling tools that return single products or search results.

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