ai-furniture-hub

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

With no annotations, the description carries full burden and provides good behavioral context: it separates required vs. recommended items, includes Rakuten search results for immediate proposals, expands to depth=2 for 'related of related', and mandates that required items must be communicated to the user. However, it doesn't mention rate limits, error handling, or authentication needs.

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?

Front-loaded with purpose, followed by key behavioral details in a single, dense sentence. Every clause adds value: separation of item types, Rakuten integration, depth expansion, and user communication requirement. 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?

For a tool with 5 parameters, 100% schema coverage, no annotations, and no output schema, the description provides strong context on behavior and usage. It covers the tool's role in workflow, output structure (separated items with search results), and expansion logic. Minor gap: no mention of output format or error cases.

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 well. The description adds minimal value beyond schema: it mentions depth=2 behavior but doesn't explain other parameters like intent or include_rakuten beyond what's in schema descriptions. Baseline 3 is appropriate when schema does 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: to propose 'what else is needed' after finding a product via search_products, returning required and recommended accessories/parts with Rakuten search results. It distinguishes from siblings like search_products (which finds products) and get_product_detail (which provides details).

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 states when to use: 'after search_productsで商品を見つけた後' (after finding a product with search_products) and for the purpose of '他に何が必要？を提案する' (proposing what else is needed). It distinguishes from alternatives by specifying its unique role in the workflow.

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