ai-furniture-hub

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

With no annotations provided, the description carries full burden. It discloses key behaviors: calculates box quantities and total costs, provides coordination tips based on location, includes persona-based advice with budget/brand recommendations, and requires affiliate URL presentation. However, it doesn't mention rate limits, error handling, or data sources.

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 with the primary use case. Every sentence adds value: first establishes when to use, second explains core calculations, third adds coordination advice, fourth details persona hints, fifth specifies affiliate requirement. Minor redundancy exists in mentioning persona_hints twice.

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 complex tool with 6 parameters, no annotations, and no output schema, the description provides good coverage of what the tool does, when to use it, and key behavioral aspects. It explains the calculation logic, recommendation approach, and output requirements (affiliate URLs). The main gap is lack of information about return 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 baseline is 3. The description adds meaningful context beyond the schema by explaining how parameters relate to the tool's functionality: '設置場所(押入れ/洗面所/キッチン等)に応じた' clarifies the 'scene' parameter's purpose, and 'persona_hints' connects to the broader recommendation system. However, it doesn't provide additional syntax or format details for individual parameters.

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 with specific verbs ('計算し' for calculation, '算出' for computation, '提供' for provision) and resources (shelves, storage boxes). It distinguishes from siblings by focusing on coordination advice with quantity calculations, unlike general search or comparison tools in the sibling list.

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 with example user queries ('「この棚に合うボックスは？」「カラーボックスの整理方法」のときに呼ぶ'). It also distinguishes usage context by mentioning specific scenarios like storage locations (押入れ/洗面所/キッチン) and persona-based recommendations.

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