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 effectively describes the tool's behavior: grid-based simulation, returns coordinates and rotation status, and explicitly states limitations (doesn't consider doors/circulation). However, it doesn't mention performance characteristics, error conditions, or what happens with impossible configurations.

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 perfectly concise with three sentences that each earn their place: first establishes use case with example, second explains inputs and simulation method, third provides crucial limitations. No wasted words, front-loaded with the primary purpose.

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 simulation tool with 7 parameters, no annotations, and no output schema, the description does well by explaining the simulation approach, inputs, outputs, and limitations. However, it could provide more detail about the output format and what constitutes success/failure in the simulation to be fully complete.

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?

With only 43% schema description coverage, the description adds significant value by explaining the core parameters: room dimensions in mm, furniture list with width/depth/count, and the simulation approach. While it doesn't detail all 7 parameters, it provides essential context about what the simulation does with these inputs, compensating well for the low schema coverage.

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: performing a grid-based simulation to check furniture placement feasibility in a room. It specifies the input (room dimensions and furniture list) and output (coordinates and rotation status), distinguishing it from siblings like search_products or get_product_detail which handle product information rather than spatial simulation.

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 ('家具の配置可否を確認するときに呼ぶ' - call when checking furniture placement feasibility) and provides important limitations: it doesn't consider doors or circulation paths, and should be treated as a rough guide. This gives clear context for when to use it versus more detailed alternatives.

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