Ask ArchiGPT (architecture & design expert)

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

Annotations declare readOnlyHint=false and destructiveHint=false, and the description corroborates this by disclosing a real cost ('Costs 1 credit per ~3000 words'), which is valuable behavioral context not present in the annotations. It does not describe failure modes or response format, but the pricing disclosure is a meaningful addition beyond structured fields.

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 the core purpose, followed by usage hints and a cost note; three compact sentences with little waste. The capability enumeration is slightly long but each item adds real scope, so the size is justified.

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?

With no output schema, the description should carry the return-value burden, but for a conversational assistant the text reply is implied. It covers purpose, image/history usage, and cost; only the response shape and language/persona behavior are left implicit. Annotations cover the safety profile, so this is close to 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?

Schema description coverage is 100%, so the schema already documents all five parameters, making 3 the baseline. The description lightly reinforces the image and history params ('Attach an image to discuss it', 'Pass earlier turns in history') but adds no format, syntax, or constraint detail beyond what the schema provides.

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?

States a specific verb ('Ask') and resource (ArchiGPT, an AI architect) and enumerates concrete capabilities: design advice, feng shui, space planning, materials/colors, technical questions, and square-meter estimation from a photo or plan. The purpose is unmistakable, though it never names or contrasts itself against the sibling design tools (luw_interior_design, luw_exterior_design, etc.), so differentiation is left to inference.

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?

Gives clear operational context: 'Attach an image to discuss it' and 'Pass earlier turns in history to continue a conversation.' These tell the agent how to drive the tool across turns. However, there is no guidance on when to prefer ArchiGPT over the image-generation siblings or when not to use it, so routing remains implied.

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