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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds value beyond that: it discloses the shape of the answer (exact products with title, vendor, finish, size, list price, URL), the one-question-per-call constraint, and the 600-character input cap. It does not describe failure modes or latency, but that is minor given the annotation coverage.

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 purpose is front-loaded in the first sentence, followed by a compact best-for list and a single actionable instruction about what context to include. Every sentence carries information; the enumeration is dense but scannable rather than redundant.

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?

There is no output schema, and the description compensates by specifying the fields returned in the answer and the input constraints (one question, 600 characters). Combined with the annotations, an agent has enough to invoke it correctly; only explicit sibling routing is missing.

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 coverage is 100% and there is a single required string, so the baseline is 3. The description goes further by telling the caller what content to pack into that string: room, drawer widths, existing hole spacing, finish, style, budget per piece, brand likes or dislikes, plus the 600-character limit, which meaningfully improves answer quality beyond the schema's terse 'question, with what is known'.

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 and resource: ask the automated cabinet-hardware advisor one plain-language question and receive one answer with named products (title, vendor, finish, size, list price, URL). It is clearly distinct from siblings like search_catalog, get_product, and sizing_guide because it produces a curated advisory answer rather than records or raw data.

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 'Best for' list gives concrete question categories (pull length for drawer width, hole center-to-center fit, knobs vs pulls, finish pairing, samples, returns, trade program), which is strong when-to-use guidance. It does not explicitly say when not to use it or route to a specific sibling alternative (e.g., sizing_guide or search_catalog), so it stops short of a 5.

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