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

Without output schema, the description carries the burden and does so well: it specifies the exact price semantics (9% GST + Singapore delivery included), the confidence tiers (exact/spec/similar, with differences listed for similar), the no-match behavior ('needs_detail' plus what to ask), and the hard rule to never invent a price. The annotations (readOnlyHint, openWorldHint=false) already establish safety and closed-world scope; the description adds the pricing and matching behavior on top. It doesn't cover rate limits or latency, but that's minor for a read-only quote tool.

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?

It is long and dense, but the upfront sentence delivers the core value first (all-in price + ready-by date + scope) before the enumeration and per-category spec list. The spec guidance is genuinely useful and not padded, though the length is at the upper end for a tool description. It earns most of its 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 7-param, no-output-schema read-only quoting tool, the description is complete: it defines what the tool returns, the input it expects, the confidence model for results, the vague-input handling path, and the fallback to request_quote when nothing matches. An agent has everything needed to call it, interpret the result, and act on 'needs_detail'. Nothing essential 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%, so the schema already documents each parameter. The description adds value beyond that by prescribing per-category key specs (cables: connector at each end + length in metres; adapters: from + to; memory cards: card type + capacity; flash drives: capacity + connector; SSD/HDD: capacity + internal/external; UPS: VA rating or model; ink/toner: printer brand + cartridge code + colour; mice/keyboards: model or wired/wireless; monitors: size in inches; switches: port count). This is actionable guidance that improves match quality, exceeding the baseline 3 despite full 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 opens with a precise statement of what the tool returns: a current all-in SGD price (including 9% GST and Singapore delivery) and a ready-by date for office/IT/electronics supplies. It enumerates the supported categories and scopes the result to Singapore, distinguishing it clearly from the other quote_* siblings (quote_event_print, quote_list, request_quote).

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?

It explicitly tells the agent to 'Pass category, brand, model, specs, quantity and needed_by whenever you know them, plus the buyer's own words in item.' It also handles the vague-request case: if the result has match 'needs_detail', ask the buyer and call again. And it routes to the alternative sibling: 'if nothing matches, call request_quote with category office-it-supplies.' Nothing is left to inference.

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