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request_quote

Price a specific set of line items against a business's rate card. Call get_rate_card first and name code values from it; we do the arithmetic. Returns quoted. When true you get total, lines showing what each one came to, and validUntil. A quote is a statement, NOT a hold — nothing is reserved and no price is locked. commit_order prices the same items again from the card at the moment it binds, so if the merchant changed a figure in between you are told rather than charged. When quoted is false, reason is "unknown-items" (not on their card), "quantity-out-of-range" (change the number and call again), "no-rate-card", "not-authorised" or "below-price-floor". All but the second put the question in front of a person and return an escalation whose ref you can poll with check_escalation. Authentication: none. This tool works with no credentials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoOptional. The `kind` field from the same search result. Defaults to "entity".
noteNoOptional. What the job is, in the buyer's own words. Never parsed and never changes the figure; it is what a human reads if the quote has to go to one.
slugYesThe `slug` field from a search_businesses result.
itemsYesThe lines to price. Each is an object with a `code` from get_rate_card and an optional quantity, which defaults to 1. Up to 100 lines.
languageNoOptional. The buyer's language, recorded with the request. Defaults to English.

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries the full transparency burden. It discloses that a quote is not a hold, nothing is reserved, no price is locked, and commit_order re-prices from the card, with the agent told if the merchant changed a figure. It details all return fields and the meaning of each failure reason, plus escalation refs and authentication state. This is exceptionally transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Although dense, every sentence earns its place. It starts with the core action, then prerequisites, return values, caveats, error handling, escalation path, and authentication. The structure is logical and front-loaded, with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters, no output schema, and no annotations, the description is remarkably complete. It covers how to invoke, what to expect, all failure modes with actionable outcomes, escalation polling, and security context. There are no significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaningful context beyond the schema: items must use codes from get_rate_card, up to 100 lines, note is never parsed and never changes the figure, and language is recorded. These extra notes enrich parameter understanding without repeating schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Price a specific set of line items against a business's rate card.' It clearly distinguishes the tool from siblings by naming get_rate_card as a prerequisite and commit_order as the later binding step, so the purpose is unambiguous and differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to call get_rate_card first and use its code values. Also clarifies when to use alternatives: commit_order re-prices at bind time, and escalations are polled with check_escalation. It even tells the agent to change quantity and call again for 'quantity-out-of-range'. This is thorough usage guidance with exclusions and alternatives.

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

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TDQS

A4.6/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but ask_business and ask_business_freeform both serve the core function of asking a question about a listing, which could cause misselection. The detailed descriptions mitigate the overlap, but the similar intent remains a minor ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (ask_, check_, contact_, get_, search_, send_), with only ask_business_freeform adding a modifier that still fits the convention. Naming is predictable and readable.

Tool Count5/5

Nine tools is well-scoped for a knowledge base server, covering discovery (search, get), questioning (ask), asynchronous communication (contact, followup, replies, escalation), and verification. Each tool earns its place without unnecessary bloat.

Completeness5/5

The tool set provides full coverage of the domain: finding businesses, reading profiles, asking structured and freeform questions, escalating unresolved queries, opening and continuing conversations, and checking verification. Poll-based tools handle dead ends explicitly, so there are no obvious gaps.

Resources