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knowledge-base

by com.tunnelpowered

get_rate_card

Read the prices a business has authorised us to quote on their behalf. Returns published and, when true, a rateCard holding a currency, an optional minimum charge and items — each with a code, a label, a unit and an amount. Those code values are what request_quote and commit_order take: we price exactly what you name and never work out which line a description meant, because a near-miss there is a wrong price someone has to honour. published false comes with reason: "no-rate-card" means they have not written one, "not-authorised" means they have not allowed us to name prices at all. Neither means the work is unavailable — only that the figure has to come from a person, via ask_business_freeform or contact_business. 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".
slugYesThe `slug` field from a search_businesses result.

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description discloses key behaviors: it is a read operation, pricing is exact-match ('never work out which line a description meant'), the meaning of published/reason values, and that no authentication is needed. This fully informs the agent about side effects and data semantics.

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?

The description is well-structured and information-dense; every sentence adds value: purpose, return format, exact-match caveat, fallback tools, and authentication. No filler or redundancy.

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?

Given the simple 2-parameter schema and no output schema, the description fully covers return values, failure reasons, alternative tools, and authentication, making it complete for agent invocation.

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

Parameters3/5

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

The schema already documents both parameters at 100% coverage. The description mentions the returned codes are used by other tools but does not add new meaning to the slug or kind parameters beyond what the schema states, so the baseline 3 applies.

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 clearly states the tool reads authorised prices for a business, with a specific verb ('Read') and resource ('prices'). It also outlines the return structure and distinguishes itself from pricing/commit operations by noting the codes feed request_quote and commit_order.

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 provides fallback guidance: when published is false, use ask_business_freeform or contact_business. It also implies the primary use case of obtaining exact codes for quote/commit, thereby clarifying when to use this tool versus 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