knowledge-base

get_business

Read the full profile of one business. Returns identity, contact details, address, social profiles, offerings, FAQ, verification and any machine-readable endpoints we publish for it. Absent information is named in missing rather than dropped silently, so an empty field means "we do not hold this", not "they do not have one". An unknown slug returns candidate slugs instead of a bare failure. Authentication: none. This tool works with no credentials.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`kind`	No	Optional. The `kind` field from the same search result. If omitted, "entity" is tried first, then "website".
`slug`	Yes	The `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 provided, the description fully accounts for behavioral transparency. It discloses that absent information is named in a 'missing' field (not dropped silently), unknown slugs return candidate slugs, and no authentication is needed. This covers important edge cases and safety considerations.

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 concise and well-structured, front-loading the core purpose and then adding relevant details about missing fields, error handling, and authentication. Every sentence serves a purpose without 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 no output schema, the description is highly complete: it lists the categories of returned data, explains the 'missing' field convention, describes behavior for invalid slugs, and confirms no credentials are needed. This enables an agent to confidently invoke the tool.

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%, but the description adds value beyond the schema by explaining the default fallback logic for the 'kind' parameter (entity then website) and specifying that 'slug' comes from a search_businesses result. This provides essential context beyond parameter names and enum values.

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 the full business profile, listing specific fields like identity, contact, address, social profiles, offerings, FAQ, and verification. It distinguishes from siblings like search_businesses (searching) and contact_business (contacting) by focusing on reading a complete record.

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

Usage Guidelines4/5

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

The description notes the tool requires no credentials and explains behavior for unknown slugs, but does not explicitly state when to use this tool over alternatives like search_businesses or contact_business. However, the context is clear enough for an agent to infer appropriate use.

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

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