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knowledge-base

by com.tunnelpowered

ask_business

Ask one specific question about a listing and get an answer from the registry, with no human involved. Try this before contact_business: it is instant, free, and does not put a message in someone's inbox. Returns either an answer or an escalation. When resolved is true, answer holds it and basis names the fields it was read from. When escalate is true we do not hold the fact — this is NOT a negative answer, and in particular an unlisted place is "we do not know", never "they do not deliver there". Only the business can declare its own list complete. Unsupported questions come back with refused true and a supported list rather than a guess: nothing here is ever inferred, approximated or improvised. Authentication: none. This tool works with no credentials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesThe `kind` field from the same search result.
slugYesThe `slug` field from a search_businesses result.
intentYesWhich question to ask. "is_open_now" needs nothing else; "delivers_to" needs a `params` place; "lead_time" asks the shortest notice they accept an order on.
paramsNoArguments for the question. For "delivers_to": { "place": "Botanica" }. Ignored by the others.

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries full behavioral burden and does so excellently. It explains return states (`resolved`, `escalate`, `refused`), clarifies that escalation is not a negative answer, notes that unlisted means unknown, and states that nothing is inferred or approximated. Authentication is also explicitly disclosed.

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

Conciseness4/5

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

The description is well-structured with the core purpose first, then usage guidance, then semantic details. It is longer than typical due to important caveats, but every sentence adds value. Minor redundancy exists: 'Authentication: none' and 'This tool works with no credentials' say the same thing.

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 tool's complexity (4 params, nested object, no output schema), the description covers all essential aspects: what it does, return semantics, error handling via `refused`, and authentication. It also provides enough context to choose between this and contact_business. The absence of an output schema is compensated by detailed textual descriptions of response states.

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 value by explaining the intent options and the role of `params` for `delivers_to`, and by noting that `params` is ignored by other intents. It also clarifies the `supported` list for unsupported questions, going beyond the schema.

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 uses a specific verb ('Ask') and resource ('listing') and clearly distinguishes the tool from contact_business by noting it is instant, free, and does not send an inbox message. It also states it handles 'one specific question,' contrasting with the freeform sibling.

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?

Explicitly tells when to use this tool before contact_business and describes advantages. However, it does not directly contrast with ask_business_freeform, though 'one specific question' implies a structured-question use case. The guidance for when to use vs. alternatives is strong but not fully exhaustive.

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