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knowledge-base

by com.tunnelpowered

ask_business_freeform

Same answers as ask_business, but you send the person's own words instead of choosing an intent, and the reply comes back in the language they used. Supported languages: en, ro, ru, de; anything else is answered in English. Prefer ask_business when you already know which of the three questions you are asking — it is instant and costs nothing, whereas this one runs a model to read the question and is rate-limited accordingly. A model is used ONLY to decide which question was asked and in which language. It never sees the business's stored data and never writes the answer. Returns an outcome and a reply in the asker's language. Branch on outcome, not on the prose: "answered" carries reply and a structured answer; "needs_detail" means we need one more thing from the asker and reply requests it; "not_understood" means it was not one of our three questions, with supported listing them; "escalated" means a real question we do not hold the fact for — we forward that one to the business ourselves, and escalation carries the ref that reads their answer later with check_escalation. handoff still holds what was gathered, for contact_business. An escalation is never a negative answer. 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.
questionYesWhat the person actually asked, in their own words and their own language. Do not translate or rephrase it — the language of this text decides the language of the reply.
idempotency_keyNoOptional, and only matters when a question reaches a person. The same question about the same business within 24 hours attaches to the open one and does not notify them twice, which is right when you are RETRYING a failed call and wrong when it is a genuinely new problem worded the same way. Send the same key when retrying, a fresh one when it is a new ask. Omit it and the retry behaviour applies, which is the safe default for the business.

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 carries full disclosure burden. It reveals the model usage scope (only to decide question and language), privacy guarantees (never sees stored data, never writes answer), rate limiting, language support with English fallback, and detailed outcome behaviors including escalation semantics. This is far beyond typical descriptions and fully 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?

The description is a compact but information-dense paragraph, organized logically: comparison to sibling, language/rate-limit notes, privacy/model usage, outcome enumeration, and auth. Every sentence carries substantive guidance and no filler. Despite its length, it earns its place given the tool's complexity.

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?

There is no output schema, so the description must explain return values, and it does so comprehensively: `outcome` variants (`answered`, `needs_detail`, `not_understood`, `escalated`) with their respective payloads and how to branch. It also covers `handoff` for contact_business and references check_escalation. Combined with language, auth, and rate-limit context, this is fully complete for safe 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 description coverage is 100%, and the schema itself already explains each parameter thoroughly (including the nuanced idempotency_key retry behavior and the language-deciding role of `question`). The tool description mostly restates or summarizes these, adding little new parameter-specific meaning beyond what's in the schema. Baseline 3 is appropriate.

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 identifies this tool as a freeform variant of ask_business, explicitly contrasting it with the intent-based sibling. It specifies the verb (ask), the resource (business freeform query), and the key difference: sending the person's own words versus choosing an intent. This distinguishes it effectively from its primary sibling.

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?

The description gives explicit guidance: 'Prefer ask_business when you already know which of the three questions you are asking — it is instant and costs nothing, whereas this one runs a model to read the question and is rate-limited accordingly.' It also explains when to branch on specific `outcome` values and how to handle retries with `idempotency_key`. This is exemplary usage guidance.

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.

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