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knowledge-base

by com.tunnelpowered

request_order_change

Raise anything else about an order that already exists: a change to what was ordered, a refund request, or a problem with what was delivered. This tool never settles anything, and that is deliberate. Changing an order re-prices it and a refund moves money tunnel does not hold, so both are decisions only the business makes. What this does is put the request in front of them with the whole order attached — reference, terms, lines, date and what has already happened to it — on the channel they actually read. Returns settled false always, the order as it stands, and an escalation whose ref you poll with check_escalation for the business's own answer in their words. For a refund it also returns refund: their published terms at this notice, if they have published any. Nothing has been paid, refunded or changed by this call. Authentication: bearer token required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refYesThe `ref` returned by commit_order.
noteYesWhat the buyer actually said, in their own words. This is the part the business needs, so send it verbatim. Carried unchanged and never interpreted.
changeYesWhat kind of request this is: "modify" to change what was ordered, "refund" to ask about money back, "other" for anything else including something being wrong.

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the burden. It discloses critical behavioral traits: returns settled=false always, attaches the full order, re-prices on changes, moves money on refunds, requires bearer token, and explicitly states that no money or changes are executed by this call. 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.

Conciseness4/5

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

The description is dense and front-loaded with purpose, then moves into behavior and return values. It is a single paragraph, but every sentence contributes valuable context. Some minor redundancy exists (e.g., "Nothing has been paid..." restates earlier points), preventing a 5.

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?

The tool has no output schema and rich behavioral implications. The description compensates by explaining exactly what is returned (settled, order, escalation, refund terms), how to follow up (check_escalation), authentication requirements, and side-effect guarantees. This is complete for an agent to invoke and interpret the result.

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?

Schema description coverage is 100%, so the baseline is 3. The description reinforces some parameter meanings (e.g., change types, note verbatim) but does not add substantial new semantic information beyond what the schema already provides. It adds context about the order attachment, but this is behavioral, not parameter-specific.

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's purpose with a specific verb and resource: "Raise anything else about an order that already exists." It enumerates distinct request types (change, refund, problem) and differentiates itself from siblings like commit_order and cancel_order by emphasizing it never settles anything.

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 provides explicit guidance on when to use this tool: for existing orders needing changes, refunds, or issue reports. It clearly states what the tool does not do (never settles, no payment/refund/change) and directs the agent to poll check_escalation for the business's answer, effectively naming the follow-up tool.

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