get_pricing_capabilitiesProducts, option keys/choice ids, valid quantities, and ordering facts for Tabzoola custom index tab dividers (paper and poly). Call this first to learn what quote_price accepts.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to repeat those. It adds useful output-content expectations but does not disclose behavioral quirks such as pagination, filtering, or exact response shape.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first lists the returned data categories as a tight noun phrase, and the second states the intended call order. There is no filler, and the actionable guidance is direct.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter discovery tool, the description covers both content and invocation timing well. It stops slightly short by leaving 'ordering facts' somewhat vague and not detailing the exact output representation, but overall it is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so the baseline is 4. The description correctly focuses on what the call returns rather than parameter semantics, which is appropriate for a parameterless capability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description names exact resource (Tabzoola custom index tab dividers) and states the information it exposes: products, option keys, choice ids, valid quantities, ordering facts. It also explicitly casts itself as the precursor to quote_price, separating it from the sibling pricing tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives a clear directive: 'Call this first to learn what quote_price accepts,' establishing appropriate ordering relative to quote_price. It does not, however, discuss when not to use it or compare it with draft_order.
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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Each tool covers a distinct stage of the workflow: get_pricing_capabilities provides configuration discovery, quote_price returns live pricing, and draft_order creates a pre-filled order with titles. While quote_price and draft_order both produce order URLs, their purposes are clearly separated by the descriptions.
All tool names follow a consistent verb_noun snake_case pattern: get_pricing_capabilities, quote_price, draft_order. The naming clearly mirrors the intended sequence and makes the tool roles predictable.
Three tools is well-scoped for a narrow pricing/draft-order domain. Each tool has a distinct and necessary function, and there is no bloat or redundancy.
The workflow is complete for the stated purpose: discover capabilities, quote a live price, then generate a ready-to-complete draft order. Since human checkout is explicitly out of scope, no additional order-management tools are needed.