pricing

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

Annotations already declare readOnly, idempotent, and non-destructive traits; the description adds significant behavioral context by explaining the returned orderUrl opens the designer pre-filled, creates no purchase or reservation, requires human checkout, and includes a free PDF proof. This goes well beyond the annotation hints and makes the tool's side-effect-free behavior concrete.

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?

The description is two dense, front-loaded sentientes. The first sentence captures the primary purpose and output; the second covers safety and usage constraints without wasted words. Every phrase contributes unique information.

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 tool with no output schema and nested parameters, the description covers the return value (orderUrl), the follow-up workflow (human review and checkout), and the critical non-purchase/non-reservation guarantee. Combined with the fully documented input schema and rich annotations, an agent has everything needed to invoke it correctly.

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?

Schema description coverage is 100%, so each parameter is already documented. The description adds some useful semantic flavor—confirming that titles are the buyer's actual tab titles and that the build is live-priced—but doesn't fundamentally change the meaning of any parameter. Baseline 3 is appropriate because the schema carries the documentation weight.

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?

The description uses a specific verb and object: 'Compose a ready-to-complete draft order' with the key outcome being an orderUrl that opens Tabzoola's designer. It clearly differentiates from siblings by emphasizing 'nothing purchased' and 'reserves nothing', making the draft-only purpose unmistakable.

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?

The description explicitly states 'Use after get_pricing_capabilities', giving clear sequencing guidance. It also communicates the appropriate context: when you want a human-reviewed draft with actual tab titles rather than a finalized purchase. It doesn't explicitly contrast with quote_price, but the draft-vs-purchase distinction is strongly implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds meaningful context beyond annotations by explaining the output includes an orderUrl and that setup cost is included, and that it mirrors the website's live pricing engine. No contradictions with annotations.

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, front-loaded with the core purpose, and every clause adds useful context. No filler or repetition of schema details.

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?

The description is reasonably complete for a read-only pricing tool: it names expected output fields and the configurator flow. It does not mention that options should be looked up via get_pricing_capabilities, though the schema already references that sibling, so an agent can discover it.

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?

Schema description coverage is 100%, so the schema already documents all five parameters. The description adds output-level context (per-set/total pricing, setup included) but does not explain parameter selection or dependencies beyond what the schema provides.

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?

The description clearly identifies the tool's purpose: quoting a live price for a custom tab-divider build, including per-set and total USD. It is distinct from sibling tools by function, but it does not explicitly name or contrast them, so it falls just short of full sibling differentiation.

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?

The description provides clear context for when to use the tool: for live custom-pricing quotes, with an orderUrl for human completion. It implies rather than explicitly states when not to use it or which sibling to choose instead, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.