pricing

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

With no annotations provided, the description carries the full burden of safety disclosure. It explicitly states 'Purchases nothing and reserves nothing,' clarifies that a human reviews and completes checkout, and mentions a free PDF proof before printing. This is strong behavioral transparency.

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 three sentences, front-loaded with the core purpose, followed by safety/flow clarifications, and ends with usage sequencing. No wasted words; each sentence contributes to understanding the tool's role and constraints.

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?

Given there is no output schema or annotations, the description is thorough: it explains what the tool does, what it returns (an orderUrl), what it does not do (purchase/reserve), and when to use it relative to get_pricing_capabilities. It provides sufficient context for the agent to select and invoke the tool 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%, with each parameter already described in the input schema. The description adds context about 'the buyer's actual tab titles' and 'exact price' but does not materially enhance parameter understanding 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 states a specific verb ('Compose') and resource ('a ready-to-complete draft order'), and details the outcome: an orderUrl that opens Tabzoola's designer with titles pre-filled at a live price. This distinguishes it from the sibling tools by emphasizing it is a draft, not a purchase or quote.

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 says 'Use after get_pricing_capabilities,' providing clear sequencing context. However, it does not explicitly mention when not to use it or how it differs from quote_price, so it falls short of a full 5 explicit alternatives.

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?

With no annotations, the description takes on the burden of explaining behavior. It clearly states that the tool returns reference data (products, option keys, quantities, ordering facts) and frames it as a read-only discovery step. It does not mention caching, errors, or data freshness, but the provided behavioral scope is adequate for a no-parameter lookup tool.

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 sentences: the first concisely lists the returned information categories, and the second gives a one-line usage instruction. There is no filler or redundant content.

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?

Given the tool's simple nature (no parameters, no output schema) and its sibling context, the description is complete. It states what data is returned, the product scope, and the proper calling order (before quote_price), leaving no critical gaps for an agent selecting or invoking 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?

The tool has zero parameters, and the schema is empty, so the description need not explain parameter meanings. The baseline of 4 for zero-parameter tools applies, and the description adds no unnecessary parameter detail.

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 specifies exactly what the tool provides: products, option keys/choice ids, valid quantities, and ordering facts for a particular product line (Tabzoola custom index tab dividers). It also explicitly differentiates from quote_price by positioning this as its prerequisite, making the tool's purpose clear and sibling-aware.

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 clear usage context with 'Call this first to learn what quote_price accepts,' indicating when to use the tool relative to quote_price. It does not, however, list when-not-to-use scenarios or mention the draft_order sibling, so it stops short of full exclusion guidance.

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?

With no annotations provided, the description carries the full burden. It discloses return contents (per-set, total USD, setup included, orderUrl) and notes it uses the same engine as the website's live pricing. The 'for a human to complete' phrase implies no order is placed, which is a behavioral trait. It doesn't mention side effects but the read-only nature is implied. No contradiction with annotations since none exist.

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 sentences, each serving a purpose. The first sentence efficiently summarizes the tool's output and behavior, the second adds a consistency note. No fluff or redundant 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?

There is no output schema, so the description must explain return values, and it does: per-set and total USD, setup included, and an orderUrl. It also adds context about the same engine as the website, which helps set expectations. Combined with the rich schema, the description is complete for this tool's complexity.

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 coverage is 100%, so the baseline is 3. The description does not add parameter-specific semantics beyond the schema; it only mentions the return value (setup included) which is not a parameter detail. The schema already thoroughly documents all parameters (product enum, min/max, options, colorChanges).

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 states the tool provides a live price for a custom tab-divider build, including per-set and total USD, setup cost, and an orderUrl. This specific verb+resource combination distinguishes it from sibling tools like draft_order (order creation) and get_pricing_capabilities (capability lookup).

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 implies usage: when a live price is needed before placing an order, use this tool. It doesn't explicitly name alternatives, but the phrase 'for a human to complete' indicates it is not for order submission, which differentiates from draft_order. No explicit exclusions are stated, but the context is clear.

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