Standard Titanium Quotations

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well-covered. The description adds the semantic detail of the two status states, but does not disclose additional behaviors like potential errors or network latency. Given the annotation coverage, the description is adequate but not rich.

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 a single, front-loaded sentence that conveys the exact purpose without any filler. Every word earns its place, achieving maximum conciseness.

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 tool is simple with one well-documented parameter and an output schema, so the description covers the essential behavior. It outlines the two states the status can be in, which is sufficient for an agent to call the tool correctly. It doesn't mention any polling strategy, but that's not required for a basic status check.

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 provides full documentation for the single parameter 'enquiryId', including its provenance from request_quote or request_titanium_quote. Since schema coverage is 100%, the description adds no additional parameter semantics, matching the baseline of 3.

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 states a clear verb ('check'), a specific resource ('quotation enquiry status'), and specifies the two possible outcomes ('waiting for human pricing' or 'quoted'). It clearly distinguishes from the sibling submission tools (request_quote, request_titanium_quote) which are about creating enquiries, not checking status.

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 the usage context by referring to 'a previously submitted quotation enquiry', which suggests it should be used after request_quote or request_titanium_quote. It does not explicitly contrast with alternatives, but since the only siblings are submission tools, an agent can infer this is the only status-checking option. A more explicit instruction to call this after submission would improve it, but the context is clear enough.

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?

The description adds important behavioral context beyond the annotations: 'This submits a real enquiry' signals that the tool has a real-world side effect, and the consent warning reinforces non-idempotency. Annotations already mark readOnlyHint as false and idempotentHint as false, so the description usefully supplements them rather than repeating them.

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 concise sentences: the first states the core purpose, the second adds a critical guardrail. There is no redundancy or filler, and the most actionable information is front-loaded.

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 five fully documented required parameters and an output schema, the description covers the essential non-obvious context: this is a real submission requiring user consent. It is complete enough for an agent to select and invokes 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%, so each parameter is already documented in the input schema. The description does not add parameter-level meaning beyond indicating that the enquiry contains customer details, which is sufficient given the schema's completeness.

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 states a specific verb and resource: 'Create a generic quotation enquiry for human pricing.' The term 'generic' differentiates it from the sibling request_titanium_quote, and the title pairs with the description to distinguish it from get_quote_status.

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 gives a clear usage condition: 'only call it after the user has agreed to submit their details.' It does not explicitly name alternatives or state when not to use the tool, but it provides enough context that an agent knows the intended trigger.

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 non-readOnly, non-idempotent, non-destructive, and openWorld. The description adds meaningful behavioral context beyond annotations: it is for human pricing (implying manual review and delay) and it must only be called after explicit customer agreement. These are additional behavioral traits that help an agent anticipate side effects and prerequisites. No contradiction 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?

The description is two sentences, with the core purpose front-loaded and the usage condition following succinctly. Every sentence adds value: the first establishes the tool's action, the second the critical precondition. No redundancy or filler, making it optimally concise for an agent to parse.

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 tool has 18 parameters and 7 required, but an output schema exists, so return values are documented elsewhere. The description covers the essential action ('submit enquiry for human pricing') and the critical precondition (customer agreement). It does not explicitly state that submission is a long-running process or how to track it, but 'human pricing' implies manual handling, and the output schema likely covers the response. Given complexity and existing schema, the description is sufficiently complete 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?

Schema description coverage is 100%, so the schema already documents all 18 parameters, including required ones. The description adds no parameter-specific meaning beyond what the schema provides. Per the rubric, a baseline of 3 is appropriate when the schema does the heavy lifting; the description's general context does not enhance parameter understanding.

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 ('Submit') and resource ('structured titanium material enquiry') and adds the purpose 'for human pricing'. This clearly distinguishes it from the generic sibling 'request_quote' and the status-checking 'get_quote_status'. The description is not a tautology and immediately conveys what the tool does.

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 gives an explicit precondition: 'Only call after the customer has reviewed the interpreted requirement and explicitly agreed to submit it.' This is a clear when-to-use directive. It does not explicitly mention alternatives (e.g., when to prefer request_quote), but the context of titanium and human pricing implies selection. The condition is sufficiently explicit to guide correct usage.

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