cintra-quote

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

No annotations are provided, so the description carries full burden. It lists the types of information (categories, quotes, payments, delivery, reorder mechanics) but does not disclose whether the operation is read-only, requires authentication, or has any side effects or rate limits.

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, no wasted words. The first sentence lists the information categories; the second gives a practical use case. Front-loaded and efficient.

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 no parameters and no output schema. The description implies the output structure by listing fields but does not explicitly state the return format (e.g., JSON). Could mention error handling or default values, but for a simple tool it is adequate.

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?

There are no parameters; schema coverage is 100% by default. The description does not add parameter information, but none is needed. Baseline 3 is appropriate.

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 information on categories, quote turnaround, payment terms, delivery, and reorder mechanics. It also gives a use case: checking scope before submitting a parts list. However, it lacks a strong imperative verb like 'retrieve' or 'list', relying on the title and name.

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 includes one usage guideline: 'Use to check whether a parts list is in scope before submitting.' It does not specify when not to use the tool or mention alternatives like get_vendor_info or submit_bom_quote.

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?

No annotations are provided, so the description carries the full burden. It does not disclose any behavioral traits such as read-only nature, safety, authentication requirements, or side effects. As a data retrieval tool, it likely has no destructive side effects, but this is not stated.

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 efficiently lists the data fields, the second gives the usage context. No superfluous words; 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?

Given the simplicity of the tool (zero parameters, no output schema), the description provides sufficient information about what is returned and when to use it. The mention of 'documents available for procurement systems' is slightly vague, but overall adequate.

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 100% schema description coverage. The description does not need to add parameter information. Baseline score 4 is appropriate for a parameterless tool.

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 what data the tool returns: legal entity, ownership/diversity status, NAICS codes, payment terms, and documents. It also specifies the exact use case: registering Cintra Supply as a vendor. This distinguishes it from sibling tools like get_capabilities and submit_bom_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 provides explicit context for when to use the tool ('when a buyer needs to register Cintra Supply as a vendor'), but does not mention scenarios where it should not be used or suggest 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 provided, the description carries the full burden and discloses key behaviors: the quote is human-reviewed, emailed within 15 minutes during US business hours, and requires email confirmation. This goes beyond a basic mutation description.

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: first explains the core action, second lists applicable categories, third provides a critical usage reminder. No redundant information, and key details are 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?

Given the tool has 7 parameters, no output schema, and no annotations, the description adequately covers the process (human review, turnaround time), target items, and a required precaution. It lacks error handling or response details but is sufficient for a submission tool.

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 schema already documents parameters. The description adds minor value by emphasizing email confirmation and listing use categories, but does not significantly enhance parameter meaning beyond the schema.

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 submits a bill of materials for a human-reviewed, line-by-line priced quote, which is distinct from sibling tools get_capabilities and get_vendor_info that retrieve information.

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 lists specific product categories for use and instructs to always confirm the contact email before submitting, providing clear when-to-use guidance. It does not explicitly state when not to use, but the context is sufficient.

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