Cintra Supply Quote Desk

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

Annotations already declare this is not read-only, is idempotent, and non-destructive. The description adds valuable context about the outcome: returns an order_id and conditionally a payment link, and describes the email invoice fallback. This goes beyond annotations by explaining what happens after acceptance.

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 with no waste, front-loaded with the core action and result, then conditional behavior. Efficient and clear.

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 annotations and full schema coverage, the description is nearly complete: it covers outcomes and conditional flows. However, it doesn't mention any permissions or error handling, though these may be inferred. For a mutation tool, this is strong but not exhaustive.

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 both parameters thoroughly. The description doesn't add parameter-specific details beyond implying 'ready' status for rfq_id, which the schema also states. 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 states a specific verb ('Accepts') and resource ('quote') and clearly distinguishes this from sibling read tools like get_quote and get_order by noting it returns an order_id. It also specifies the precondition ('ready' 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 implies usage when a quote is 'ready', but doesn't explicitly state when to use this tool versus alternatives or exclusions. The schema parameter 'confirm' provides some usage context, but the description itself lacks explicit 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?

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: the record is mutable in that fulfillment updates accrue over time, meaning repeated calls can return richer data. It does not cover error behavior for invalid or non-accepted order_ids.

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 tightly written sentences with no filler, and the return content (status values, amount, payment link) is front-loaded before the secondary note about fulfillment updates.

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?

With no output schema, the description carries the burden of describing returns and does so well by listing statuses, amount, and payment link. It stops short of describing failure modes for unknown or unaccepted order_ids, which is the main remaining gap for a lookup 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 description coverage is 100% and the single parameter already documents that the order_id comes from accept_quote. The description's reference to an 'accepted order' is consistent with the schema but adds no format or validation detail beyond it, so baseline 3 applies.

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 names a specific verb (Returns) and resource (an accepted order's status) and enumerates the exact status values an agent can expect. The phrase 'accepted order' implicitly separates it from get_quote, which deals with pre-acceptance quotes.

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?

Usage is implied rather than stated: the schema ties order_id to accept_quote, so the agent can infer this is the post-acceptance lookup. There is no explicit statement of when to prefer this over get_quote or what to do if the order_id is not an accepted 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?

The description goes beyond the readOnlyHint annotation by detailing the possible statuses and their meanings, including that 'ready' includes total and line pricing. This gives the agent a clear model of what the tool will return and how state evolves, though it does not cover error or not-found behavior.

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?

One focused sentence front-loads the core behavior and then efficiently enumerates all status values with their conditions. No filler or redundant repetition of the title or schema.

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 simple read-only tool with one parameter and no output schema, the description covers the essential return semantics and status values. It could be slightly more complete by noting what happens when the rfq_id is not found, but this is a minor gap.

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% and the rfq_id parameter is well-documented in the schema as coming from submit_rfq. The main description adds no further parameter detail, so the baseline of 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 states a specific verb ('Returns') and resource ('current state of a quote') and identifies the lookup key by rfq_id. This clearly distinguishes it from siblings that accept quotes, create RFQs, or fetch orders.

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?

Usage is implied through the status lifecycle: an agent can infer this tool is for checking quote status after submit_rfq and before accept_quote. However, there is no explicit guidance about when to use it versus alternatives, and no alternative tool is named.

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=true and openWorldHint=false, so safety and scope are covered. The description usefully enumerates what comes back (categories, accepted inputs, quote-to-order flow), but says nothing about format, size, or freshness of the capability data.

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?

A single front-loaded sentence with no filler; it names the returned content up front and stops. Every clause earns its place.

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?

With no output schema, the description must signal what is returned, and it does list three return components. Given a zero-param read-only tool with annotations covering safety, the only minor gap is the absence of any hint about calling it before the quote flow or its relationship to the sibling tools.

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 takes zero parameters, so the baseline is 4. There is nothing to document, and the description correctly introduces no parameter concepts that would need aligning with the empty 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?

States a specific verb ('Returns') and a concrete resource ('Cintra Supply's supported categories, accepted inputs, and the quote-to-order flow'). This clearly marks it as the informational/discovery tool among the transactional siblings (submit_rfq, accept_quote, get_quote, get_order), though it never names them for contrast.

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?

Usage is only implied: an agent can infer this is the call to make before entering the quote flow, especially with transactional siblings present. There is no explicit when-to-use statement, no prerequisites, and no guidance on whether to call it before submit_rfq.

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 readOnly=false, destructive=false, openWorld=true, idempotent=false, so the safety profile is partly covered. The description adds genuine value beyond them: it is non-binding, no charge occurs at this step, results arrive both via polling and by email. It does not discuss auth requirements, duplicate submissions, or error behavior.

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 action and return value, then the follow-up workflow and the safety caveat. No filler and nothing repeats the schema or title verbatim.

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 lifecycle (submit, poll, email), the returned rfq_id, and the non-binding/no-charge guarantee cover the highest-risk unknowns for a write-style call, and no output schema means explaining returns is unnecessary. However, for an 8-parameter tool with 38% schema coverage, the description leaves several inputs unexplained.

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 only 38% and the description adds essentially no parameter meaning: it mentions the parts list and buyer_email only incidentally and says nothing about company, needed_by, ship_to_zip, contact_name, or account_number. With a low-coverage schema, the description should have compensated here and does not.

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?

States a specific verb and resource ('Submits a parts list for a wholesale quote') plus the concrete artifact returned ('returns an rfq_id'). This clearly distinguishes it from the read-oriented siblings get_quote and get_order and the follow-on accept_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?

Routes the agent explicitly to the next step and sibling: 'Poll get_quote(rfq_id) until status is ready'. That is a strong when/what-next signal. It stops short of a stateable exclusion or an explicit condition for choosing this over any other entry point, so it is not a full 5.

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