Cintra Supply Quote Desk

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

Annotations cover the safety profile (readOnly=false, destructive=false, idempotent=true), so the description's job is to add side-effect context — and it does: it discloses that acceptance creates an order, may return a payment link the buyer must complete, or triggers an email invoice as the fallback. It omits the idempotency guarantee (re-accepting is safe), which would be valuable for a mutating tool, so it's not a 5.

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 the core action and result front-loaded and the payment contingencies following. No filler or restated boilerplate.

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 correctly carries the return-value burden, naming order_id and the conditional payment link, and it explains the offline email fallback. It would be complete at 5 if it also addressed whether calling again on an already-accepted quote is safe, given idempotentHint=true.

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% and both parameters are fully documented, including the 'ready' status requirement and the confirm authorization semantics. The description adds no syntax or format detail beyond the schema, which is the expected baseline for fully covered parameters.

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 ('Accepts a ready quote') plus the concrete outcome ('returns an order_id'), which cleanly separates it from the read-only siblings get_quote/get_order. An agent immediately knows this transitions a quote into an order.

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 embeds the applicability precondition ('a "ready" quote'), matching the schema's rfq_id constraint, so the agent knows when this tool applies. It does not name explicit exclusions or alternatives, but none of the siblings (get_order, get_quote, get_supplier_capabilities, submit_rfq) are substitutes for this action, so the gap is minor.

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 the agent knows this is a safe, closed-domain read. The description adds only content scope (categories, inputs, flow), not rate limits, caching, or freshness/snapshot behavior for what is effectively server metadata.

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 sentence, front-loaded with the verb and the three returned artifacts; nothing redundant or padded.

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 and no parameters, the description carries the burden of describing the return payload and does so at a coarse level (categories, accepted inputs, quote-to-order flow). It is adequate for an agent to decide to call it, though it does not indicate structure or granularity of the returned data.

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 of 4 applies. The description correctly implies a no-argument, whole-capability query rather than a filtered one.

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 set: supported categories, accepted inputs, and the quote-to-order flow. It is clearly distinguishable in kind from the transaction siblings (get_quote, submit_rfq, accept_quote, get_order), though it never names or contrasts them explicitly.

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?

No explicit when-to-use or when-not-to-use is given, and none of the four sibling tools are named as alternatives. Usage is only implied by the discovery-style purpose — an agent can infer 'call this first to learn what is supported,' but the description does not state that sequencing.

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-read-only, non-destructive, non-idempotent, open-world. The description adds genuinely useful behavior beyond that: the request is non-binding, no charge occurs, an rfq_id is returned, and the quote is emailed to buyer_email asynchronously. It omits the notable non-idempotent trait (resubmitting likely mints a new RFQ), which would be worth stating.

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 filler, and the most important fact (async polling via get_quote) is front-loaded right after the core action. Every clause carries 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 mutation tool with no output schema, the description conveys the async lifecycle, the return handle, and the safety profile (non-binding, no charge) — enough to call it correctly. The gap is the near-empty parameter explanation, which leaves the 38%-covered schema to stand alone.

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%, so the description must carry more weight, yet it explains no parameters except implying buyer_email receives the quote. It says nothing about the lines array shape, quantity/unit semantics, needed_by format, or why account_number matters for repeat-customer recognition.

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') and names its output artifact (rfq_id). It also explicitly routes to the sibling get_quote for the follow-up step, so an agent can distinguish it from accept_quote and the read tools without opening a schema.

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?

Gives clear usage context: this is the entry step, then 'Poll get_quote(rfq_id) until status is ready'. It names the alternative tool and the completion condition, though it never states when not to use this (e.g., when a quote already exists) or how it relates to accept_quote.

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