Reqo Supply Quote Desk

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

Annotations already signal mutation (readOnlyHint=false), idempotency, and non-destructiveness. The description adds meaningful context beyond those: the buyer must complete a payment link to place the order, and if payment is already settled, acceptance confirms the order. 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?

Two sentences with no filler. The core behavior is front-loaded, and the settled-payment nuance is a compact addendum. Every sentence 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?

For a simple two-parameter tool with annotations covering safety and idempotency, the description explains the key return values and the payment-flow behavior. It does not cover error handling for non-ready quotes, but that is a minor gap given the schema already constrains the input.

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 both rfq_id and confirm are already documented in the schema. The description reiterates the 'ready' status requirement but adds no new parameter-level meaning 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 opens with a specific verb and resource: 'Accepts a ‘ready’ quote.' It then states the outcome—returns an order_id and a secure payment link—and clarifies the settled-payment edge case. This clearly distinguishes it from sibling tools like get_quote or submit_rfq.

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 clear context: only quotes with status 'ready' should be accepted, and it explains the flow after acceptance. It does not explicitly name alternatives or state when not to use the tool, but the ready-status constraint is a practical usage rule.

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 safety profile is well covered. The description adds the contextual detail that fulfillment updates appear on the record over time, indicating the returned data is dynamic rather than a static snapshot. It does not discuss response format or error behavior, but these are less critical given the 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?

Two sentences with no redundancy: the first enumerates the key return values, and the second adds relevant behavioral context about dynamic fulfillment updates. The essential information is front-loaded, and 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?

The description covers the main return values and the dynamic nature of fulfillment updates, which is sufficient for a one-parameter read-only tool with no output schema. Minor omissions such as invoice link availability conditions or error handling are acceptable at this level of 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 description coverage is 100%, and the order_id description ('The order_id returned by accept_quote') already explains its provenance and meaning. The tool description adds no extra parameter semantics beyond what the schema provides. Baseline 3 is appropriate when the schema carries the full parameter explanation.

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 the exact data returned: payment status, amount, and invoice link. This cleanly distinguishes get_order from siblings like accept_quote or get_quote, whose names suggest quote submission and retrieval. No ambiguity remains about what resource and operation the tool targets.

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 alternative exclusions are provided. The schema's parameter description notes order_id comes from accept_quote, which implies usage after quote acceptance, but the tool description itself lacks that context. Usage is only inferred from the name 'get_order' and the return semantics, not stated as a clear guideline.

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, so the description correctly aligns by stating it 'returns' data. It adds value by specifying the exact content (categories, inputs, quote-to-order flow) and notes availability 'over this server,' giving context beyond the annotation. No contradiction.

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 zero filler. Every word earns its place, and the most important content (what is returned) appears immediately.

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 zero-parameter, read-only capability discovery tool with no output schema, the description adequately covers what the agent needs to know before calling it. It could optionally describe the return format, but that is not essential for invoking 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?

The tool has zero parameters and the schema coverage is trivially 100% (empty properties). There is nothing for the description to explain about parameters, so the baseline 4 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 states a specific verb ('returns') and a concrete resource ('Reqo's supported categories, accepted inputs, and the quote-to-order flow'). It clearly differentiates from sibling tools like get_quote or submit_rfq, which focus on individual quotes/orders rather than overall capabilities.

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 this is a discovery tool—useful for understanding what Reqo offers before engaging the quote flow—but it does not explicitly say 'use this before submitting an RFQ' or mention alternatives. Sibling names suggest the workflow, but the guidance is left to inference.

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?

Beyond the annotations, the description adds meaningful behavioral context: the operation is asynchronous (requires polling) and non-binding with no charge. It also states the specific completion signal ('ready'). No contradiction with annotations is present.

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 tight sentences carry all essential information: what the tool does, what it returns, how to follow up, and a key commercial caveat. There is no filler or redundant restatement of the title.

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 description covers the full request lifecycle: submit, obtain rfq_id, poll until ready, and no charge at this step. Since there is no output schema, the explicit return value is sufficient. It does not discuss error cases or parameter prerequisites, but the schema covers required fields, and the high-level flow is complete enough 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 only 38%, but the description does little to compensate. 'Parts list' loosely maps to the required 'lines' parameter, but there is no guidance on the other seven parameters, including required buyer_email and optional but meaningful fields like needed_by, ship_to_zip, and account_number.

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 and resource ('Submits a parts list for a wholesale quote') and states the concrete outcome ('returns an rfq_id'). It also distinguishes itself from sibling tools by positioning this as the initiating step, while get_quote is the follow-up and accept_quote is the later binding step.

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 explicit follow-up guidance: poll get_quote(rfq_id) until status is 'ready'. The phrase 'Non-binding; no charge occurs at this step' clarifies that this is not the acceptance step. It does not explicitly list when-not-to-use alternatives, but the intended workflow is clear.

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