GF Agent Toll

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

With no annotations, the description must fully disclose behavioral traits. It only says 'Evaluate,' which suggests a read-only operation, but it never explicitly states whether it modifies state, requires authentication, or has side effects. It also omits any details about return values or error conditions. The disclosure is minimal and insufficient for a tool that likely governs payment safety.

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 sentence with no waste, which is efficient. However, it is too terse to convey essential information for a complex tool. While it is concise, the brevity undermines usefulness, making it 'under-specified' rather than 'appropriately sized.'

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 13 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain the return format, the criteria for the evaluation, the interaction between limits, or the significance of the required price_usdc. An agent cannot correctly invoke this tool without guessing at parameter meanings and expected behavior.

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 0%, so the description must compensate. It names the limit categories (per-call, daily, monthly, approval) which map to four parameters, but the tool has 13 parameters, including price_usdc, provider_id, and allowed lists. The description adds some meaning for limit-related fields but ignores the rest, leaving many parameters entirely unexplained.

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 the tool evaluates per-call, daily, monthly, and approval limits before payment, which gives a clear enough action and resource (budget limits). However, it does not specify what 'evaluate' entails—whether it returns a boolean, a report, or performs a calculation—nor does it differentiate from sibling tools like gf.quote or gf.payment_status. It is more specific than a tautology but lacks precision.

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 phrase 'before signing payment' provides context on when to use it, implying it should be invoked prior to payment approval. Yet there is no mention of alternatives or conditions when this tool should not be used, despite many related siblings such as gf.quote or gf.execute. The guidance is implicit and incomplete.

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 are absent, so the description carries the full burden of behavioral disclosure. 'Describe' weakly implies a read-only operation, but the description does not state the output form, data source, freshness, or any side effects. The agent is left to infer the safety and behavior profile.

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 one short, front-loaded sentence with a clear list of topics. It is concise, but it sacrifices details that would improve clarity around status semantics.

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 annotations, the tool name says 'status' but the description says 'Describe', creating ambiguity about what a call returns. The topic list is too thin for an agent to know whether this tool returns current state, a static explanation, or a structured report.

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 zero parameters, so there is nothing for the description to explain about inputs. The baseline of 4 applies because no parameter documentation is needed.

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 scope: spend controls, reputation, and marketplace economics. It uses 'Describe' as a concrete action, so an agent can infer this is an informational/reporting tool. It does not differentiate from sibling status tools like universal_status or payment_status, so it stops short of a 5.

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 guidance is given about when to use this tool versus alternatives. With many related siblings such as universal_status, payment_status, settlement_status, and provider_health, the agent receives no selection context.

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, the description carries full behavioral burden and does add important context: native paid services return x402 challenges and caller funds are never spent automatically. It does not disclose side effects, authorization requirements, idempotency behavior, or how capability selection works, leaving meaningful gaps.

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 no filler. The primary purpose is front-loaded in the first sentence, and the second sentence delivers a critical safety behavior, making it easy to scan and act on.

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 13 undocumented optional parameters, no output schema, and no annotations, this short description is not complete enough to guide correct invocation. It communicates high-level routing and a key safety property but omits parameter semantics, return behavior, and error or consent flows.

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 0% across 13 parameters, and the description adds essentially no parameter-level meaning. It never clarifies goal, task, intent, arguments, budget fields, paymentSignature, or mandate_id, so an agent has no textual help for populating the large optional parameter surface.

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 action ('Route an intent') and a distinct resource area ('best verified capability'), which clarifies the tool's job. It is distinguishable from siblings like search_capabilities and list_services, though 'best verified capability' remains somewhat vague.

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 intended use is implied: use this tool when an intent needs to be routed to a capability. However, the description gives no explicit when-not-to-use guidance and does not reference alternatives such as search_capabilities or quote, so an agent must infer the correct selection context.

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 must carry the full burden of behavioral disclosure. It only mentions free and preliminary, but doesn't explain side effects, authentication requirements, data handling, or limitations. For a tool that likely computes an estimate, non-mutating behavior is implied but 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 only two sentences and contains redundancy: 'Price: free' repeats the word 'free' from the first sentence. The essential information is not front-loaded or organized effectively, and the structure is overly terse.

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 8 parameters, no output schema, and no annotations, the description is grossly inadequate. It fails to explain required inputs, expected output, or any operational context, leaving an agent without sufficient information to invoke 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 0%, so the description must compensate for the 8 parameters, but it mentions none of them. It doesn't even hint that 'landed_cost' and 'expected_sale_price' are required, providing no semantic value 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 provides a profit and margin estimate for GCC products, and identifies it as free and preliminary. The resource and outcome are clear, but it doesn't differentiate from sibling tools like gf.gcc_opportunity_score or gf.gcc_product_decision, so it falls short of a perfect score.

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?

There is no guidance on when to use this tool versus the 17 sibling tools, nor any mention of scenarios or exclusions. The description states only what it does and its price, leaving the agent to infer usage context.

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, the description carries the full behavioral burden, but it only discloses the price and payment method (12.00 USDC via x402). It fails to state that payment is required before the plan is produced, whether the tool performs a purchase/authorization, how payment status is returned, or any side effects. This is inadequate for what appears to be a paid commercial operation.

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 short and front-loads the product range and price, but it is sparse to the point of being a snippet. There is no waste, yet the brevity is not 'appropriate' because it omits essential purpose and behavior details.

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 paid tool with no output schema and no annotations, the description is far from complete. It does not explain the payment flow, return value, required working capital semantics, or how this pack relates to the merchant GCC tool family. A model selecting this tool would not know what it will receive after paying.

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 0%, so the description must explain the parameters; it doesn't. It only references the product count range and gives no meaning for working_capital, referralCode, paymentSignature, or any nested product fields such as product_value, shipping, or duty_rate_pct.

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 calls it a 'Merchant portfolio plan for 3-25 products' and states a price, but it uses no verb and never says what invoking the tool does. It is more of a product listing snippet than a tool contract, and it does not differentiate from siblings like gf.free_profit_check or gf.gcc_portfolio_rank.

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?

There is no explicit when-to-use guidance and no mention of alternatives. The only implied context is the 3-25 product range, which hints at eligibility but does not tell the agent when to choose this over a free sibling or a quote tool.

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 behavioral burden. It does disclose the cost (0.75 USDC) and payment mechanism (x402), which is useful context. However, it does not state whether the call is read-only, what side effects occur, whether paymentSignature is required, or what the response contains.

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 compact and front-loaded, with the core concept first and the pricing detail in a separate sentence. It contains no filler words, though it could be more informative without becoming verbose.

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 13-parameter paid tool with no annotations and no output schema, the description omits parameter guidance, return value expectations, and usage context. It is enough to hint at what the tool returns, but not enough for an agent to confidently decide to call it or prepare a correct request.

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 0% for 13 parameters, and the description does not explain any of them beyond the general phrase 'unit economics, ROI.' Required fields like landed_cost and expected_sale_price are not semantically expanded, and no units, percentage conventions, or input relationships are provided. This is insufficient for an agent to correctly populate the many optional 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?

The description identifies the subject (GCC opportunity score) and hints at the inputs (unit economics, ROI), but it lacks a verb such as 'calculates' or 'returns' and does not differentiate this tool from siblings like gf.gcc_product_decision or gf.gcc_merchant_pack. It is a partial purpose statement rather than a clearly defined operation.

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?

There is no guidance on when to use this tool versus alternatives. Sibling tools such as gf.free_profit_check and gf.gcc_product_decision exist, but the description provides no selection criteria, prerequisites, or exclusions. The pricing line is payment context, not usage 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?

The 'Price: 5.00 USDC via x402' statement is a useful behavioral disclosure not available from annotations. However, with no annotations, the description still omits whether this is read-only, how payment is captured, what happens on payment failure, or whether any side effects occur.

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 short sentences with no filler. The ranking purpose is front-loaded and the price/payment method is stated compactly. 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?

Given the complexity of a 15-field product array, payment parameters, no output schema, and no annotations, this description is too thin. It lacks output format, field-level guidance, payment flow details, and any decision criteria for when the paid ranking is appropriate.

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 0%, and the description does not explain the products array, referralCode, or paymentSignature beyond implying 'product scenarios.' Required fields like product_value and expected_sale_price are self-explanatory, but the many optional economics fields and payment parameters remain unexplained.

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?

Description clearly states a specific verb and resource: 'Rank 2-12 product scenarios by economics and risk.' The 2-12 range differentiates it from single-product siblings like gf.gcc_product_decision and gf.gcc_opportunity_score, making the tool's purpose immediately identifiable.

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 guidance is provided on when to use this tool versus the many commerce-related siblings. It does not mention alternatives such as gf.free_profit_check or gf.gcc_product_decision, nor any conditions like portfolio-level analysis or paid multi-scenario ranking.

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, the description carries the full burden of behavioral disclosure. It does state a price and payment mechanism ('2.50 USDC via x402'), which is a useful operational trait, but it says nothing about side effects, authorization requirements, data mutation, failure modes, or what the returned decision looks like. The 'Premium end-to-end' phrasing is vague and does not disclose concrete 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?

At 18 words, the description is short and the price/payment detail is front-loaded in the second sentence. However, 'Premium end-to-end' is marketing fluff that adds little technical value. Given the tool's complexity, the brevity is not backed by substance; it is concise but not effectively structured for decision-making.

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?

This is a complex 17-parameter tool with no output schema and no annotations, yet the description explains almost nothing: no expected behavior, no input semantics, no return value, and no usage context. An agent cannot confidently select or invoke this tool based on the current description. The price detail is the only concrete contextual signal.

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 schema has 17 parameters with 0% description coverage, and the tool description mentions none of them. Required fields like product_value and expected_sale_price are only inferable by their names, while the many optional cost, fee, and rate parameters (e.g., duty_rate_pct, marketplace_fee_pct, returns_reserve_pct) are left entirely undocumented. The description does nothing to compensate for the absence of schema descriptions.

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, 'Premium end-to-end GCC product decision,' essentially restates the tool title and lacks an actionable verb or specific resource. It does not explain what a 'GCC product decision' is, what it computes, or what output it produces. This makes it nearly tautological and fails to distinguish it from sibling tools like gf.gcc_opportunity_score or gf.gcc_portfolio_rank.

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?

There is no guidance about when to use this tool versus alternatives. The phrase 'Premium' suggests this is a paid or higher-tier option, but no explicit conditions, exclusions, or sibling comparisons are provided. Agents cannot determine whether this tool or a free sibling like gf.free_profit_check is the right choice.

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 burden of behavioral disclosure. The verb 'List' implies a read-only operation, and the description enumerates the content categories returned. However, it does not disclose response format, pagination, authentication needs, or any other operational traits.

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, tightly worded sentence that front-loads the action and names all content areas without extraneous words. Every word 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 zero-parameter read-only catalog tool, the description is largely complete: it names the five content areas returned. The absence of an output schema is mitigated by this enumeration, though terms like 'identity' remain somewhat ambiguous.

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 declares zero parameters, so there are no parameter semantics to explain. The description correctly focuses on what the tool returns rather than inputs, matching the baseline 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 uses a specific verb, 'List', and identifies the resource as a service catalog containing schemas, prices, identity, robot-priority policy, and discovery URLs. It is clear, but it does not explicitly distinguish itself from sibling tools like search_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?

No guidance is provided on when to use this tool versus alternatives such as search_capabilities or provider_health. There are no exclusions, prerequisites, or conditions stated.

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 of behavioral disclosure. It explicitly discloses the key safety-relevant behavior: no funds are moved. This is the most important behavioral trait for a quote/calculation tool. It does not go further into side effects or state changes, but for a non-mutating calculator this is reasonably transparent.

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 with no filler. It states the action, the outputs, and the key safety constraint compactly. Every word 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 tool has no output schema and no annotations, so the description should explain return behavior and default behavior for the optional take_rate_bps. It does neither. It is unclear what happens when take_rate_bps is omitted, whether the take rate is an input or an output, and what shape the quote result takes. For a fee-quote tool this is a meaningful 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 0%, so the description must compensate for missing parameter meaning, but it does not clearly map the inputs. 'gross_amount_usdc' and 'take_rate_bps' are never explained, and the relationship between the optional take_rate_bps input and the described 'calculate marketplace take rate' output is ambiguous. The description adds little beyond the parameter names already present in 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 states a specific verb ('Calculate'), a precise resource ('marketplace take rate and provider net'), and an explicit boundary ('without moving funds'). This clearly distinguishes it from execution-oriented siblings like gf.execute and from generic quoting tools, since it names exactly what it computes.

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 phrase 'without moving funds' implies the tool is for estimation rather than execution, which is a useful context cue. However, the description does not explicitly say when to prefer this over siblings such as gf.quote or gf.execute, nor does it name alternatives or provide exclusions. The usage guidance is implied rather than stated.

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?

There are no annotations, so the description carries the behavioral burden. It does disclose that the operation is a read and that it will not resend the signed payment, which is useful safety context. It does not mention authentication, failure behavior, or what 'durable status' means.

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, compact sentence with no filler. The core purpose and the key non-resending guarantee are front-loaded, making it easy for an agent to parse quickly.

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's low complexity, the description is minimally viable for selecting and invoking it with transactionId. However, with no output schema and no explanation of includeResult or the returned 'recovered result' shape, there are clear gaps an agent would need to resolve.

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 0%, so the description must compensate. It indirectly maps 'transaction' to transactionId and 'result' to includeResult, but it never explains what includeResult controls or how transactionId is used. This leaves the optional parameter's semantics unclear.

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 operation ('Read') and the resource ('durable status or recovered result for a GF payment transaction'). It is specific enough to identify the tool's function, but it does not explicitly contrast it with sibling status tools like gf.settlement_status or gf.universal_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 phrase 'without resending the signed payment' implies a use case: retrieve status instead of re-sending the payment. However, it does not explicitly state when to prefer this tool over related status tools or provide exclusions or alternative conditions.

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 of behavioral disclosure. It only says 'Read,' which implies a read-only operation, but it does not explain what 'verified' means, whether results are filtered, what side effects or auth requirements exist, or how latency/circuit-breaker data is represented.

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 sentence that front-loads the verb and resource. It contains no filler and is appropriately sized for a simple read operation.

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 one optional parameter and no output schema, the description covers the core purpose but leaves gaps: it does not describe the return shape, ordering, or what 'verified' filters out. These gaps are meaningful because no output schema or annotations fill them.

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 0%, and the description does not mention the 'limit' parameter at all. The parameter name and min/max constraints in the schema give some inherent meaning, but the description adds no further explanation of how limit affects the returned provider health data.

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 ('Read') and a specific resource: provider health, circuit-breaker, and latency state. This makes the tool's purpose understandable, though it does not explicitly contrast it with sibling status/list tools like gf.universal_status or gf.list_services.

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 guidance is given about when to use this tool versus alternatives. There are no exclusions, conditions, or references to sibling tools, leaving the agent to infer usage solely from the tool's name and brief description.

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 explicitly states it does not change fixed settlement prices, which is a genuine behavioral guarantee beyond the schema and beyond the absent annotations. However, it is silent on whether the tool mutates anything else, executes a transaction, or is read-only, so behavioral disclosure is only partial.

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 concise sentence with no filler, and the key constraints are front-loaded. It is appropriately sized for a tool description and contains no redundant restatement of the 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?

With no annotations, no output schema, and seven undocumented parameters, a single vague sentence leaves out nearly everything needed for correct invocation: parameter semantics, required fields, output shape, side effects, and distinction from sixteen sibling tools. The description is far from complete for a tool of this 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?

The schema contains seven parameters with 0% description coverage, and the description references only an abstract 'agent budget' without mapping to any specific field. It does not clarify the roles of goal, task, intent, product_count, budget_usdc, max_spend_usdc, or description, leaving the agent unable to determine what to pass.

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 an action ('choose'), a resource ('GF commerce outcome'), and constraints ('within the agent budget', 'without changing fixed settlement prices'), so it is not a tautology. However, 'highest-value GF commerce outcome' is vague and does not define what an outcome is or what quoting entails, and it does little to distinguish this from siblings like gf.gcc_opportunity_score or gf.free_profit_check.

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 only usage signal is the budget and fixed-price constraint, from which an agent might infer a selection task under budget limits. It names no alternatives, no conditions for when to prefer this over gf.execute or gf.marketplace_fee_quote, and no when-not-to-use 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly states the operation is a read ('Read aggregate...') and adds an important privacy guarantee ('without exposing buyer identities'). This is meaningful behavioral context beyond the tool name, though it does not cover caching, auth, or output shape.

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, well-structured sentence that front-loads the core action and resource, then adds the privacy constraint. Every part earns its place, and there is no 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 tool's main purpose and privacy stance, which is enough for a basic no-argument invocation. However, it does not document the optional 'days' parameter or describe what the response will look like, and there is no output schema to compensate. For a low-complexity tool this is adequate but not fully complete.

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 has a single optional 'days' parameter, but schema description coverage is 0% and the tool description never mentions it. The parameter's name implies a time window, but the description adds no explanation of how 'days' affects the returned metrics or whether it is a lookback period, which leaves meaningful ambiguity for an agent.

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 ('Read') and names a concrete resource: aggregate discovery, quote, payment, confirmed revenue, and repeat-buyer metrics. It also adds a key scope qualifier ('without exposing buyer identities'), which helps distinguish this analytics-oriented tool from sibling tools like gf.quote or gf.payment_status that likely operate at a more transactional or identity-specific level.

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 tool is for aggregate revenue metrics rather than buyer-level or individual transaction lookup, but it never explicitly states when to prefer it over sibling tools such as gf.free_profit_check, gf.payment_status, or gf.gcc_opportunity_score. There is no direct when-to-use or when-not-to-use guidance, only an implied analytics context.

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, the description carries the full burden. It discloses the 0.25 USDC price via x402, but does not explain whether this initiates payment, requires an existing payment signature, or what side effects or outputs occur.

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 very brief and front-loaded, naming the core purpose before the pricing detail. It is not bloated, but the brevity comes at the cost of missing behavioral and parameter guidance.

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, no annotations, and 8 parameters, this description leaves too much unknown: what the result looks like, how the x402 payment is handled, and how optional fields affect the calculation. It is minimally functional but not adequate for safe autonomous 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 0%, and the description adds only general context about landed cost. It does not clarify ambiguous parameters like referralCode, paymentSignature, currency defaults, or whether shipping and insurance are optional despite being non-required.

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 this tool performs a Saudi import landed-cost calculation. It is specific enough to distinguish it from generic pricing tools like gf.quote or gf.marketplace_fee_quote, though it does not explicitly name siblings.

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?

There is no guidance on when to choose this tool over alternatives, no scenario examples, and no mention of prerequisites such as requiring a prior payment or x402 session. The paid nature is mentioned but not contextualized.

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 present, so the description carries the full disclosure burden. It only says 'Rank' but does not disclose whether the operation is read-only, how results are ordered, whether results are limited, what response shape to expect, or any side effects.

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 sentence that is concise and front-loaded with the main action and criteria. It could be more structured given the parameter complexity, but it has no fluff.

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 10 parameters, no annotations, no output schema, and zero schema description coverage, this single-sentence description is inadequate for an agent to invoke the tool correctly. It omits required/optional param semantics, the meaning of goal/task/query/limit, and expected return behavior.

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 0%, so the description must compensate. It maps a few parameters ('intent', 'budget', 'region', 'protocol', 'preferred_payment') but leaves 'goal', 'task', 'limit', and 'query' semantically unexplained, which is insufficient for a 10-parameter 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 uses a specific verb ('Rank') and identifies the resource ('native and verified provider capabilities') with explicit filtering criteria. It is clear about what the tool does, though it does not explicitly differentiate it from siblings such as gf.list_services or gf.gcc_portfolio_rank.

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 guidance is provided about when to use this tool instead of alternatives, and there are no stated prerequisites or exclusions. The only implied usage is that it searches/ranks capabilities based on the listed dimensions.

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 of behavioral disclosure. It hints at non-destructive behavior ('without initiating payment') but does not explicitly state that the tool is read-only, nor does it disclose other behaviors such as authentication requirements, rate limits, or side effects. The description is minimal and leaves room for ambiguity.

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, concise sentence that clearly communicates the dual functionality and the key constraint (no payment initiation). Every word adds value, and there is no redundancy.

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 one optional parameter and no output schema, the description is adequately complete. It covers both modes of operation (with and without order_id) and clarifies the non-payment nature. Given the simple scope, no additional context seems necessary.

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 sole parameter, order_id, is optional and just a string with no schema description. The description adds meaning by explaining that providing order_id allows inspecting a specific universal order, while omitting it describes active settlement adapters. This clarifies the parameter's role, which is valuable given 0% schema description coverage.

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's actions: to describe active settlement adapters or inspect one universal order. It also explicitly notes 'without initiating payment,' which differentiates it from payment-related tools like gf.payment_status. However, it doesn't name specific sibling tools, so it's not a 5.

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 when to use this tool (when you need to inspect adapters or an order without initiating payment) but does not explicitly state when not to use it or name alternatives like gf.payment_status or gf.universal_status. The 'without initiating payment' phrase hints at the exclusion but leaves routing 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Describe' implies an informational read-only operation, but the description does not explicitly state side effects, safety, output format, or what happens when called. The term 'safety boundaries' hints at some behavioral scope but remains undefined.

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 short sentence that is easy to parse and front-loads the main subject. However, it is vague enough that the brevity slightly hurts usefulness; it is concise but not optimally informative.

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 parameters, no output schema, and no annotations, the description is the only source of guidance. It fails to explain what the tool returns, how it relates to status-based siblings, or what 'safety boundaries' refers to. This is insufficient for an agent to confidently invoke the 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?

The input schema has zero parameters, so there is nothing for the description to explain. Per the baseline for 0-parameter tools, this dimension is well-served by 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 names a resource ('intent-first universal commerce gateway') and uses the verb 'describe', but it never explicitly states what the tool does. The title says 'status', so an agent might infer it retrieves status, but the description's wording suggests something more like an explanatory text. It does not clearly distinguish itself from status-like siblings such as gf.agent_commerce_status or gf.payment_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 provides no guidance on when to use this tool vs. alternatives. It does not state the intended context, prerequisites, or exclusions. With 17 siblings including several status tools, this is a significant omission.

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