Credinet

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds two pieces of context the annotations cannot express: that inputs must be non-sensitive, and that the result is documentation-only and not an eligibility determination — an important constraint on how to interpret output.

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, zero filler, with the primary use case front-loaded and the interpretive limit second. Nothing needs trimming.

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?

An output schema exists, so return values need not be described. Given that, the description supplies the two things an agent most needs: the trigger condition and the explicit statement that the result is not an approval decision. Complete for this tool's 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?

With schema description coverage at only 33% and a nested characteristics object containing eight sub-fields, the description does little beyond referring to 'supplied non-sensitive characteristics'. The 'non-sensitive' qualifier is a genuine addition, but it does not clarify field meaning; a 3 reflects partial compensation for the coverage gap.

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 ('checked') and resource ('documented requirements') scoped to 'one returned product', which implicitly distinguishes it from find_borrowing_products (which returns products) and get_product_details. A reader can tell what it does, though the explicit contrast with siblings is left to inference.

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?

'Use when a user wants documented requirements checked' gives a clear triggering context, and 'Never predicts eligibility or approval' acts as a boundary condition on interpretation. It does not, however, name an alternative tool for the case where the agent wants an eligibility judgement.

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 cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description still adds real behavior: it refuses to mix incompatible products or representative scenarios, which tells the agent failure conditions the annotations do not. It does not say what an 'incompatible' pairing produces or how errors surface.

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 compact sentences, front-loaded with the usage trigger before the limitation. Every clause carries information and nothing is repeated from 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?

An output schema exists, so return values need not be described, but the tool has four parameters with deep nested objects and low coverage. The description omits what context fields are needed and what happens when scenarios conflict, leaving meaningful gaps for a comparison 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 only 25% across four parameters, and the large nested context object is undocumented. The description adds only the 'scenario-bound' hint and the min-two requirement already enforced by minItems, so it fails to compensate for the coverage gap.

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?

Names a specific verb (compare) and resource (borrowing costs) with clear scope: two or more already-returned products. It implies the discovery-then-compare workflow of its siblings but never names find_borrowing_products or get_product_details to make the distinction explicit.

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?

'Use after product discovery' gives a concrete precondition, and 'two or more returned products' plus the no-mixing constraint set boundaries. It stops short of naming alternative tools or stating when NOT to use it (e.g., for a single product).

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 annotations already establish this as a safe, read-only, idempotent operation. The description adds the useful caveat that it returns governed match states rather than eligibility or approval, but it does not explain what those match states mean or other operational 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, both front-loaded and purposeful: the first gives the usage trigger, the second gives the key output caveat. There is no wasted framing or repetition.

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 11 parameters, nested objects, and very low schema description coverage, the description is incomplete. It omits parameter guidance and does not help an agent understand how to supply term, amount, borrower type, or the many enums, even though the output schema reduces the need to explain return values.

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 9% for 11 parameters, so the description should compensate heavily but does not. It only hints at country and broad stated requirements, leaving term, amount, purpose, product_type, borrower_type, and nested object semantics entirely to the schema enums and types.

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 and resource: finding borrowing products that may fit stated requirements in a supported country. It also distinguishes the output from eligibility or approval, which helps separate it from check_product_requirements, 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?

It gives a clear usage trigger — when a user asks which borrowing products may fit requirements in a supported country. It does not name alternatives or state when not to use it, but the context is clear enough for routing.

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, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds only that it targets 'one canonical product' and returns 'evidence-backed' facts; it says nothing about permissions, scope, or result characteristics beyond that.

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 or repetition. It is efficiently sized, though its brevity comes at the cost of substance rather than being tight and complete.

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 input schema is complex (nested objects, many enums, a constrained execution_mode) and schema coverage is low, so the description carries a heavy burden it does not meet. The output schema does cover return values, but nothing explains the context object or how to build a valid 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 33% across three parameters, and the description explains none of them. The nested 'context' object with its many enums (purpose, borrower_type, offer_context, etc.) is left entirely to the schema, and the description's words 'applicability' and 'requirements' only loosely gesture at those fields.

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 implies retrieving facts about a single canonical product but never states a concrete verb+resource like 'Retrieve details for one product by ID'. It reads as a usage trigger rather than a purpose statement, and it does not differentiate itself from siblings such as check_product_requirements or compare_borrowing_costs.

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?

It does give a 'use when' condition covering evidence-backed facts, limitations, requirements, and applicability, which is more than nothing. However, it names no alternatives and gives no when-not-to-use guidance, which is a real gap given the overlapping check_product_requirements and find_borrowing_products siblings.

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