Fail-closed refund, cancellation, return, and trial checks for 100 US subscription vendors.
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Average 3.9/5 across 4 of 4 tools scored.
Each tool evaluates a distinct policy aspect (cancellation penalty, refund, return, trial terms) with no overlap.
All names follow a consistent snake_case pattern with a clear noun_qualifier structure (e.g., cancellation_penalty).
Four tools is well-scoped for evaluating core subscription policies without redundancy.
Covers cancellation, refund, return, and trial policies comprehensively, though minor gaps like modification policies exist but are outside scope.
cancellation_penaltyCheck cancellation penaltyAEvaluate whether cancelling a US consumer subscription incurs a penalty or lock. Returns UNKNOWN when billing cadence is required or the policy needs manual review.
| Name | Required | Description | Default |
|---|---|---|---|
| plan | Yes | Plan type. Currently only 'individual' plans are supported. | |
| region | Yes | Region code. Currently only 'US' is supported. | |
| vendor | Yes | Vendor identifier (lowercase, underscore-separated). | |
| billing_cadence | No | Required when the vendor applies different cancellation terms to monthly and annual plans. |
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| policy | No | |
| vendor | No | |
| message | Yes | |
| penalty | No | |
| verdict | Yes | |
| notice_days | No | |
| source_hash | No | |
| evaluated_at | No | |
| rules_version | No | |
| policy_version | No | |
| billing_cadence | No | |
| rulebook_result | No | |
| required_context | No | |
| policy_source_url | No | |
| policy_last_checked | No | |
| policy_source_notes | No | |
| policy_last_verified_utc | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. Description adds value by stating the UNKNOWN return condition when billing cadence is needed or manual review is required, which is a key behavioral trait.
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 concise sentences with no wasted words. The key information is front-loaded and every sentence adds value.
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 an output schema present, description does not need to cover return format. It covers core purpose and an important edge case (UNKNOWN). Adequate for a tool with 4 parameters and clear annotations.
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 the schema already documents parameters well. Description adds marginal value by linking billing_cadence to the UNKNOWN return, but does not significantly enhance parameter understanding beyond 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?
Description clearly states the tool evaluates cancellation penalties for US consumer subscriptions and mentions an UNKNOWN return case. It does not explicitly differentiate from sibling tools, but the purpose is specific enough.
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 guidance on when to use this tool vs alternatives (refund_eligibility, return_eligibility, trial_terms). The mention of billing cadence requirement is mild usage context but not a clear guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
refund_eligibilityCheck refund eligibilityAEvaluate a US consumer subscription refund against versioned source-backed rules. Returns UNKNOWN when required conditions are absent or the vendor requires approval or manual policy review.
| Name | Required | Description | Default |
|---|---|---|---|
| plan | Yes | Plan type. Currently only 'individual' plans are supported. | |
| region | Yes | Region code. Currently only 'US' is supported. | |
| vendor | Yes | Vendor identifier (lowercase, underscore-separated). | |
| days_since_purchase | Yes | Number of days since the subscription was purchased. | |
| qualifying_conditions_met | No | Required when the vendor policy has source-specific conditions such as first purchase, unused benefits, or an eligible annual plan. |
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| vendor | No | |
| message | Yes | |
| verdict | Yes | |
| refundable | No | |
| source_hash | No | |
| window_days | No | |
| evaluated_at | No | |
| rules_version | No | |
| policy_version | No | |
| rulebook_result | No | |
| required_context | No | |
| policy_source_url | No | |
| days_since_purchase | No | |
| policy_last_checked | No | |
| policy_source_notes | No | |
| policy_last_verified_utc | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context by stating the tool returns UNKNOWN under specific conditions (missing required conditions, vendor approval needed). This goes beyond 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?
The description is two sentences, front-loads the core action, and contains no redundant information. Every sentence adds value.
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 presence of an output schema, the description does not need to detail return values. It covers the main evaluation behavior and the UNKNOWN edge case. Could mention versioning or rule updates, but overall adequate for a read-only check 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 100% description coverage, so parameter semantics are already well-defined. The description does not add additional meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool evaluates refund eligibility for US consumer subscriptions against versioned rules, and distinguishes itself by specifying the UNKNOWN return case. This clearly identifies the tool's purpose and differentiates it from sibling tools like cancellation_penalty or return_eligibility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking refund eligibility but does not explicitly contrast with sibling tools or state when not to use it. Without guidance on alternatives or exclusions, the agent must infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
return_eligibilityCheck return eligibilityAEvaluate whether a US consumer subscription purchase can be reversed under versioned source-backed rules. Returns UNKNOWN when required conditions are absent or manual review is required.
| Name | Required | Description | Default |
|---|---|---|---|
| plan | Yes | Plan type. Currently only 'individual' plans are supported. | |
| region | Yes | Region code. Currently only 'US' is supported. | |
| vendor | Yes | Vendor identifier (lowercase, underscore-separated). | |
| days_since_purchase | Yes | Number of days since the subscription was purchased. | |
| qualifying_conditions_met | No | Required when the vendor policy has source-specific conditions such as first purchase, unused benefits, or an eligible annual plan. |
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| method | No | |
| vendor | No | |
| message | Yes | |
| verdict | Yes | |
| returnable | No | |
| return_type | No | |
| source_hash | No | |
| evaluated_at | No | |
| rules_version | No | |
| policy_version | No | |
| rulebook_result | No | |
| required_context | No | |
| policy_source_url | No | |
| return_window_days | No | |
| days_since_purchase | No | |
| policy_last_checked | No | |
| policy_source_notes | No | |
| policy_last_verified_utc | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, indicating safe read operations. The description adds the detail that the tool returns UNKNOWN when conditions are absent or manual review is required, which is a behavioral trait beyond annotations. However, it lacks disclosure of other aspects like rate limits or auth needs.
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 front-loads the core purpose and key behavior (UNKNOWN return). Every word adds value, with no redundancy or filler.
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 presence of a complete input schema, annotations, and an output schema (indicated), the description sufficiently covers the tool's behavior. It could mention error handling or prerequisites, but for a simple eligibility check, the UNKNOWN detail adds necessary context. Slightly incomplete for a fully comprehensive view.
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 covers all 5 parameters with 100% description coverage, providing detailed meanings for each (e.g., enums, constraints). The tool description does not add additional parameter-level context beyond what the schema already provides, so it meets the baseline with no extra value.
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 evaluates return eligibility for US consumer subscription purchases under versioned source-backed rules, and explicitly mentions the UNKNOWN return state. This is specific and distinguishes from sibling tools like refund_eligibility or cancellation_penalty.
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 versus alternatives (cancellation_penalty, refund_eligibility, trial_terms). It does not mention prerequisites, context, or exclusions. The only implicit hint is 'US consumer subscription purchase', which is not sufficient to differentiate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trial_termsCheck trial termsAEvaluate a live US consumer subscription trial offer. Supply observed availability, duration, card, and auto-conversion facts; the tool returns UNKNOWN instead of inferring current offers from static data.
| Name | Required | Description | Default |
|---|---|---|---|
| plan | Yes | Plan type. Currently only 'individual' plans are supported. | |
| region | Yes | Region code. Currently only 'US' is supported. | |
| vendor | Yes | Vendor identifier (lowercase, underscore-separated). | |
| offer_confirmed | No | For account- or promotion-specific trials, whether a live offer has been confirmed for this account. | |
| observed_trial_days | No | Trial duration shown by the confirmed live offer. Required when offer_confirmed is true for a variable offer. | |
| observed_auto_converts | No | Whether the confirmed live offer converts to a paid subscription after the trial. | |
| observed_card_required | No | Whether the confirmed live offer requires a payment card. |
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| vendor | No | |
| message | Yes | |
| verdict | Yes | |
| trial_days | No | |
| source_hash | No | |
| evaluated_at | No | |
| auto_converts | No | |
| card_required | No | |
| rules_version | No | |
| policy_version | No | |
| rulebook_result | No | |
| trial_available | No | |
| required_context | No | |
| policy_source_url | No | |
| policy_last_checked | No | |
| policy_source_notes | No | |
| policy_last_verified_utc | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds value by disclosing that the tool returns UNKNOWN when observed facts are missing, which is beyond the annotations. 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?
The description consists of two clear sentences that are front-loaded with purpose and a key behavior. Every sentence adds value, with no redundant or extraneous 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?
Given the full schema, annotations, and presence of an output schema, the description covers the core behavior and data requirements. It implicitly notes the US-only and individual plan constraints via the schema, but could be slightly more explicit about output behavior. Still, it is fairly 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?
Schema description coverage is 100%, so the baseline is 3. The description groups parameters into 'availability, duration, card, and auto-conversion facts' but does not add new meaning beyond the schema's individual 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 clearly states the verb 'evaluate' and the resource 'live US consumer subscription trial offer', distinguishing it from sibling tools that deal with penalties and eligibility. It also clarifies the tool's unique behavior of returning UNKNOWN instead of inferring from static data.
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 explains when to use the tool (supply observed facts) and what it does not do (infer from static data), but does not explicitly mention when not to use it or compare with siblings. The context is clear but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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