lemon-squeezy-mcp

Server Quality Checklist

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Latest release: v1.0.1
Disambiguation4/5
Most tools have distinct purposes targeting specific resources and actions, such as get_customer vs. list_customers or create_discount vs. delete_discount. However, some tools like get_financial_metrics and predict_churn_risk could overlap in analyzing subscription health, and search_orders vs. list_orders might cause confusion if an agent misinterprets filtering needs. Overall, descriptions help clarify, but minor ambiguities exist.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, such as create_customer, list_subscriptions, update_webhook, and get_order. There are no deviations in style (all snake_case) or verb usage, making the set predictable and easy for an agent to parse and understand.
Tool Count2/5
With 53 tools, the count is excessive for a typical MCP server, even for a comprehensive e-commerce platform like Lemon Squeezy. This many tools can overwhelm agents, increase complexity, and likely includes redundant or overly granular operations that could be consolidated. A well-scoped server typically has 3-15 tools, so this is a significant mismatch.
Completeness5/5
The tool set provides complete CRUD/lifecycle coverage for the Lemon Squeezy domain, including customers, subscriptions, orders, products, discounts, webhooks, and more. It covers creation, retrieval, listing, updating, deletion, and specialized operations like analytics, refunds, and integrations, with no obvious gaps that would hinder agent workflows.
Average 3/5 across 53 of 53 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 mentions 'soft delete' which implies the customer record is retained but marked as archived, but doesn't cover permissions needed, whether the action is reversible, side effects on related data, or response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It front-loads the core action and includes clarifying parenthetical information, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'archive' entails operationally, what the tool returns, error conditions, or how it fits into broader customer management workflows alongside siblings like 'list_customers' or 'get_customer'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the single 'customerId' parameter. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('archive') and resource ('a customer'), with the parenthetical '(soft delete)' adding specificity about the deletion type. However, it doesn't explicitly differentiate from sibling tools like 'delete_discount' or 'update_customer' beyond the resource focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'update_customer' for status changes or 'delete_discount' for hard deletions. The description lacks context about prerequisites, recovery options, or typical workflows.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Cancel a subscription' implies a destructive mutation, but it doesn't specify whether this is reversible, requires specific permissions, affects billing, or has side effects like data retention. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words, making it highly efficient and front-loaded. Every word earns its place by conveying the core action without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive mutation tool with no annotations and no output schema, the description is inadequate. It lacks critical details like return values, error conditions, or behavioral implications, failing to compensate for the missing structured data and leaving the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, fully documenting the 'subscriptionId' parameter. The description adds no additional semantic context beyond what the schema provides, such as format examples or validation rules, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Cancel') and resource ('a subscription'), making the purpose immediately understandable. However, it doesn't distinguish this from sibling tools like 'update_subscription' or 'archive_customer' which might also involve subscription changes, missing full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'update_subscription' for modifying subscriptions or 'archive_customer' for broader customer actions. It lacks context about prerequisites, timing, or exclusions, offering minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'create' implies a write operation, the description doesn't reveal important behavioral aspects like authentication requirements, rate limits, whether this initiates a payment flow, what happens on success/failure, or what the response contains. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for the tool's purpose and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that creates checkout sessions (a potentially complex financial operation) with 8 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what a 'checkout session' entails, what happens after creation, or provide any context about the broader checkout process. The description leaves too many behavioral questions unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'product variant' which relates to the variantId parameter, but doesn't add meaningful semantic context beyond what the schema already provides. With 100% schema description coverage, the baseline is 3, and the description doesn't significantly enhance understanding of parameter purposes or relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('create') and resource ('checkout session for a product variant'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential siblings like 'create_customer' or 'create_discount' beyond the specific resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There's no mention of prerequisites, when this should be used instead of other checkout-related tools (none listed in siblings), or any contextual constraints for creating checkout sessions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states it creates a customer but doesn't disclose what happens on success/failure, whether it's idempotent, if it requires specific permissions, or how it handles duplicates. For a mutation tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or behavioral constraints. Given the mutation nature and lack of structured data, more context is needed for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 6 parameters. The description adds no parameter-specific information beyond implying a 'store' context, which is already covered by the 'storeId' parameter description. Baseline 3 is appropriate when the schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and resource ('new customer in a store'), making the purpose immediately understandable. It distinguishes from obvious siblings like 'update_customer' or 'list_customers' by specifying creation, though it doesn't explicitly differentiate from all potential creation tools like 'create_checkout'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., store existence), when not to use it (e.g., for existing customers), or refer to sibling tools like 'update_customer' for modifications or 'list_customers' for viewing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It states this is a creation operation (implying mutation) but doesn't cover permissions needed, whether the discount is immediately active, error conditions, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for what it communicates, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 7 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, error handling, side effects, or how it differs from related operations. The agent lacks critical context needed to use this tool effectively beyond basic parameter passing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema descriptions (e.g., explaining relationships between 'duration' and 'durationInMonths'). Baseline 3 is appropriate when the schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and resource ('a new discount code'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get_discount' or 'delete_discount' beyond the obvious verb difference, which prevents 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.
Usage Guidelines2/5
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 like 'update_customer' for modifying existing discounts or 'list_discounts' for viewing them. There's no mention of prerequisites, constraints, or typical use cases, leaving the agent to infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Create' implies a write operation, but it doesn't disclose behavioral traits like permissions needed, whether it's idempotent, rate limits, error conditions, or what happens on success. The parenthetical about billing adds some context but insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the core purpose. The parenthetical adds useful context without verbosity. No wasted words, though it could be slightly more structured (e.g., separating purpose from context).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error handling, or important behavioral aspects like side effects. The 100% schema coverage helps with parameters, but overall context is lacking for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the three parameters. The description doesn't add any meaning beyond what's in the schema (e.g., no examples of 'action' values, no explanation of how 'quantity' interacts with billing). Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('create') and resource ('usage record for a subscription item'), with the parenthetical adding context about usage-based billing. It distinguishes from siblings like 'get_usage_record' (read) and 'create_customer' (different resource), though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 versus alternatives. The description implies it's for billing-related usage tracking, but doesn't mention prerequisites, constraints, or when to choose other tools like 'update_subscription' for different modifications.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Create' which implies a write operation, but doesn't disclose behavioral traits like required permissions, whether this is idempotent, rate limits, or what happens on success/failure. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and appropriately sized for its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what a webhook does in this system, what happens after creation, or provide any behavioral context. The agent lacks crucial information to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no additional meaning beyond the schema's parameter descriptions, such as explaining event types or secret usage. Baseline 3 is appropriate when the schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and resource ('a new webhook'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'update_webhook' or 'delete_webhook' beyond the basic verb, nor does it specify what a webhook is in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'update_webhook' or 'get_webhook'. The description lacks context about prerequisites, such as needing an existing store, or when webhook creation is appropriate versus other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the action is 'Delete' which implies a destructive, irreversible mutation, but doesn't disclose behavioral traits such as permission requirements, whether deletion is permanent or soft, error handling, or rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence 'Delete a discount.', which is front-loaded and wastes no words. Every part of the sentence directly contributes to understanding the tool's purpose, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a destructive operation with no annotations and no output schema, the description is incomplete. It lacks crucial context such as what happens post-deletion, return values, error conditions, or dependencies. For a mutation tool, this minimal description fails to provide sufficient guidance for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'discountId' documented in the schema as 'The discount ID'. The description adds no additional meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Delete') and resource ('a discount'), making the purpose immediately understandable. It distinguishes from sibling tools like 'create_discount' and 'get_discount' by specifying the destructive action. However, it doesn't specify what type of discount (e.g., coupon, promotion) or system context, keeping it from 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.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing an existing discount ID), exclusions, or compare with related tools like 'archive_customer' or 'cancel_subscription' for similar destructive operations. Usage is implied only by the verb 'Delete'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Delete' implies a destructive, irreversible mutation, but the description doesn't mention permissions required, confirmation steps, side effects (e.g., stopping notifications), or error handling. This is inadequate for a destructive operation with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action ('Delete a webhook'), making it immediately scannable and appropriate for a simple tool. Every word earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a destructive mutation tool with no annotations and no output schema, the description is incomplete. It lacks critical context like what happens post-deletion, return values, error cases, or system-specific behaviors. For a tool that permanently removes resources, this minimal description poses risks for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter 'webhookId'. The description adds no additional meaning about the parameter (e.g., where to find the ID, format constraints, or examples). This meets the baseline of 3 since the schema does the heavy lifting, but no value is added beyond it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Delete') and resource ('a webhook'), making the purpose immediately understandable. It distinguishes from siblings like 'create_webhook' and 'update_webhook' by specifying the deletion action. However, it doesn't specify what type of webhook or system context, which prevents 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.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing an existing webhook ID), when not to use it, or how it relates to siblings like 'list_webhooks' for finding IDs or 'create_webhook' for replacement. This leaves the agent with minimal contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 but offers minimal information. It implies a write operation (generating an invoice) but doesn't specify if this creates a new record, triggers notifications, requires permissions, or has side effects like updating order status. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero waste, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (mutation with 8 parameters), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., invoice ID, PDF link), error conditions, or behavioral details, leaving significant gaps for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 8 parameters (orderId required, others optional for customer details). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints, meeting the baseline score of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Generate an invoice for an order,' which specifies the verb (generate) and resource (invoice for an order). It distinguishes from sibling tools like 'generate_subscription_invoice' by focusing on orders rather than subscriptions, though it doesn't explicitly mention this distinction in the description itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., order must exist), exclusions, or compare it to similar tools like 'generate_subscription_invoice' or 'issue_order_refund,' leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states 'generate' which implies a write/mutation operation, but doesn't clarify whether this creates a new invoice, triggers billing, requires specific permissions, has side effects (e.g., sending notifications), or what the output contains. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool with one parameter and is front-loaded with the core action. Every word earns its place, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool (implied by 'generate') with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, error conditions, permissions needed, or how it differs from similar invoice operations. For a tool that likely creates financial records, more context about behavior and outcomes is needed for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents the single parameter 'subscriptionInvoiceId' with its type and description. The tool description adds no additional parameter context beyond what's in the schema (e.g., format examples, relationship to other entities, or why this ID is needed). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and the resource 'invoice for a subscription', making the purpose immediately understandable. It distinguishes from sibling tools like 'generate_order_invoice' by specifying subscription context, though it doesn't explicitly contrast with other invoice-related tools. The description avoids tautology by not just restating the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing an existing subscription), contrast with similar tools like 'generate_order_invoice' or 'issue_subscription_invoice_refund', or indicate when this operation is appropriate versus other invoice-related actions. The agent must infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read operation ('Get details') but doesn't disclose authentication requirements, rate limits, error conditions, or what details are returned. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence contributes directly to understanding the tool's function, making it appropriately concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple single-parameter input, the description is incomplete. It doesn't explain what 'details' are returned, potential error cases, or how this tool fits into broader workflows with siblings. For a tool in a rich ecosystem with many alternatives, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the single parameter 'customerId' as a number. The description adds no additional semantic context beyond implying it's used to identify a customer, which is already clear from the schema. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get details') and resource ('specific customer by ID'), making the purpose immediately understandable. It distinguishes from sibling 'list_customers' by specifying retrieval of a single customer rather than multiple, though it doesn't explicitly mention all siblings like 'analyze_churn_risk' or 'update_customer'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention when to choose 'get_customer' over 'list_customers' for multiple customers, or when to use other sibling tools like 'update_customer' for modifications or 'analyze_churn_risk' for analysis.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'Get details' implies a read operation, the description doesn't specify what details are returned, whether authentication is required, error conditions, rate limits, or response format. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple single-parameter input schema, the description is inadequate. It doesn't explain what 'details' are returned, error handling, authentication requirements, or how this tool relates to sibling tools. For even a simple retrieval tool, more context is needed for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'by ID' which aligns with the 'fileId' parameter in the schema. With 100% schema description coverage (the schema already documents 'fileId' as 'The file ID'), the description adds minimal value beyond what's in the structured data. It doesn't provide additional context about ID format, sources, or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get details') and resource ('a specific file by ID'), making the purpose unambiguous. It distinguishes from sibling tools like 'list_files' by specifying retrieval of a single file rather than listing multiple files. However, it doesn't explicitly differentiate from other 'get_' tools that retrieve different resource types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention when to use 'get_file' versus 'list_files' for multiple files, or versus other 'get_' tools for different resources. There's no context about prerequisites, permissions, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool 'calculates' metrics but doesn't disclose whether this is a read-only operation, whether it requires specific permissions, what data sources it uses, or how it handles large date ranges. For a financial calculation tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first lists the comprehensive metrics calculated, the second mentions the date range filtering capability. Every element serves a purpose with zero wasted words, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a financial metrics calculation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what specific metrics are returned, their format, whether calculations are real-time or cached, or any limitations. With 3 parameters and complex financial calculations implied, more context is needed for an agent to use this effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all three parameters (storeId, startDate, endDate) with their types and formats. The description mentions 'supports date range filtering' which aligns with startDate/endDate but doesn't add meaningful semantic context beyond what the schema provides. The baseline of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates comprehensive financial metrics and lists specific metric categories (revenue, MRR/ARR, subscription metrics, order statistics, customer metrics). It distinguishes itself from siblings by focusing on financial metrics calculation rather than data retrieval or CRUD operations. However, it doesn't explicitly differentiate from potential similar financial analysis tools that might exist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions date range filtering but provides no guidance on when to use this tool versus alternatives. With many sibling tools for retrieving specific data (get_customer, get_order, list_subscriptions, etc.), there's no indication whether this tool aggregates across those entities or when to prefer direct data retrieval versus this comprehensive calculation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states a read operation ('Get details') but does not mention potential errors (e.g., invalid ID), permissions required, rate limits, or response format. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded and wastes no space, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description is minimal. It covers the basic purpose but lacks context on usage guidelines, behavioral traits, or output details, making it incomplete for effective agent use despite the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, documenting the single parameter 'licenseKeyId' as a number. The description adds no additional semantic details beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high schema coverage without enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get details') and resource ('a specific license key by ID'), making the purpose evident. However, it does not explicitly distinguish this tool from its sibling 'list_license_keys', which might retrieve multiple keys, so it misses full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'list_license_keys' or other get_* tools. It lacks context on prerequisites, such as needing a valid license key ID, or exclusions, leaving the agent without clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it 'gets details' but doesn't disclose behavioral traits like whether it's a read-only operation (implied but not confirmed), error handling (e.g., for invalid IDs), authentication needs, rate limits, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Get details') and resource ('order item by ID'). There is zero wasted wording, and it directly communicates the essential information without redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple single-parameter input, the description is incomplete. It lacks details on behavioral aspects (e.g., read-only nature, error responses), return values (since no output schema exists), and usage context. For a tool in a server with many siblings, more guidance would help agents use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'orderItemId' documented as 'The order item ID'. The description adds no additional meaning beyond this, such as format examples (e.g., numeric range) or context (e.g., where to find the ID). Given high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'details of a specific order item by ID', making the purpose unambiguous. It distinguishes from siblings like 'list_order_items' (which returns multiple items) by specifying retrieval of a single item. However, it doesn't explicitly contrast with 'get_order' (which might retrieve the parent order), leaving slight room for improvement in sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing a valid order item ID), exclusions (e.g., not for bulk retrieval), or comparisons to siblings like 'list_order_items' for multiple items or 'get_order' for parent order details. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it retrieves details without disclosing behavioral traits like error handling, authentication needs, rate limits, or what 'details' entails. This is inadequate for a read operation with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a simple parameter, the description is too minimal. It lacks context on return values, error cases, or how it fits with siblings like 'list_stores', making it incomplete for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter 'storeId'. The description adds no additional meaning beyond implying ID-based lookup, meeting the baseline for high schema coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get details') and resource ('specific store by ID'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_stores' or explain what 'details' includes, which prevents 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.
Usage Guidelines2/5
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 like 'list_stores' or 'get_customer', nor does it mention prerequisites such as needing a valid store ID. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('Get details') but lacks critical information: whether this is a read-only operation, authentication requirements, error handling (e.g., for invalid IDs), rate limits, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('Get details', 'specific subscription invoice', 'by ID') contributes directly to understanding, making it appropriately sized and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, 100% schema coverage) but lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like safety, response format, or error conditions, which are crucial for an agent to use it correctly. For a read operation with no structured output guidance, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'subscriptionInvoiceId' fully documented in the schema. The description adds no additional meaning beyond implying the parameter is required for lookup. Since the schema handles the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('details of a specific subscription invoice by ID'), making the purpose immediately understandable. It distinguishes this tool from sibling tools like 'list_subscription_invoices' by specifying retrieval of a single invoice via ID. However, it doesn't explicitly contrast with other get_* tools (e.g., 'get_subscription'), which slightly limits differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing a valid invoice ID), exclusions, or comparisons to sibling tools like 'list_subscription_invoices' for bulk retrieval or 'generate_subscription_invoice' for creation. Usage is implied but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a read operation ('Get details'), which implies safety, but doesn't mention authentication requirements, rate limits, error conditions, or what 'details' includes (e.g., fields returned). This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'details' are returned, potential errors, or behavioral traits like idempotency. For a read tool in a complex domain with many siblings, this leaves the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents the single parameter 'subscriptionItemId'. The description adds no additional meaning beyond what's in the schema (e.g., format examples, constraints, or relationship to other tools), meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get details') and resource ('specific subscription item by ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_subscription' or 'list_subscription_items', which would be needed for 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.
Usage Guidelines2/5
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 like 'get_subscription' or 'list_subscription_items'. It lacks context about prerequisites, typical use cases, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool retrieves 'current usage statistics,' implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns real-time or cached data, or details the response format. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get current usage statistics for a subscription item') and adds a brief, relevant context ('useful for usage-based billing'). There is no wasted text, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a read operation with one parameter), no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., authentication needs, data freshness), usage guidelines compared to siblings, and expected return values, leaving the agent with insufficient context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the 'subscriptionItemId' parameter. The description adds no additional parameter details beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('current usage statistics for a subscription item'), and it adds helpful context about usage-based billing. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_usage_record' or 'get_subscription_item', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance by mentioning 'useful for usage-based billing,' which implies a context but doesn't specify when to use this tool versus alternatives like 'get_usage_record' or 'get_subscription_item.' No explicit when/when-not instructions or prerequisites are included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'Get details' implies a read operation, the description doesn't specify authentication requirements, rate limits, error conditions, or what format/details are returned. For a tool with zero annotation coverage, this leaves significant behavioral gaps for an agent to understand.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and multiple sibling tools that could cause confusion, the description is insufficiently complete. A simple retrieval tool needs more context about what 'details' are returned, how this differs from listing operations, and any behavioral constraints. The current description leaves too many questions unanswered for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'usageRecordId' clearly documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'details of a specific usage record by ID', making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_usage_records' or 'get_subscription_item_usage', which could cause confusion about when to use this specific retrieval tool versus other related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With siblings like 'list_usage_records' and 'get_subscription_item_usage', there's no indication of when this single-record retrieval is preferred over listing or other specific retrieval methods. The description lacks any context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states 'Get details' but doesn't clarify what details are returned, whether it's a read-only operation, if it requires authentication, or any error handling (e.g., for invalid IDs). This is inadequate for a tool that likely involves data retrieval with potential constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core action without unnecessary words. It's front-loaded with the main purpose and avoids redundancy, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'details' are returned, potential response formats, or error cases. For a data retrieval tool, this leaves significant gaps in understanding how to interpret results or handle failures.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal value beyond the input schema, which has 100% coverage and clearly documents the 'variantId' parameter as a number. The description mentions 'by ID' but doesn't provide additional context like ID format or sourcing, so it meets the baseline for high schema coverage without compensating with extra insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'product variant by ID', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_product' or 'list_variants', which would require mentioning it retrieves detailed information for a single variant rather than listing or getting product-level data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention sibling tools like 'get_product' for product details or 'list_variants' for listing variants, nor does it specify prerequisites such as needing a variant ID from another operation. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states this is a read operation ('Get details'), which implies non-destructive behavior, but doesn't cover aspects like authentication requirements, error handling (e.g., for invalid IDs), rate limits, or response format. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Get details') without unnecessary words. Every part of the sentence contributes directly to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that retrieves data. It doesn't explain what details are returned (e.g., webhook configuration, status), error scenarios, or behavioral traits like idempotency. For a read operation with no structured support, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'webhookId' documented in the schema. The description adds minimal value by implying the parameter is used to identify a specific webhook, but doesn't provide additional context like ID format or sourcing. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get details') and resource ('a specific webhook by ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_webhooks' or 'create_webhook', which would require mentioning it retrieves a single webhook rather than listing or creating one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention sibling tools like 'list_webhooks' for multiple webhooks or 'update_webhook' for modifications, nor does it specify prerequisites such as needing an existing webhook ID.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Issue a refund' implies a financial mutation, but it doesn't disclose critical behaviors: whether this requires specific permissions, if it's reversible, what happens to order status post-refund, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a financial mutation tool with no annotations and no output schema, the description is inadequate. It doesn't cover behavioral traits (permissions, reversibility), output expectations (what the refund returns), or error conditions. Given the complexity and lack of structured data, more context is needed to guide safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('orderId' and 'amount') clearly documented in the schema. The description adds no additional semantic context beyond what's in the schema (e.g., it doesn't clarify if 'amount' must be less than or equal to order total, or if 'orderId' must be valid). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('issue a refund') and the target resource ('for an order'), making the purpose immediately understandable. It distinguishes from sibling tools like 'issue_subscription_invoice_refund' by specifying 'order' rather than 'subscription invoice'. However, it doesn't specify what type of refund (full/partial) or the scope of the operation, keeping it from 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.
Usage Guidelines2/5
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 like 'issue_subscription_invoice_refund' or 'cancel_subscription'. It doesn't mention prerequisites (e.g., order must be in a refundable state) or exclusions (e.g., cannot refund already refunded orders). The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'issue a refund' implies a financial transaction, it doesn't specify whether this requires special permissions, if the refund is immediate or processed later, what happens to the original invoice status, or any rate limits/constraints. This is a mutation tool with significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a tool with only 2 parameters and gets straight to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a financial mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after the refund is issued, what the response contains, error conditions, or business logic constraints. The agent would need to guess about important behavioral aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters thoroughly. The description doesn't add any additional meaning about the parameters beyond what's in the schema, so it meets the baseline expectation when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('issue a refund') and target resource ('for a subscription invoice'), providing a specific verb+resource combination. However, it doesn't differentiate from the sibling tool 'issue_order_refund' which handles refunds for orders rather than subscription invoices.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'issue_order_refund' or when refunds are appropriate versus cancellations. It doesn't mention prerequisites, constraints, or typical usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'optional filtering' and 'useful for finding' information, but lacks details on behavioral traits such as pagination behavior (implied by the 'page' parameter but not explained), rate limits, authentication requirements, or return format. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: the first states the purpose, and the second adds context. It is front-loaded with the core functionality. However, the second sentence could be more specific (e.g., clarifying what 'finding' entails), slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It does not explain return values, error conditions, or important behavioral aspects like pagination or filtering mechanics. For a list tool with multiple sibling alternatives, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters ('email' and 'page'). The description adds marginal value by mentioning 'optional filtering' in general, but does not provide additional semantics beyond what the schema specifies (e.g., how filtering works or pagination details). Baseline 3 is appropriate as the schema handles most documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List customers with optional filtering.' It specifies the verb ('List') and resource ('customers'), and mentions the scope includes 'customer information, subscription status, and order history.' However, it does not explicitly differentiate from sibling tools like 'get_customer' or 'search_orders,' which slightly reduces its specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance: 'Useful for finding customer information, subscription status, and order history.' It implies usage for retrieval but does not specify when to use this tool versus alternatives like 'get_customer' (for single customers) or 'search_orders' (for order-based queries). No explicit when-not or alternative recommendations are included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions filtering and implies pagination via the 'page' parameter, but doesn't describe the return format, pagination behavior, rate limits, authentication needs, or whether it's read-only. This leaves significant gaps for a tool with two parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List all discounts') and adds optional context. There's no wasted verbiage, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with no annotations and no output schema, the description is incomplete. It doesn't explain the return format, pagination behavior, or how results are structured. Given the complexity of listing operations and the lack of structured data, more contextual information would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters. The description adds marginal value by mentioning store filtering, but doesn't provide additional semantics beyond what's in the schema (e.g., format details for storeId or pagination behavior). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('discounts'), and includes optional filtering by store. However, it doesn't explicitly differentiate from sibling tools like 'get_discount' (which likely retrieves a single discount), leaving some ambiguity about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance, mentioning optional filtering by store but not explaining when to use this tool versus alternatives like 'get_discount' or other list tools. No context about prerequisites, exclusions, or typical use cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, if it requires authentication, pagination behavior beyond the 'page' parameter, rate limits, or what the output format looks like. The mention of 'optionally filtered' and 'page' parameter hints at some behavior but is insufficient for a mutation-free tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core action ('List files') and succinctly adds filtering details. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral transparency (e.g., read-only nature, pagination details), usage differentiation from siblings, and output expectations. While concise, it doesn't compensate for the missing structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds minimal value by mentioning filtering by 'product or variant', which aligns with 'productId' and 'variantId' parameters, but doesn't provide additional context like format examples or interdependencies. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('files'), and specifies optional filtering capabilities. It distinguishes from 'get_file' (singular retrieval) but doesn't explicitly differentiate from other list_* tools like 'list_products' or 'list_variants' that might return related resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions optional filtering by product or variant, which implies when to use those parameters, but provides no guidance on when to choose this tool over other list_* tools (e.g., 'list_products' for product metadata vs. 'list_files' for files). No exclusions or alternatives are specified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but reveals little. It mentions optional filtering but doesn't disclose pagination behavior, rate limits, authentication needs, or what 'list' entails (e.g., format, limits). For a read operation with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a read operation with two parameters, the description is incomplete. It lacks behavioral context (e.g., pagination details, response format) and doesn't compensate for the missing structured data, making it inadequate for reliable tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters. The description adds marginal value by mentioning filtering by order, which aligns with the 'orderId' parameter, but doesn't provide additional semantics beyond what's in the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('order items'), and specifies optional filtering by order. However, it doesn't distinguish this tool from similar sibling tools like 'list_orders' or 'get_order_item', which limits its score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance with 'optionally filtered by order', but offers no explicit when-to-use advice, no exclusions, and no alternatives. It doesn't help an agent choose between this and related tools like 'list_orders' or 'search_orders'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions listing 'all stores' but does not clarify key behaviors like pagination handling (implied by the 'page' parameter), rate limits, authentication needs, or output format. This leaves significant gaps for a tool that likely returns multiple items.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a list operation. It does not address behavioral aspects like pagination, response structure, or error handling, which are critical for an agent to use the tool effectively. The high schema coverage helps with parameters but does not compensate for missing context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'page' parameter documented as optional for pagination. The description adds no additional parameter semantics beyond what the schema provides, such as default values or pagination details. With high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all stores in your Lemon Squeezy account'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_store' (singular) or other list tools (e.g., 'list_customers'), which slightly reduces clarity in a crowded toolset.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as 'get_store' for a single store or other list tools for different resources. It lacks context about prerequisites, timing, or exclusions, leaving the agent to infer usage based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions listing and optional filtering, but lacks critical details: it doesn't specify if results are paginated (though 'page' parameter implies it), what the default ordering is, whether it requires authentication, rate limits, or what the output format looks like. For a listing tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List subscription invoices') and adds a brief qualifier ('optionally filtered by subscription'). There is zero waste or redundancy, making it appropriately concise for a simple listing tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It covers the basic purpose but misses behavioral context (e.g., pagination behavior, authentication needs) and output details. For a tool with two parameters and no structured safety or output information, more guidance is needed to ensure reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters ('subscriptionId' and 'page'). The description adds marginal value by mentioning optional filtering by subscription, which aligns with the 'subscriptionId' parameter, but doesn't provide additional semantics beyond what's in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List subscription invoices' with optional filtering by subscription. It specifies the verb ('List') and resource ('subscription invoices'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_subscription_invoice' (singular) or 'generate_subscription_invoice', which would be needed for 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance: it mentions optional filtering by subscription, but offers no explicit advice on when to use this tool versus alternatives. For example, it doesn't clarify when to choose 'list_subscription_invoices' over 'get_subscription_invoice' (singular) or how it relates to other listing tools like 'list_orders'. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only mentions filtering capability. It lacks critical behavioral details like pagination behavior (implied by 'page' parameter but not explained), rate limits, authentication needs, or response format, leaving significant gaps for a list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words, clearly front-loading the core purpose. It's appropriately sized for a simple list tool, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with no annotations and no output schema, the description is incomplete. It doesn't explain pagination behavior, return format, error conditions, or how it differs from similar siblings, leaving the agent under-informed despite the tool's relative simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds marginal value by explicitly stating the filtering purpose of 'subscriptionId', but doesn't provide additional semantics beyond what the schema already covers, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('subscription items'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'list_subscriptions' or 'get_subscription_item', which could cause confusion about scope boundaries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance by mentioning optional filtering by subscription, but offers no explicit when-to-use advice, alternatives (e.g., vs. 'get_subscription_item'), or exclusions. This leaves the agent with little context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions optional filtering but doesn't describe pagination behavior (implied by the 'page' parameter), return format, rate limits, authentication requirements, or whether this is a read-only operation. For a list tool with zero annotation coverage, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List all subscriptions') and adds the optional filtering detail. There's no wasted language or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with no annotations and no output schema, the description is insufficient. It doesn't explain what data is returned, pagination behavior, or how results are structured. While the purpose is clear, the lack of behavioral and output information makes it incomplete for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters fully. The description mentions filtering by 'store or customer' but the schema only has 'storeId' (not customer), creating a minor mismatch. It doesn't add meaningful semantics beyond what the schema provides, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('subscriptions'), and specifies optional filtering by store or customer. However, it doesn't explicitly differentiate from sibling tools like 'get_subscription' (singular) or 'list_subscription_items', leaving some ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'get_subscription' (for a single subscription) or 'list_subscription_items'. It mentions optional filtering but doesn't explain when filtering is appropriate or what happens without filters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool lists records with optional filtering, but doesn't disclose critical behaviors like pagination details (implied by the 'page' parameter), rate limits, authentication needs, or whether it's read-only (though listing implies it). This leaves significant gaps for safe agent operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List usage records') and adds a useful qualifier ('optionally filtered by subscription item'). There's no wasted language, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a listing tool. It doesn't explain return values (e.g., format, fields), pagination behavior (critical with a 'page' parameter), or error handling. This leaves the agent under-informed for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters fully. The description adds minimal value by mentioning optional filtering by subscription item, which aligns with the 'subscriptionItemId' parameter, but doesn't provide additional context beyond what's in the schema. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('usage records'), and specifies optional filtering by subscription item. However, it doesn't distinguish this tool from sibling tools like 'get_usage_record' or 'get_subscription_item_usage', which could cause confusion about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'get_usage_record' or 'get_subscription_item_usage'. It mentions optional filtering but doesn't explain when filtering is appropriate or what happens without it, leaving the agent to guess about context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it's a listing operation with optional filtering. It doesn't disclose whether this is paginated (though 'page' parameter hints at it), what permissions are needed, rate limits, response format, or whether it's safe/read-only. The description is minimal and leaves key behavioral traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes the key optional feature. Every word earns its place without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a listing tool with no annotations and no output schema, the description is insufficient. It doesn't explain the response format, pagination behavior (though hinted by 'page' parameter), error conditions, or how filtering works. Given the context of sibling tools like 'get_webhook', more differentiation and usage context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters. The description adds marginal value by mentioning 'optionally filtered by store' which aligns with 'storeId', but doesn't provide additional context beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all webhooks'), and specifies optional filtering by store. It distinguishes this as a listing operation rather than creation or deletion. However, it doesn't explicitly differentiate from sibling 'get_webhook' (singular retrieval) or other list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'get_webhook' (singular retrieval) or 'create_webhook'/'delete_webhook'/'update_webhook' (mutations). It mentions optional filtering but doesn't explain when filtering is appropriate or what happens without it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions cross-referencing across data sources, which adds some context, but fails to describe critical behaviors such as authentication requirements, rate limits, error handling, or what the output looks like (e.g., format, pagination). For a search tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, consisting of a single sentence that directly states the tool's function and includes helpful examples. There's no unnecessary information, and it efficiently communicates the core idea without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It covers the basic purpose and parameter semantics but misses essential behavioral details (e.g., how results are returned, error cases) and usage guidelines. For a tool that interacts with multiple data sources, more context is needed to ensure reliable agent operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'query' parameter documented as a natural language query. The description adds value by providing examples ('refunds from yesterday', 'subscriptions this week'), which clarify the expected format and semantics beyond the schema. However, it doesn't detail constraints or advanced usage, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: searching transactions using natural language queries. It specifies the verb 'search' and resource 'transactions', and mentions the cross-referencing across Lemon Squeezy and Firestore, which adds specificity. However, it doesn't explicitly differentiate from sibling tools like 'search_orders', leaving room for ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It mentions natural language queries but doesn't clarify if this is the preferred method over structured search tools like 'search_orders' or when to choose it based on context. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Update an existing customer's information' implies a mutation operation, but it doesn't disclose what permissions are required, whether changes are reversible, what happens to fields not specified, or what the response looks like. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a straightforward update operation and gets directly to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens when fields are omitted (partial updates?), what validation occurs, what error conditions exist, or what the tool returns. The agent would need to guess about important behavioral aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all 6 parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema (e.g., it doesn't explain relationships between parameters or provide usage examples). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('update') and resource ('existing customer's information'), making the purpose understandable. It distinguishes from obvious siblings like 'create_customer' and 'get_customer', but doesn't explicitly differentiate from other update tools like 'update_license_key' or 'update_subscription'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing an existing customer ID), when not to use it, or how it differs from other customer-related tools like 'sync_customer_to_crm' or 'archive_customer'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Update' implies a mutation, but it doesn't specify required permissions, whether changes are reversible, rate limits, or what happens on success/failure. The examples (activate, deactivate, update status) add some context but lack operational details needed for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be slightly more structured by separating examples or adding brief context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a mutation tool. It lacks behavioral details (e.g., side effects, error handling) and output expectations, leaving gaps that could hinder an AI agent's ability to use it correctly in complex scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear parameter documentation in the schema. The description doesn't add meaning beyond the schema (e.g., it doesn't explain licenseKeyId format or status implications), so it meets the baseline of 3. However, it doesn't compensate for any gaps since there are none in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('update') and resource ('license key'), with examples of actions (activate, deactivate, update status) that provide specificity. However, it doesn't explicitly differentiate from sibling tools like 'get_license_key' or 'list_license_keys', which would require mentioning it's for modifying rather than retrieving license data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing an existing license key), exclusions, or comparisons to siblings like 'create_customer' or 'update_subscription' that might involve license-related operations. The description only states what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it updates a subscription with examples. It doesn't disclose behavioral traits such as required permissions, whether changes are immediate or scheduled, impact on billing cycles, error conditions, or rate limits, leaving significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and includes helpful examples. It avoids redundancy, though it could be slightly more structured by separating use cases.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral transparency, error handling, and return values, making it inadequate for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all parameters. The description adds minimal value by hinting at purposes ('change plan' relates to variantId/productId, 'update billing details' relates to billingAnchor), but doesn't provide additional syntax or format details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Update') and resource ('a subscription'), and provides specific examples of what can be updated ('change plan, update billing details'). It distinguishes from siblings like 'cancel_subscription' by focusing on modifications rather than termination, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 versus alternatives like 'update_customer' or 'cancel_subscription'. The description implies usage for modifying subscriptions but lacks context on prerequisites, constraints, or comparisons with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Update an existing webhook' implies a mutation operation but provides no information about permissions required, whether changes are reversible, rate limits, error conditions, or what happens to unspecified fields. For a mutation tool with zero annotation coverage, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the essential action and resource. Every word earns its place, making it immediately scannable and understandable without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens during the update, what the response contains, error conditions, or side effects. The agent must rely entirely on the input schema and name inference, which is insufficient for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all 4 parameters with their types and optionality. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain parameter relationships, constraints, or provide examples. The baseline of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Update') and resource ('an existing webhook'), making the purpose immediately understandable. It distinguishes from sibling tools like 'create_webhook' and 'delete_webhook' by specifying it's for modifying existing webhooks rather than creating or deleting them. However, it doesn't specify what aspects can be updated (URL, events, secret) which would make it more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (like needing a webhook ID), when not to use it, or how it differs from similar operations. With siblings like 'create_webhook' and 'delete_webhook' available, the agent receives no contextual guidance about selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool 'Records' a decision, implying a write operation, but doesn't clarify if this is a one-time action, reversible, or requires specific permissions. The mention of a 'snapshot of current active user metrics' hints at data capture, but lacks details on what metrics are included or how they're stored. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose: 'Record a business decision with a snapshot of current active user metrics.' It avoids unnecessary words and gets straight to the point, making it easy for an agent to parse quickly. Every part of the sentence contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with 4 parameters) and the absence of annotations and output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavioral aspects like side effects, return values, or error handling. The high schema coverage helps, but for a tool that records decisions with metrics, more context on the 'snapshot' mechanism would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents all parameters (decision, rationale, expectedOutcome, category) with clear descriptions. The tool description doesn't add any additional meaning or context beyond what's in the schema, such as examples or formatting guidelines. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even without parameter info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Record a business decision with a snapshot of current active user metrics.' It specifies the verb ('Record') and resource ('business decision'), and the mention of 'snapshot of current active user metrics' adds useful context. However, it doesn't explicitly differentiate from sibling tools like 'archive_customer' or 'create_usage_record', which also involve recording data but for different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites, timing, or comparisons to sibling tools like 'create_usage_record' or 'archive_customer', which might be used in similar decision-making contexts. Without such context, the agent must infer usage based on the tool name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool retrieves details but doesn't describe what 'details' include (e.g., discount amount, validity period), whether it's a read-only operation (implied but not explicit), error handling (e.g., for invalid IDs), or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get details of a specific discount by ID'). There is no wasted verbiage, repetition, or unnecessary elaboration, making it easy for an agent to parse quickly. Every word serves a functional role in conveying the tool's intent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate but incomplete. It covers the basic purpose but lacks behavioral details (e.g., what 'details' entail) and usage context. Without annotations or an output schema, the description should do more to explain the tool's operation and expected results, leaving gaps for the agent to navigate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'discountId' parameter fully documented in the schema. The description adds no additional meaning beyond what the schema provides (e.g., no examples of valid IDs or format constraints). Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get details') and resource ('a specific discount by ID'), making the purpose unambiguous. It distinguishes from sibling tools like 'list_discounts' by specifying retrieval of a single discount rather than listing multiple. However, it doesn't explicitly contrast with other 'get_' tools (e.g., 'get_customer'), leaving some room for improvement in sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention prerequisites (e.g., needing a valid discount ID), contrast with 'list_discounts' for bulk retrieval, or specify use cases like verifying discount existence or fetching details for a known ID. Without such context, the agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool 'Get details' but doesn't mention whether this is a read-only operation, requires authentication, has rate limits, or what the return format looks like (e.g., JSON structure). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence earns its place by specifying the action, resource, and key input, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (single parameter, no output schema) and lack of annotations, the description is minimally adequate but incomplete. It covers the basic purpose but misses behavioral details and usage context. Without an output schema, it should ideally hint at return values, but the simplicity of the tool keeps it from being severely inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'productId' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get details') and resource ('specific product by ID'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_products' or 'get_variant', which would require mentioning this retrieves a single product's full details rather than listing multiple or getting variant-specific data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. For example, it doesn't specify that this is for retrieving a single product's details when you have the ID, as opposed to 'list_products' for multiple products or 'get_variant' for variant-specific information. The description implies usage but offers no explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool returns all matching orders, which hints at behavior, but lacks details on permissions, rate limits, pagination, or error handling. For a search tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences that are front-loaded: first states the action, second provides usage context, third specifies output. There's no wasted text, though it could be slightly more structured for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It doesn't explain return format, error cases, or behavioral constraints like search scope. For a tool with 1 parameter but missing structured context, it should provide more guidance on what 'returns all orders' entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'userEmail' documented as 'The email address of the customer.' The description adds minimal value by restating this as 'by email or customer email,' but doesn't clarify if it's exact match, partial, or case-sensitive. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for orders using email addresses, specifying 'by email or customer email' and 'returns all orders matching the email.' It distinguishes from siblings like 'list_orders' by focusing on email-based filtering, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context with 'useful for finding a payment when you only have a user's email address,' suggesting it's for lookup by email. However, it doesn't explicitly state when to use this vs. alternatives like 'get_order' (by ID) or 'list_orders' (general listing), leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 describes the tool's function but lacks details on permissions, rate limits, output format, or side effects. For a tool that likely involves data analysis, this omission is significant, as the agent cannot anticipate behavioral traits beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. Every word contributes to understanding the tool's function, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (analysis-based with no output schema) and lack of annotations, the description is minimally adequate. It explains what the tool does but doesn't cover output format, error handling, or integration with sibling tools. This leaves gaps in contextual understanding, though it meets the basic requirement for a no-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the schema's completeness. A baseline of 4 is appropriate as the tool requires no inputs, and the description adequately explains the operation without redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Identify users with active subscriptions who haven't logged in recently (>28 days).' It specifies the verb 'identify' and the target resource 'users with active subscriptions,' with a clear criterion for identification. However, it doesn't explicitly distinguish this from sibling tools like 'predict_churn_risk,' which might have overlapping or related functionality, preventing 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.
Usage Guidelines2/5
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. It doesn't mention prerequisites, exclusions, or comparisons to sibling tools such as 'predict_churn_risk' or 'list_customers,' leaving the agent to infer usage context. This lack of explicit direction reduces its effectiveness in tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions filtering and pagination (via schema), but lacks critical details: whether this is a read-only operation, what authentication is needed, rate limits, response format, or error conditions. For a list operation with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose ('List license keys') and adds only essential qualifying information about filtering.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a list operation with pagination and filtering, the description is incomplete. It should address behavioral aspects like read-only nature, response structure, or error handling to adequately guide an agent. The current description leaves significant gaps for practical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds minimal value beyond the schema by mentioning filtering by 'store or order,' which aligns with storeId and orderId parameters. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('license keys'), and specifies optional filtering capabilities. It distinguishes this tool from 'get_license_key' (singular retrieval) but doesn't explicitly differentiate from other list_* tools in the sibling set.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'optionally filtered by store or order,' suggesting when to apply filters. However, it provides no explicit guidance on when to use this tool versus alternatives like 'search_orders' or 'get_license_key,' nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions optional filtering but lacks critical behavioral details: it doesn't disclose pagination behavior (implied by 'page' parameter but not explained), rate limits, authentication requirements, or response format. The description is minimal and misses key operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes the key optional feature. Every word earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a list tool. It lacks details on pagination behavior, response structure, error handling, or any operational constraints. While concise, it doesn't provide enough context for reliable agent use beyond basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no additional meaning beyond mentioning optional store filtering, which is already covered in the schema. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('products'), with optional filtering by store. It distinguishes from 'get_product' (singular retrieval) but not from other list tools like 'list_variants' or 'list_orders', which have similar patterns but different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving products with optional store filtering, but provides no explicit guidance on when to use this versus alternatives like 'get_product' (for single product) or other list tools. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it's a list operation with optional filtering. It doesn't disclose behavioral traits like pagination details (implied by 'page' parameter but not explained), rate limits, authentication needs, or what 'list all' entails (e.g., default sorting, limits). This is a significant gap for a tool with potential data volume concerns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('List all product variants') and adds optional details concisely. There is zero waste, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a list operation with pagination (implied by 'page' parameter), the description is incomplete. It doesn't explain return values, pagination behavior, or error handling, leaving gaps for an AI agent to correctly invoke and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters ('productId' for filtering by product ID, 'page' for pagination). The description adds marginal value by mentioning filtering by 'product or store', but 'store' isn't in the schema, creating slight confusion. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and resource 'product variants', with optional filtering by product or store. It distinguishes from siblings like 'get_variant' (singular) and 'list_products', but doesn't explicitly contrast with other list tools like 'list_products' or 'list_stores' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving variants, optionally filtered, but provides no explicit guidance on when to use this vs. alternatives like 'get_variant' for a single variant or other list tools. It mentions filtering options but lacks context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the tool as a 'check' operation, implying read-only behavior, but doesn't disclose critical behavioral traits such as authentication requirements, rate limits, error conditions, or what happens if the subscriptionId is invalid. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose ('Check the status of a subscription') followed by specific use cases. Every word adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, read operation) and no output schema, the description provides basic purpose and usage but lacks details on return values, error handling, or behavioral context. With no annotations and incomplete behavioral transparency, it's adequate for a simple lookup but could be more complete for reliable agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'subscriptionId' fully documented in the schema. The description doesn't add any additional meaning beyond the schema, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check the status of a subscription' with specific details on what information it provides (credits, status, renewal dates, billing). It distinguishes from siblings like 'list_subscriptions' (which lists multiple) or 'update_subscription' (which modifies). However, it doesn't explicitly contrast with 'get_subscription_invoice' or 'get_subscription_item', which are related but different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by stating 'Use this to verify...', suggesting it's for checking subscription details. However, it doesn't explicitly state when to use this vs. alternatives like 'list_subscriptions' (for multiple subscriptions) or 'get_subscription_invoice' (for invoice-specific data). No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 adds useful context about sorting ('most recent first') and hints at filtering capabilities, but doesn't cover important aspects like pagination behavior (implied by the 'page' parameter), rate limits, authentication needs, or what happens with large result sets. It adequately describes a read operation but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences that are front-loaded with core functionality. The first sentence states the purpose, and the second adds context about use cases and sorting. There's minimal waste, though the use case examples could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (list operation with filtering), no annotations, and no output schema, the description is adequate but has clear gaps. It covers purpose and basic behavior but lacks details on output format, error handling, or comprehensive usage guidelines relative to siblings like 'search_orders'. It meets minimum viability but isn't fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters ('page' and 'storeId'). The description mentions 'optional filtering' which aligns with the schema but doesn't add any additional semantic meaning, syntax details, or examples beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as listing orders with optional filtering, which is a specific verb+resource combination. It distinguishes from 'get_order' (singular retrieval) but not explicitly from 'search_orders' (which might offer different filtering capabilities).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance by mentioning it's 'useful for finding recent payments, the last successful payment, or browsing order history,' which suggests common scenarios. However, it doesn't explicitly state when to use this versus 'search_orders' or other sibling tools, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions retrieving details but does not cover critical aspects such as authentication requirements, rate limits, error conditions, or response format. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence and uses a second sentence to specify key details retrieved. Both sentences are essential and waste no words, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with no output schema and no annotations, the description adequately covers the purpose and usage but lacks behavioral details like response structure or error handling. It is minimally viable but incomplete for full operational understanding, especially given the absence of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'orderId' clearly documented as 'The unique ID of the order'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieve details'), resource ('Lemon Squeezy order'), and key identifier ('by ID'), distinguishing it from siblings like 'list_orders' or 'search_orders' which handle multiple orders. It explicitly mentions what details are retrieved (payment status, order total, customer information), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'by ID' and listing the types of details retrieved, which helps differentiate it from sibling tools like 'list_orders' (for multiple orders) or 'search_orders' (for broader queries). However, it does not explicitly state when not to use it or name alternatives, leaving some ambiguity in edge cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool returns risk scores (0-100) and risk levels with detailed factors, which is good behavioral context. However, it doesn't mention potential side effects, performance characteristics, or authentication requirements that would be helpful for a prediction tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in a single sentence that front-loads the core purpose and then specifies the return values. Every element earns its place with no redundant information or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a prediction tool with no annotations and no output schema, the description does well by explaining what it predicts, what factors it analyzes, and what it returns. However, it could benefit from more detail about the prediction methodology or limitations given the complexity of churn risk analysis.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all three parameters thoroughly. The description doesn't add any additional meaning about the parameters beyond what's in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verb ('predict') and resource ('churn risk for active subscriptions'), and distinguishes it from siblings like 'analyze_churn_risk' by focusing on prediction rather than analysis. It specifies the scope ('active subscriptions') and what factors are analyzed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for predicting churn risk based on specific factors, but does not explicitly state when to use this tool versus alternatives like 'analyze_churn_risk' or other customer/subscription tools. It provides context about what it does but lacks explicit guidance on when it's most appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: conditional logic (check existence first), creation with specific source ('AI Agent'), and return value (Lead ID). However, it doesn't mention mutation implications, error handling, authentication needs, or rate limits for a write operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise at two sentences with zero waste. It's front-loaded with the core purpose, followed by behavioral details. Every word earns its place in explaining the tool's conditional logic and return value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description provides adequate but incomplete context. It explains the conditional write behavior and return value, but lacks details about error cases, side effects, or what happens when a Lead already exists (does it update or skip?).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all 5 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('sync', 'checks', 'creates') and resources ('customer', 'Salesforce CRM', 'Lead'). It distinguishes from sibling tools like 'create_customer' by specifying the CRM integration aspect and conditional logic (check existence before creation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (for syncing customers to Salesforce CRM) but doesn't explicitly state when NOT to use it or name alternatives. It doesn't mention prerequisites like CRM connectivity or compare with other customer-related tools like 'create_customer' or 'update_customer'.
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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