InventPay MCP Server

Server Quality Checklist

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Latest release: v1.1.0
Disambiguation4/5
Most tools target distinct resources and actions. Slight overlap exists between get_store and get_store_analytics (both show order/product counts) and between create_payment and create_invoice, but descriptions clarify their different use cases.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with snake_case: get, create, update, delete, list, add. Resources are singular for single-item operations and plural for list operations, with only minor naming variance like get_key_pool_stats.
Tool Count4/5
With 20 tools, the count is higher than the ideal 3-15 range but appropriate for the broad merchant platform scope covering stores, products, keys, payments, withdrawals, orders, and analytics. Each tool has a distinct purpose, so it does not feel bloated.
Completeness4/5
The tool surface covers core lifecycle operations for stores, products, keys, payments, withdrawals, and orders. Minor gaps exist (e.g., no store deletion, no key revocation, no payment cancellation), but these are typically not required for merchant operations and can be worked around.
Average 3.9/5 across 20 of 20 tools scored. Lowest: 3.1/5.
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
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This repository is licensed under MIT License.
This repository includes a README.md file.
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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?
No annotations are provided, so the description carries full burden. It discloses that the tool returns a wallet address, QR code, and invoice URL, but does not mention side effects (e.g., creating a persistent payment record), potential fees, rate limits, or that the payment expires if not completed. The creation action is implicit but not elaborated with safety or 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, front-loaded sentence that immediately states the action and key returns. Every word earns its place, with no filler or repetition of schema details. This is exemplary conciseness.
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?
The tool has 7 parameters and no output schema, but the description explains the return values. The schema covers parameter details, so the description only needs to tie them together. However, it does not mention any prerequisites like requiring a store, or the meaning of the callback URL and expiration, leaving some context gaps. Adequate but not rich.
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% (all parameters have descriptions), so the baseline is 3. The tool description does not add parameter semantics beyond saying the payment is crypto and returns payment details; it does not compensate for or augment the schema. This meets the baseline but doesn't exceed 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 and resource: 'Create a crypto payment.' It adds specific return information (wallet address, QR code, invoice URL) that helps differentiate from sibling tools like create_invoice or create_withdrawal. However, it does not explicitly name alternatives, so it slightly misses the top 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?
There is no guidance on when to use this tool vs alternatives, such as create_invoice for non-crypto invoices or create_withdrawal for payouts. The description implies use for accepting crypto payments but does not state exclusions or prerequisites, leaving the agent to infer context 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 the full burden of behavioral disclosure. It indicates the operation is a creation (mutating), but fails to disclose important traits such as authentication requirements, behavior if the merchant already has a store, error conditions, or what the tool returns. The mention of a 'unique URL slug' provides some context, but overall transparency is minimal 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 front-loaded with the core action: 'Create a new merchant storefront.' The second sentence adds a valuable constraint (one store per merchant, unique slug), while the third sentence describes the storefront's purpose, which is somewhat tangential to the tool operation. Still, it remains concise and readable.
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 (5 parameters, nested settings object) and lack of output schema, the description provides a clear high-level context. It explains the purpose and a key constraint, but omits crucial behavioral details such as return values, failure modes, or when not to use it. The schema covers parameters, so completeness is moderate but not fully sufficient.
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 description does not need to explain parameters in detail. The only added context is the 'unique URL slug' phrase, which already appears in the schema's description of the 'name' property. The description adds no meaningful parameter semantics beyond what the schema already provides.
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 a specific verb and resource: 'Create a new merchant storefront.' It distinguishes from siblings like get_store and update_store by emphasizing the creation aspect and the unique constraint that each merchant gets exactly one store. This makes the tool's scope unambiguous.
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 implicitly suggests when to use this tool: when a merchant needs a new storefront. The 'each merchant gets one store' constraint implies that update_store should be used for modifications, but no explicit alternatives or exclusions are mentioned. This is implied usage rather than clear guidance.
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, the description carries the burden. It discloses the return value ('Returns an invoice URL') and a key behavior (customer selects cryptocurrency), but omits authorization, side effects, or persistence details. This provides some transparency but not full 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 two sentences, front-loaded with the action, and contains no unnecessary words. It efficiently communicates the core purpose.
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 6 parameters and no output schema, the description states the return URL and core behavior but does not elaborate on the invoicing workflow, prerequisites, or how parameters interact. It is adequate but leaves room for more 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?
Schema description coverage is 100%, so the description does not need to explain parameters. It adds minimal context about multi-currency support but relies on the schema for parameter details, matching the baseline for high coverage.
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 action ('Create a multi-currency invoice') and the resource, and adds a distinguishing feature: 'The customer can choose which cryptocurrency to pay with.' This separates it from sibling tools like create_payment.
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 when to use this tool (when you need an invoice with customer cryptocurrency choice) but does not explicitly mention alternatives or when not to use it. It lacks exclusions or comparisons to sibling tools.
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?
Since no annotations are provided, the description carries the full burden. It discloses the response categories (available, pending, total earned, total withdrawn) and indicates it is a read operation by using 'Get' and 'Shows.' However, it does not explicitly state that it has no side effects, requires no authentication, or how balances are aggregated, though these may be inferred from the 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 two concise sentences, front-loaded with the primary action ('Get all cryptocurrency balances'), followed by a brief list of the data shown. No redundant or filler content.
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?
Given the tool's simplicity—no parameters, no output schema, no annotations—the description sufficiently explains what the tool does and what data it returns. However, it omits details such as potential errors, currency format, or whether the list is comprehensive, which would be helpful for full completeness. It is adequate but not exhaustive.
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 tool has zero parameters, and the schema is trivially fully covered. The description adds no parameter explanation, but with 0 parameters, there is nothing to explain. Per the baseline rule for 0 params, a score of 4 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 uses the verb 'Get' and specifies the resource 'all cryptocurrency balances for your merchant account', clearly distinguishing it from sibling tools like get_store or get_withdrawal by its focus on balances. No other sibling tool targets balances, so the purpose is unambiguous.
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 usage context is provided. The description does not state when to choose this tool over alternatives like get_withdrawal or get_payment_status, nor does it mention any prerequisites or exclusions. It only explains the tool's basic function.
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, the description carries the burden of behavioral disclosure. It lists the return fields, which is useful, but it does not explicitly state that this is a read-only operation, nor does it mention permissions or rate limits. The verb 'check' implies non-destructiveness, so the gap is moderate.
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, front-loaded sentence that immediately states the purpose and enumerates the return information. Every word is informative, with no redundant or vague phrasing.
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 simple status-checking tool with one parameter and no output schema, the description is largely complete. It names all return fields, compensating for the missing output schema, and the provided information is sufficient for an agent to call the tool correctly. It could mention error handling, but that is often beyond scope for such a tool.
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 already provides a clear description for the single parameter (paymentId) with 100% coverage, so the baseline is 3. The description adds no extra meaning or examples beyond what the schema states, just confirming that it handles payments or invoices.
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 checks the current status of a payment or invoice, with a specific verb ('Check') and resource. It also lists the return fields (status, amount, confirmations, transaction details), which distinguishes it from sibling tools like get_withdrawal or get_order.
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 the tool is used when you need payment/invoice status, but it does not explicitly mention when to use it versus alternatives like get_withdrawal or get_order. No exclusions or alternative-recommendations are provided, but the domain (payments/invoices) is clear.
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?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns status, amount, transaction hash, and processing details, which implies a non-destructive read. However, it does not mention error behavior, required permissions, or whether the status values are standardized, leaving some behavioral aspects undisclosed.
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, front-loaded sentence that states the purpose and the key return fields. It contains no filler or redundant content, making it highly concise and easy to parse.
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 simple single-parameter status check, the description is largely complete: it names the key return fields (status, amount, transaction hash, processing details) and implies a read-only operation. However, because there is no output schema and no mention of error cases or missing data handling, it leaves a minor gap in what the agent should expect in unusual 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%, so the baseline is 3. The description does not add any information about the withdrawalId parameter beyond its name and type, which is already documented in the schema. No additional format or usage details are provided.
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 uses the specific verb 'check' with the resource 'withdrawal request', clearly indicating a read operation. It distinguishes itself from siblings like create_withdrawal (opposite) and get_payment_status (different resource type) by focusing on withdrawals.
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 clearly implies when to use this tool (to check withdrawal status) but does not explicitly provide alternatives or exclusions. It does not mention get_payment_status as a distinct tool for payment statuses, leaving potential ambiguity for agents choosing between sibling tools.
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 must carry the behavioral disclosure burden. It adds meaningful detail about FIFO allocation ('Each customer gets one unique key on purchase (FIFO)'), which is not captured in the schema. However, it omits other behavioral traits such as duplicate handling, error behavior, permissions, or idempotency, leaving gaps 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 two sentences, with the primary action front-loaded: 'Upload unique keys/codes to a product's key pool.' It then adds one behavioral note (FIFO) and example use cases. There is no fluff or repetition, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description should explain outcomes or response behavior. While it gives the core functionality and FIFO logic, it does not mention what happens after a successful upload (e.g., response body, number of keys added) or how errors are surfaced. This leaves the context incomplete for an agent invoking the tool.
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 all three parameters (productId, keys, label) are already described in the schema. The main description reinforces the purpose ('key pool') but does not add per-parameter semantics beyond what the schema provides. Thus, the baseline 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 tool's function: 'Upload unique keys/codes to a product's key pool.' This uses a specific verb and resource, and the FIFO note further clarifies its role. It is distinct from sibling tools like list_product_keys (which is read-only) and get_key_pool_stats (which reports statistics), so purpose clarity is high.
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 provides contextual use cases ('use this for license keys, activation codes, gift cards, etc.'), which helps the agent decide when to invoke it. However, it does not explicitly state when not to use it or name alternative tools for similar operations, so it falls short of a 5.
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 adds valuable behavioral context: products are priced in USDT and auto-converted at checkout, and digitalContent triggers automatic delivery. However, it does not disclose side effects, requirements (e.g., conditional fields), or return behavior, leaving 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 two sentences, front-loads the primary purpose, and contains no fluff. It is concise and every sentence adds useful information about what the tool does.
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?
The description gives a solid overview but does not cover important nuances like content types (GENERAL vs SKILL) or conditional requirements. With 10 params and nested objects, more guidance would be helpful, but the schema covers parameter details, and no output schema means return values are not explained.
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 coverage is 100%, so the baseline is 3. The description mentions digitalContent for automatic delivery, but the schema already states 'Digital delivery content — auto-delivered after payment'. It adds no new parameter meaning beyond what the schema provides.
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 action ('Add a digital product') and the resource ('to your store'). It distinguishes create_product from siblings like update_product and delete_product by specifying 'Add'. It also clarifies the product type as digital.
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 provides clear context: use this to add a digital product to a store. It mentions pricing and delivery behavior, giving a sense of when this tool is appropriate. However, it does not explicitly exclude alternatives or mention when to use update_product, so it misses the 'when-not' element.
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, the description carries the full burden. It implies a read-only operation via the verb 'get' but does not explicitly state there are no side effects or mention any permissions or rate limits. It adds some value by listing the returned fields, but this is more output semantics than behavioral disclosure.
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 sentence that immediately states the verb (get), the resource (store details), and key output fields. It is entirely front-loaded with no filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter with no output schema, the description sufficiently communicates what will be returned. The list of fields gives the agent a clear expectation, and no additional context about side effects or prerequisites seems necessary for this straightforward operation.
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?
There are zero parameters, and the schema is trivially 100% covered. The description adds nothing about parameters, but the baseline for zero-parameter tools is 4 because no parameter explanation is needed.
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 retrieves store details and enumerates specific fields (name, slug, URL, product count, order count). This distinguishes it from sibling tools like get_order or get_store_analytics.
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_store_analytics or update_store. No exclusions or conditional use cases are mentioned, leaving the agent to infer usage solely from the tool name.
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?
No annotations are provided, so the description carries the full burden. It discloses the core behaviors: listing, filtering by status, and pagination. However, it does not mention specific edge cases, return format, or default behavior, leaving some transparency 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 sentence that front-loads the verb and resource, with no filler or redundant information. It is appropriately sized for the tool's simplicity.
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 has no output schema and no annotations, the description could be more complete by stating what key information is returned or the default pagination behavior. However, for a straightforward list operation, it covers the essential scope adequately.
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?
All parameters are described in the schema (100% coverage), and the description's mention of 'status filter' and 'pagination' maps directly to existing properties without adding new semantics. Thus, it provides no value beyond the schema.
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 uses the specific verb 'List' and identifies the resource as 'keys in a product's key pool', clearly distinguishing it from siblings like list_products and add_product_keys. It also mentions status filter and pagination, making the scope 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 clearly implies when to use the tool: to enumerate keys in a product's key pool with optional filtering. It does not explicitly mention alternatives or exclusions, but the context is clear enough given sibling names like list_products and get_key_pool_stats.
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 does reveal the key partial-update behavior ('Only provided fields are changed'), which is valuable. But it does not mention required permissions, error conditions, response format, or what happens when no fields are provided. Some critical behaviors remain undisclosed.
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 sentence, immediately states the purpose, and contains zero filler. It is front-loaded and every word earns its place. Perfectly concise for a tool of this scope.
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 has 6 optional parameters and a nested object, the description is minimal. It covers the core behavior but omits return value, error handling, and authentication context (no output schema or annotations). While the schema fills in parameter details, the overall context is not fully complete for an agent to invoke the tool without additional assumptions.
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 already describes all six parameters (100% coverage), so the baseline is 3. The description adds semantic value by clarifying that only provided fields are updated, implying that parameters are optional and that unprovided fields remain unchanged. This goes beyond what the schema states, enhancing understanding.
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 function: 'Update your store details.' This is a specific verb+resource combination, and the sibling context (create_store, get_store, update_product) makes it obvious this updates store-level fields, distinguishing it from 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for modifying store details, and the 'Only provided fields are changed' note gives partial-update semantics. However, it does not explicitly mention when to prefer this over create_store or get_store, nor does it state exclusions or alternatives. Usage context is inferred rather than explicit.
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?
The description discloses the important behavior that products with existing orders are soft-deleted, adding context beyond the tool name. However, it does not clarify what happens to products without existing orders, leaving ambiguity about potential permanent deletion.
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?
Two short sentences with the main action front-loaded and the necessary caveat in the second sentence. Every word is purposeful with no redundancy.
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 simple one-parameter tool, the description covers the core outcome and a key behavioral nuance. The ambiguity about no-order products and lack of return/error details are minor gaps given the tool's 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?
The input schema already fully describes the single 'id' parameter as 'Product ID to deactivate' (100% coverage), so the description adds no additional parameter information. Baseline 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 uses the specific verb 'Deactivate' and names the resource 'product from your store', with the added nuance of soft-delete behavior. This clearly distinguishes it from sibling tools like update_product and create_product.
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 for deactivating a product, which is a clear context. However, it does not explicitly mention alternatives or when not to use it, relying on the tool name and sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. The verb 'Get' clearly indicates a read-only operation, and the listed counts give a good sense of the response content. However, it does not mention potential error conditions, authentication requirements, or any side effects, though for a simple getter these are less critical.
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, well-structured sentence that efficiently conveys the tool's purpose and key output. It contains no redundant words and is immediately informative, earning the highest score for conciseness.
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?
Given the tool's simplicity (one parameter, no output schema), the description adequately explains what the tool returns (counts for available, assigned, revoked, total). It does not explicitly state the response format, but the listed counts provide a clear expectation of the output. It is sufficiently complete for a simple getter tool.
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 only parameter productId described as 'Product ID'. The tool description does not add additional meaning beyond what the schema already provides, so 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 tool's function with a specific verb ('Get'), a resource ('key pool statistics'), and the exact data returned (available, assigned, revoked, and total counts). It distinguishes itself from sibling tools like list_product_keys or add_product_keys by focusing on aggregate statistics rather than individual key management.
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 when key pool statistics are needed, but does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. The intended use case is clear from the description, but there is no explicit guidance on scenarios where this tool should not be used.
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, the description must carry the full behavioral burden. The verb 'Get' implies a safe read operation and it lists response content, but it does not disclose error behavior (e.g., missing ID), authorization requirements, or rate-limit implications.
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, front-loaded sentence that states the action and resource immediately, then lists valuable detail without redundancy. Every word earns its place.
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 low-complexity tool with one parameter and no output schema, the description adequately covers the return scope by listing the included fields. It omits error-handling context, but the simplicity of the operation and full schema coverage keep this from being a significant gap.
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 already provides 100% coverage of the single parameter (id) with a basic but sufficient description ('Order ID'). The tool description only reinforces that the ID refers to a specific order, adding no new semantic value beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' with a clearly identified resource 'specific order' and enumerates the returned data (items, payment status, customer info, timestamps). This distinguishes it from sibling tools like list_orders and get_payment_status.
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 phrase 'full details of a specific order' makes it clear this is for retrieving a single order's complete record, contrasting with list-oriented or status-only tools. However, it does not explicitly name alternatives or state when not to use it, so it stops short of full exclusion guidance.
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, the description carries the burden for behavioral disclosure. It mentions optional status filter and pagination, but does not state that this is a read-only operation, what the response structure will be, or any default ordering. The straightforward nature of a list operation mitigates this gap, but more context would be useful.
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, concise sentence that leads with the primary action and scope, then the qualifying options. Every part earns its place, with no wasted words.
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 simple list tool with three well-documented optional parameters and no output schema, the description is mostly adequate. It clearly states the scope ('all orders for your store') and optional filters, but it does not mention the return format or any pagination details beyond the parameter names, leaving a slight gap in 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% coverage with descriptions for page, limit, and status. The description adds little beyond the schema, only tersely summarizing 'optional status filter and pagination' which the schema already documents in detail.
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 uses the specific verb 'List' with the resource 'orders', and adds scope ('for your store') plus optional status filter and pagination. This clearly distinguishes it from the sibling tool get_order, which fetches a single order.
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: to retrieve all orders rather than a specific one, as contrasted with get_order. However, it does not explicitly mention exclusions or alternatives, so there is no direct 'use get_order instead' guidance.
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?
No annotations are provided, so the description is the sole source of behavioral info. It mentions the optional search and pagination capabilities, which is useful, but it does not disclose other traits like sorting order, default behavior, authentication requirements, or response format. For a simple read-only list operation, this is adequate but not rich.
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 sentence that states the core purpose and key options with no redundancy or filler. It is concise and front-loaded with the verb and resource.
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 straightforward listing tool with three optional parameters and no output schema, the description is complete enough. It covers the scope ('your store') and the optional features. It does not detail return values, but that is reasonably implicit for a list action.
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 for all three parameters (page, limit, search), including defaults and bounds. The description adds minimal extra meaning beyond that, 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and clearly identifies the resource ('products in your store'). It also mentions optional search and pagination, which distinguishes it from other product-related tools like create_product, update_product, or delete_product.
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 provides clear context that this tool is for listing products and implies its use when you need to view or search products. However, it does not explicitly mention alternatives or when not to use it, though the purpose is unambiguous in context with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It does so effectively by noting 'Only provided fields are changed' (partial update) and 'Updating the name regenerates the slug' (side effect). These are useful, non-obvious behaviors. While it doesn't disclose auth requirements or return values, the given information goes beyond a generic 'update product' statement.
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 concise and front-loaded, stating the action and resource in the first sentence. The remaining two sentences add valuable details (partial update and slug regeneration) without any fluff. Every sentence earns its place.
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 (12 parameters, nested objects), the description covers the core action and key behavioral nuance, and the schema provides exhaustive parameter details. However, there is no output schema and the description doesn't mention what the tool returns or potential error conditions, leaving some ambiguity for the agent. It is minimally adequate but not 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 documents every parameter. The description adds extra meaning only for the 'name' parameter by mentioning slug regeneration, which is not in the schema. This is a marginal addition over the schema's rich descriptions, so 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 tool's purpose: 'Update a product in your store.' It uses a specific verb ('Update') and resource ('product'), and distinguishes itself from sibling tools like create_product and delete_product by focusing on updating existing products. The phrase 'Only provided fields are changed' further clarifies the partial-update scope.
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 provides clear context for use: you update a product when you have an existing product ID and want to modify specific fields. The statement 'Only provided fields are changed' gives practical guidance on how to call it. However, it does not explicitly mention alternatives like create_product or delete_product, nor does it state when not to use it, but the sibling tool names make the distinction obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavioral traits. It explicitly states the action (send funds) and the required configuration key, which warns the agent about a potential failure point. It does not mention response format or reversibility, but the core mutating behavior is clear.
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 purpose and immediately followed by the key prerequisite. Every word is useful, no repetition or filler.
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?
The tool is relatively simple (4 parameters, no output schema). The description covers the main purpose and the critical prerequisite. It lacks information about return value or side effects, but the schema and action clarity compensate. Without annotations, a brief configuration note adds 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?
The input schema provides 100% coverage with descriptions for all parameters (amount, currency, destinationAddress, description). The description adds minimal extra meaning beyond the schema, such as 'external' wallet address. Baseline 3 is appropriate as the schema already documents parameters thoroughly.
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 begins with a specific verb + resource: 'Create a withdrawal request' and clarifies the destination as 'an external wallet address.' This clearly distinguishes it from sibling tools like get_withdrawal (which reads) and the payment/invoice creation tools.
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 clearly states the use case (sending funds to an external wallet) and mentions a prerequisite (INVENTPAY_WITHDRAWAL_KEY) that must be configured. It does not explicitly name alternatives or exclusions, but the context is sufficient for selecting this tool over siblings.
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?
The description discloses the output contents (metrics returned) but does not clarify the data scope (e.g., which store, time range) or any limitations like data freshness or permissions. With no annotations provided, the description carries the full burden, but it is a read-oriented tool and the core behavior is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action and resource, and every listed item adds value. No filler or redundant words.
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?
Given no output schema, the description lists the key return components (orders, revenue, products, recent activity). It is largely complete for a no-parameter analytics tool, though it leaves minor ambiguity about how the store context is determined.
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 zero parameters, so the schema coverage is trivially 100%. Baseline is 4 because there are no parameters to document; the description does not need to add parameter semantics.
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 uses the specific verb 'Get' with the resource 'store analytics', and enumerates the exact metrics returned (total orders, revenue breakdown by status, product count, recent order activity). This clearly distinguishes it from sibling tools like get_store or list_orders.
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 clear usage when aggregated store analytics are needed, and the specific metric list signals this tool is for summaries rather than raw data. No explicit alternatives are named, but the purpose is distinct enough that the intended context is evident.
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 must carry full disclosure. It does reveal meaningful behaviors: valid transitions and digital orders auto-transitioning to COMPLETED. However, it omits CANCELLED from the transition list even though it appears in the enum, and it doesn't clarify error handling or side effects. This creates gaps for edge cases.
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 with no filler. The purpose is front-loaded, and the state machine rule is packed concisely. Every sentence contributes valuable information without redundancy.
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 mutation tool with no annotations and no output schema, the description does a good job explaining core domain rules (transitions and special case). However, it leaves out the CANCELLED state, return format, and error conditions, which are relevant for a status update tool. It's mostly complete but missing edge-case details.
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 schema already provides full descriptions for all parameters (100% coverage), so the baseline is 3. The description adds extra meaning by defining the state machine and how status values relate to each other, enriching the enum semantics. Notes remain only schematically described, but the overall parameter meaning is enhanced.
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 'Update the fulfillment status of an order' with a specific verb and resource. It also lists valid transitions, which distinguishes it from other order-related tools like get_order or list_orders. There is no ambiguity about what this tool does.
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 structure of valid transitions provides clear context for when the tool can be used, but it does not explicitly mention alternatives or exclusions. Since there is no other order update tool among siblings, usage is fairly obvious, but the absence of explicit when-not-to-use guidance prevents a higher score.
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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