InventorySystem MCP Server

by AllanSJoseph

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Tools are mostly distinct by resource and action. The only potential confusion is between update_inventory_item and update_inventory_item_stock, but descriptions clarify the difference. Other similar tools like fetch_bill_records and open_bill target different aspects of a bill.
Naming Consistency3/5
Uses a mostly consistent fetch_/add_/update_ pattern, but deviates with create_draft_bill, open_bill, issue_bill, and discard_bill. The mix of add_ and create_ plus fetch_ and open_ creates minor inconsistency, though still readable.
Tool Count4/5
15 tools is on the upper end of reasonable for an inventory system with users, items, and bills. Each tool has a defined purpose, though a few could be consolidated (e.g., update_inventory_item_stock could be merged into update_inventory_item).
Completeness3/5
Bills have good lifecycle coverage (create, edit, delete items, discard, issue, fetch). However, users only have add and list, and inventory items have no delete operation. These are notable gaps for a management system, though not severe enough to break core workflows.
Average 3.8/5 across 15 of 15 tools scored. Lowest: 2.6/5.
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
- CI status not available
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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 must disclose behavioral characteristics. It only mentions the action and return value, but does not state side effects (e.g., inventory impact), preconditions (e.g., existing bill), or error causes. This is insufficient for a mutating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and not overly verbose, but the Args section is empty shells, providing no useful information. The Returns section is generic. It is not well-structured for quick comprehension; a more concise and informative format would be better.
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 simple schema (3 integers) and no annotations, the description is incomplete. It does not address usage context, error conditions, or the relationship to the bill lifecycle. An agent would likely struggle to determine when this tool is appropriate without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description merely lists argument names without explanations. It does not clarify expected units, constraints, or relationships (e.g., prod_id must exist, quantity must be positive), so it adds no value 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 'Adds an item to the bill with the provided invoice_no,' which is a specific action on a specific resource. While it doesn't explicitly contrast with sibling tools like edit_bill_item_quantity or delete_bill_item, the action 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 guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites such as the bill being open, nor does it state when to prefer this over edit_bill_item_quantity.
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 full responsibility for behavioral disclosures. It mentions the return format ('confirmation message or an error message in json format'), but omits details about side effects, permissions, or failure conditions like duplicate names or invalid input. The mutation is implied by 'adds', but no further context is given.
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 a clear structure: a one-sentence purpose, Args list, and Returns section. Each part serves a purpose, though the Args descriptions are redundant with the schema. Overall, it is well-organized and not overly verbose.
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 provides a basic understanding of what the tool does and its return format, but lacks critical context for a mutation tool with no annotations. It does not explain when to use add versus update, what validation occurs, or any prerequisites. The presence of a Returns section partially compensates for the missing output schema, but the overall completeness is average.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The Args section repeats parameter names with tautological descriptions ('name: The name of the inventory item'), offering no additional meaning beyond the schema. The phrase 'new_stock quantity' for stock is confusing and does not clarify units or constraints. Given 0% schema description coverage, the description fails to compensate with meaningful 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 clearly states 'Adds a new inventory item to the inventory management system' with a specific verb and resource. It distinguishes itself from siblings like add_user or update_inventory_item by clearly focusing on adding inventory items.
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. The description only states what it does, leaving the agent to infer usage without explicit exclusions or mentions of sibling tools like update_inventory_item or update_inventory_item_stock.
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 mentions that the operation updates an existing item and returns a confirmation or error message in JSON, which provides some transparency. However, it doesn't disclose whether all fields are required for a full replacement (though schema shows required), or any side effects, permissions, or idempotency. The typo 'new new_stock' slightly undermines clarity.
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 structured with 'Args:' and 'Returns:' sections, making it easy to parse. It is moderately concise, covering all parameters without excessive verbosity. The typo and redundant 'new' are minor flaws, but overall it's appropriately sized and well-organized.
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 5 parameters, no annotations, and no output schema, the description provides a baseline of what the tool does and its return type, but it lacks critical context about when to use this versus the sibling 'update_inventory_item_stock'. It also doesn't mention any prerequisites (e.g., item must exist) or what exactly the confirmation message contains. This is a clear gap for a tool with such a close sibling.
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 has 0% description coverage, so the description must compensate. It lists each parameter with a semantic explanation: prod_id as the ID to update, name/price/stock/description as the new values. This adds meaning beyond the bare schema titles. However, the redundant phrase 'new new_stock' is a minor error, and some descriptions are simplistic (e.g., 'The new name') but adequate.
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 states 'Updates an existing inventory item' which clearly identifies the action (update) and resource (inventory item). However, it doesn't distinguish from the sibling tool 'update_inventory_item_stock', which likely serves a more specific purpose. The verb+resource is clear but lacks 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?
No guidance is provided on when to use this tool versus alternatives like 'update_inventory_item_stock'. The description implies general use but doesn't state prerequisites or exclusions. It doesn't mention scenarios where a more targeted update (e.g., stock-only) might be preferred.
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 a confirmation/error return, but does not disclose that discarding is permanent, whether permissions are needed, or what happens to associated bill items. This is a significant gap for a destructive operation.
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 a clear structure, including purpose, Args, and Returns. Every sentence adds value, though the Args section is redundant with the schema.
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 covers the main purpose, parameter, and return value. However, for a destructive tool with no annotations, it omits important context about permanence and side effects, making it only partially 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 coverage is 0%, but the description explains 'invoice_no: Invoice Number of the bill', adding meaning beyond the schema's title. It lacks detail on how to obtain the invoice number, but provides the core semantic.
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 states 'Discards a draft Bill' with a specific verb and resource, clearly distinguishing it from sibling tools like issue_bill or open_bill. The inclusion of 'draft' clarifies the target 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 explicitly targets 'draft Bill', providing clear scope of use (only for drafts). However, it does not mention alternatives or when-not-to-use, but the scope limitation is evident from the verb and resource.
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 burden. It discloses the mutation behavior and return format ('confirmation message or an error message in json format'), and implies the item must exist. However, it does not mention permissions, reversibility, or whether stock is absolute versus incremental beyond the word 'new'.
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 compact and well-structured with Args and Returns sections. There is slight redundancy ('new_stock' and 'new new_stock'), but overall every sentence earns its place without unnecessary verbosity.
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 simple two-parameter mutation tool, the description covers purpose, parameters, and return format. However, it lacks any comparison with sibling tools and does not state prerequisites like 'item must exist' explicitly. Given the simplicity, this is adequate but not complete.
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?
Schema coverage is 0%, but the description fully explains both parameters: prod_id as the item ID and stock as the new quantity. This adds meaning beyond the raw schema, which only gives types. The semantics are clear enough to invoke correctly.
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 a specific action ('Updates the new_stock quantity') on a specific resource ('existing inventory item'), distinguishing it from the sibling tool update_inventory_item which likely updates other fields. The scope 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 guidance is provided on when to use this tool versus alternatives such as update_inventory_item or add_inventory_item. The description only states what it does without any context or exclusions.
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 discloses that the tool deletes an item, restricts to unpaid/unissued bills, and returns a confirmation or error message. However, it does not state whether the deletion is permanent, any permission requirements, or how the system handles edge cases like invalid invoice numbers or product IDs.
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 compact and front-loaded with the main purpose. It uses a clean Args/Returns structure, with no wasted words. Every sentence adds value, including the restriction on unpaid/unissued bills and the return behavior.
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 simple parameter set (two integers) and lack of output schema, the description provides sufficient context: the operation, the bill status restriction, and the return format. It does not explain edge cases or failure reasons in detail, but for this simplicity level, it is mostly 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 0%, so the description must compensate. It adds the constraint that prod_id must be a positive value, which is valuable. However, invoice_no is described only as 'Invoice Number of the bill,' which matches the schema's title but adds no new meaning. The parameter semantics are minimal but slightly enhanced by the positive-value constraint.
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: "Deletes an existing item from an unpaid/unissued bill." It uses a specific verb and resource, and distinguishes from sibling tools like discard_bill (which deletes the entire bill) and add_item_to_bill (which adds items).
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 use case by stating it works on unpaid/unissued bills, but it does not explicitly mention when to use this tool versus alternatives like edit_bill_item_quantity or discard_bill. No exclusions or alternative references are provided.
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 discloses the return format (json list) and error behavior, but does not explicitly state that the operation is read-only or mention pagination or performance implications. 'Fetches' implies a safe read, but this is not confirmed.
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: the first sentence states the core action and resource, while the second sentence covers the return value. No redundant phrases 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?
For a no-parameter, no-output-schema tool, the description covers essential behavior: fetching all items, returning JSON, and error handling. Missing details like authentication or rate limits are not critical for this simple fetch action, so the description is sufficiently complete.
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, so schema description coverage is complete. The description reinforces the lack of filtering by specifying 'all inventory items', which aligns with the baseline that no-parameter tools need minimal parameter guidance.
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 'Fetches the list of all inventory items' with a specific verb (fetches), resource (inventory items), and scope (all). This distinguishes it from sibling fetch tools like fetch_users and fetch_bill_records, which target 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 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. Though the name implies inventory items, the description does not mention exclusions or alternative tools for fetching users or bills, leaving usage decisions to the agent.
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 the return type ("a confirmation message or an error message in json format") but does not mention permissions, side effects, validation constraints, or failure scenarios. This is a minimal level of behavioral disclosure 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 well-structured with purpose, Args, and Returns sections. It is slightly verbose as it repeats the parameter names already present in the schema, but given the lack of schema descriptions, this duplication is acceptable and not wasteful.
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 moderate complexity (6 required params, no output schema), the description covers all parameters and the return format. It lacks edge-case information such as duplicate username handling or permission requirements, but it is largely sufficient for an agent to invoke the tool correctly.
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?
Schema description coverage is 0%, so the description must compensate. It lists all six parameters with meaningful explanations, including examples for the 'type' field (e.g., Admin, Stocker, Cashier). However, it lacks constraint details such as format, length, or uniqueness requirements, though it suffices for basic invocation.
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: "Adds a new user to the inventory management system." This uses a specific verb and resource, and the tool is distinct from siblings like fetch_users, making its 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use case (creating users) but does not provide explicit guidance on when to use it versus alternatives or any prerequisites. It also does not mention exclusions or when not to use the tool.
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 mentions the JSON return format and the event of an error message, which is useful. But it lacks detail on read-only guarantees, authentication, or handling of invalid cashier_id. It does not contradict any annotations since none exist.
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 highly concise, with a one-sentence summary followed by clear Args and Returns sections. It is front-loaded with the primary action and contains no fluff, earning every sentence.
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 (1 required parameter, no output schema, no annotations), the description is mostly complete. It explains what is returned and the error case. It could provide more detail about the structure of bill records, but this is not critical for a filtered fetch 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?
Schema coverage is 0%, so the description must compensate. It adds meaning to 'cashier_id' by describing it as the 'Unique id of the cashier,' which clarifies its role beyond the schema's simple 'Cashier Id' title. While brief, it adequately explains the parameter for such a simple tool.
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 fetches bill records, with a specific verb (Fetches), resource (bill records), and scope (by cashier). It distinguishes itself from the sibling 'fetch_bill_records' by specifying the cashier filter, making its 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a cashier_id is provided, and the name signals a filtered version of fetch_bill_records. However, it does not explicitly mention alternatives or scenarios when not to use this tool, so guidance is only implicit.
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 burden. It states 'Reads' (indicating a non-destructive operation) and mentions the return format as a JSON list of products. However, it doesn't disclose error handling, authorization needs, or behavior for nonexistent invoice numbers.
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 brief and well-structured with a purpose statement, Args, and Returns. Every sentence provides useful information without redundancy, making it easy to scan.
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 read tool, the description covers the purpose, parameter, and return value. It lacks explicit handling of edge cases like missing invoices or empty results, but the tool's simplicity makes it reasonably complete.
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 has no description for invoice_no, but the description compensates by explaining it as 'The Invoice No of the bill.' This adds meaning beyond the schema's bare parameter definition.
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 states 'Reads the products inside a bill with the provided invoice_no,' which specifies a clear verb, resource, and scope. It distinguishes itself from siblings like fetch_bill_records (which fetches bill records) and add_item_to_bill (which modifies bills).
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 one needs to read products from a bill, but it does not explicitly mention when to prefer this over alternatives or when not to use it. There are no exclusions or alternative tool references.
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 disclose behavior. It states the update action, the unpaid/unissued condition, and the return format (confirmation or JSON error). However, it does not mention edge cases like non-existent items or whether the quantity is overwritten, leaving some behavioral ambiguity.
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 well-structured with a clear opening sentence, a labeled Args section, and a Returns section. It is somewhat longer than necessary but every sentence earns its place by providing required parameter details. It remains focused and readable.
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 update tool with no output schema, the description provides the action, parameter constraints, and return format. It does not explicitly list error scenarios, but the 'unpaid/unissued' condition covers a key prerequisite. The description is sufficiently complete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only parameter names and types (all integers), but the description adds human-readable meaning for each parameter: 'invoice_no: Invoice Number', 'prod_id: a unique identifier', and 'quantity: quantity', along with validation rules like 'must be a positive value' and 'cannot be zero'. This fully compensates for the 0% schema description 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 opens with 'Updates the quantity of an existing unpaid/unissued bill item', which is a specific verb+resource+scope. This clearly distinguishes it from sibling tools like add_item_to_bill and delete_bill_item, which perform different operations on bill items.
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 specifies the tool applies to 'existing unpaid/unissued bill items', providing a clear context for when to use it. It does not explicitly name alternatives or exclusions, but the condition is sufficient for an agent to infer when this tool is appropriate.
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, the description carries the full behavioral burden. It explains the creation action and return behavior (confirmation or error message in JSON). It does not mention permissions or side effects, but for a simple creation tool this is adequate.
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 well-organized, front-loading the main action, then detailing arguments, example, and return format. Every section earns its place, and the example is directly useful for LLM invocation.
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 one parameter and no output schema, the description covers the essential context: purpose, parameter structure, example, and return format. It could mention edge cases like empty product lists or invalid product IDs, but that is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description fully compensates by specifying the exact structure of the 'products' parameter: each element is a dict with 'prod_id' and 'quantity' fields, including constraints. The example usage further clarifies the format.
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: 'Creates a draft bill and adds the provided products to it.' This uses a specific verb and resource, distinguishing it from sibling tools like open_bill or issue_bill.
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 through the example (creating a bill with products) but does not explicitly contrast with alternative flows like open_bill + add_item_to_bill. No exclusions are mentioned, so it gets a mid-range score.
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 full burden. It goes beyond a basic fetch description by explaining the structure of each record (invoice_no, Date, total_price, paymethod) and the special meaning of NULL values indicating that a bill was not issued. It also notes the error return case, which is useful 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 appropriately sized: two short paragraphs covering purpose, data content, edge-case semantics, and return behavior. It is front-loaded with the main action and contains no fluff, though there is a minor typo ('it' instead of 'its').
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?
Given the tool's simplicity (no parameters), lack of annotations, and lack of an output schema, the description adequately explains what is returned, the meaning of key fields, and the error condition. It is sufficient for an agent to confidently invoke the tool without needing additional 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 tool has zero parameters and the schema is empty, so the baseline applies as described. The description does not need to add parameter details, and it does not introduce any confusion about arguments.
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 ('Fetches') and clearly identifies the resource ('all bill records') and the system ('inventory management system server'). The word 'all' distinguishes it from the sibling tool fetch_bill_records_by_cashier, making the scope explicit.
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 conveys the tool's role as fetching the complete list of bill records, but does not explicitly state when to use it over alternatives such as fetch_bill_records_by_cashier. There is no mention of exclusions or when-not-to-use, leaving this aspect implied rather than explicit.
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 behavioral disclosure. It explicitly states this is a read operation ('Gets'), specifies the return format (JSON list), and mentions error handling ('error message if the request fails'). While it does not discuss authentication or pagination, for a simple parameterless list, this is reasonable 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 concise, with a clear first sentence stating the purpose, a brief note on user types, and a structured 'Returns' section. Every sentence adds value, and the format is easily scannable for an agent.
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 tool with no parameters and no output schema, the description is complete enough. It states what the tool does, what it returns, and even provides context about the three user types. There are no missing critical details for an agent to invoke it correctly.
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 covers all of them (none). According to the rubric, a tool with 0 parameters gets a baseline score of 4. The description adds no parameter details, but none are 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 'Gets the list of all users' from the server, specifying the resource (users) and the action (get). It also mentions the JSON format, and the reference to 'all users' differentiates it from other tools like fetch_inventory_items or fetch_bill_records.
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: if you need the list of all users, use this tool. However, it does not explicitly mention when not to use it, alternatives, or prerequisites. It relies on the tool name and the sibling context for differentiation, but lacks explicit guidance.
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 behavioral disclosure. It explicitly warns that 'the bill cannot be edited or deleted' after calling, which is critical for an irreversible action. It also notes the financial consequence ('considered paid') and describes the return message format, adding valuable context beyond a simple 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 concise and well-structured: a single sentence states the purpose and consequence, followed by clearly formatted Args and Returns sections. Every sentence earns its place 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 tool with only two simple parameters and no output schema, the description is fairly complete. It covers the tool's behavior, the irreversibility, parameter meanings, and return value. It could be more explicit about prerequisites (e.g., bill must be in draft status), but overall it provides enough context for an agent to use it correctly.
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 no descriptions (0% coverage), so the description compensates with an Args section. It explains invoice_no as 'Invoice Number of the bill' and pay_method as 'Payment Method in uppercase letters' with examples (Cash, Card, UPI). This adds meaningful guidance, though it could be more exhaustive about valid values.
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 action: 'Issues a draft bill i.e. The bill is finalised and considered paid.' This provides a specific verb and resource, and distinguishes it from siblings like create_draft_bill and discard_bill by clarifying the finalizing and 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 description clearly implies when to use the tool: when you have a draft bill that needs to be finalized and marked as paid. It does not explicitly name alternatives or exclusions, but the context is clear given the sibling tools and the description's own wording.
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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