mcp-costco

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no significant overlap. For example, 'add_to_cart' and 'update_cart' handle different cart operations, while 'check_warehouse_stock' and 'get_delivery_options' address separate availability concerns. The descriptions reinforce these distinctions, making tool selection straightforward for an agent.
Naming Consistency5/5
All tools follow a consistent verb_noun naming pattern, such as 'add_to_cart', 'get_product_details', and 'track_order'. This uniformity enhances readability and predictability across the set, with no deviations in style or convention.
Tool Count5/5
With 16 tools, the server is well-scoped for a Costco e-commerce domain, covering authentication, product search, cart management, order processing, and membership functions. Each tool serves a specific role, avoiding bloat while providing comprehensive coverage for typical shopping workflows.
Completeness5/5
The toolset offers complete coverage for the Costco shopping domain, including CRUD operations for cart items, order lifecycle from checkout to tracking, product discovery, and account management. No obvious gaps exist; agents can perform end-to-end tasks like searching, adding to cart, checking out, and tracking orders seamlessly.
Average 3.2/5 across 16 of 16 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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{
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  ]
}
```
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but only states the basic action. It doesn't mention whether this requires authentication, affects existing cart items, has rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain behavioral aspects like authentication needs, error handling, or what the tool returns, leaving significant gaps for an AI agent to operate effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents the three parameters (url, item_number, quantity). The description adds no additional parameter semantics beyond what's in the schema, but since the schema is comprehensive, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add') and resource ('Costco product to the cart'), making the tool's purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'update_cart' or 'view_cart', which would require more specific context about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'update_cart' or prerequisites such as needing to be logged in. It lacks context about typical scenarios or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'View' implies a read-only operation, but the description doesn't specify whether authentication is required, what data is returned (e.g., order details, dates, statuses), or any limitations like rate limits or access constraints. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient phrase ('View Costco order history') that is front-loaded and wastes no words. It directly conveys the core purpose without unnecessary elaboration, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns order data. It doesn't explain what 'order history' includes (e.g., list of orders, details per order), potential authentication needs, or how results are formatted. For a read operation with no structured output documentation, this leaves too many unknowns for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'limit' clearly documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting without extra value from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'View Costco order history' clearly states the verb ('view') and resource ('Costco order history'), making the purpose immediately understandable. However, it doesn't distinguish this tool from potential siblings like 'track_order' or 'status' that might also relate to orders, so it misses full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'track_order' and 'status' that might overlap with order-related functionality, there's no indication of when this tool is appropriate or what distinguishes it from other tools in the server.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions retrieving 'detailed product information' but does not specify critical traits like whether it requires authentication, has rate limits, returns real-time data, or handles errors. For a read operation with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly communicates the tool's function and key data points, making it easy to parse and understand quickly, with no wasted verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that fetches product details. It does not explain the return format, error handling, or dependencies (e.g., authentication needs), which are crucial for an AI agent to use it effectively in a context with multiple sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters ('url' and 'item_number') with examples and alternatives. The description adds no additional parameter semantics beyond implying that product details are fetched, but since the schema is comprehensive, a baseline score of 3 is appropriate as the description does not compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed product information'), listing key data fields like price, description, and availability. However, it does not explicitly differentiate from sibling tools like 'search_products' or 'check_warehouse_stock', which might also provide product-related information, leaving some ambiguity about its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'search_products' for broader queries or 'check_warehouse_stock' for availability details. It lacks context on prerequisites (e.g., whether authentication is needed) or exclusions, offering only a basic functional statement without usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool's function but lacks critical behavioral details: it doesn't specify whether this requires authentication (unlike tools like 'login' or 'get_orders'), what the return format is (e.g., list of locations with addresses), distance radius for 'nearby', error handling, or rate limits. For a read operation with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Find nearby Costco warehouses') and specifies the search method ('by ZIP code or city'). There is zero wasted verbiage, and every word contributes directly to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is incomplete. It adequately states what the tool does but fails to provide necessary context: no information on authentication requirements, return format, error conditions, or how 'nearby' is defined. Without annotations or output schema, the agent lacks guidance on how to interpret results or handle failures.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all four parameters (zip_code, city, state, limit). The description adds minimal value beyond the schema by mentioning 'ZIP code or city' as search inputs, but doesn't explain parameter interactions (e.g., that city and state might be used together, or that zip_code alone may suffice). Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Find nearby') and resource ('Costco warehouses') with the search method ('by ZIP code or city'). It distinguishes from most siblings like 'check_warehouse_stock' or 'search_products' by focusing on location lookup rather than inventory or product search. However, it doesn't explicitly differentiate from potential location-related tools that might not exist in this set.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether authentication is needed), when not to use it, or how it compares to siblings like 'get_delivery_options' which might also involve location data. The agent must infer usage from the tool name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the search functionality but lacks critical details: whether it's read-only (implied but not explicit), pagination behavior (only 'limit' parameter hints at it), rate limits, authentication requirements, or error handling. For a search tool with 6 parameters, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Search Costco products') and specifies search dimensions without unnecessary elaboration. Every element earns its place, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, no annotations, no output schema), the description is incomplete. It lacks information on return values (e.g., result format, fields included), error conditions, authentication needs, and usage context relative to siblings. For a search tool in an e-commerce environment, this leaves the agent under-informed about how to effectively use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 6 parameters with descriptions and enum values. The description adds minimal value beyond the schema, only mentioning 'name, category, or brand' which partially maps to the 'query' parameter. It doesn't explain parameter interactions (e.g., how 'query' and 'category' combine) or provide examples, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Search') and resource ('Costco products'), specifying searchable attributes ('by name, category, or brand'). It distinguishes from siblings like 'get_product_details' (specific product lookup) and 'check_warehouse_stock' (inventory check). However, it doesn't explicitly differentiate from potential overlapping tools like 'view_cart' (browsing vs. searching).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether login is required), compare to siblings like 'get_product_details' (for specific product info) or 'view_cart' (for browsing cart items), or specify use cases like exploratory shopping versus targeted lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Choose delivery method') but doesn't reveal whether this is a configuration step, a transactional operation, or has side effects like updating an order. No information about permissions, rate limits, or response format is included, which is inadequate for a tool with potential transactional 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, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's transactional nature (choosing delivery method) with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after selection, potential side effects, or how this integrates with other tools like 'checkout' or 'add_to_cart', leaving significant contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for adequate but not enhanced parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Choose delivery method — home delivery or warehouse pickup', which is a specific verb+resource combination. It distinguishes between two delivery options but doesn't explicitly differentiate from sibling tools like 'get_delivery_options' or 'check_warehouse_stock', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_delivery_options' or 'check_warehouse_stock'. It doesn't mention prerequisites, dependencies, or typical workflow context, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but only states what the tool does without additional context. It doesn't mention whether this is a read-only operation, requires authentication, has rate limits, or what the output looks like (e.g., status details, estimated delivery time). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose with zero waste. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what information is returned (e.g., delivery status, tracking number, updates) or behavioral aspects like error handling. For a tool with no structured data beyond the input schema, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'order_number' clearly documented as 'Costco order number'. The description adds no extra meaning beyond this, such as format examples or constraints, but the schema does the heavy lifting, justifying the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('track') and resource ('Costco order delivery status'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_orders' or 'status', which might have overlapping functionality, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_orders' or 'status'. It lacks context about prerequisites (e.g., whether login is required) or exclusions, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what information is retrieved but doesn't describe the tool's behavior—such as whether it requires authentication, has rate limits, returns structured data, or handles errors. This leaves significant gaps for a tool that accesses membership data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of accessing membership data, the description is incomplete. With no annotations and no output schema, it fails to disclose behavioral aspects like authentication needs, return format, or error handling. This leaves the agent under-informed for a tool that likely involves sensitive user information.
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 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here, but doesn't compensate for any gaps since there are none. A baseline of 4 is given as it's complete for a no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('check') and resources ('Costco membership status, type, and renewal date'), making it immediately understandable. However, it doesn't explicitly differentiate this from sibling tools like 'status' or 'get_orders', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., whether user authentication is required), context for use, or exclusions, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool checks availability but doesn't describe what 'availability' means (e.g., real-time stock levels, delivery timeframes), whether it requires authentication, rate limits, or what the response format looks like. This leaves significant gaps for a tool that likely queries external systems.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part earns its place by specifying what's being checked and the optional scope, 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?
Given no annotations and no output schema, the description is incomplete for a tool that likely returns complex availability data. It adequately states the purpose but lacks details on behavioral traits, response format, or error handling. For a tool with 2 parameters and external dependencies, more context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents both parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'cart items or a specific product', which loosely maps to the optional 'item_number' parameter. No additional syntax or format details are provided, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('check delivery and warehouse pickup availability') and resources ('cart items or a specific product'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'check_warehouse_stock' or 'get_warehouse_locations', which might offer overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by mentioning 'cart items or a specific product', but doesn't provide explicit guidance on when to use this tool versus alternatives like 'check_warehouse_stock' or 'get_warehouse_locations'. It hints at context (checking availability) but lacks clear when/when-not instructions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral context. It doesn't disclose whether this is a read-only operation, requires authentication, has rate limits, returns structured data, or handles errors. 'Check' suggests a query, but lacks details on what 'availability' means (e.g., binary yes/no, quantity levels).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Check in-warehouse availability') and specifies the resource and context directly. Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'availability' returns (e.g., stock status, quantities), whether authentication is needed, or how to interpret results. The lack of behavioral context leaves significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are documented in the schema. The description adds no additional meaning beyond implying 'zip_code' identifies the 'specific Costco location', which is already clear from schema descriptions. Baseline 3 is appropriate as the schema handles parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Check in-warehouse availability') and resource ('product at a specific Costco location'), distinguishing it from siblings like 'get_product_details' (general info) or 'get_warehouse_locations' (location data). It precisely defines the tool's scope as inventory checking for physical stores.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking product stock at warehouses, but provides no explicit guidance on when to use this versus alternatives like 'get_delivery_options' or 'search_products'. It doesn't mention prerequisites (e.g., needing a location) or exclusions (e.g., not for online stock).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions browser automation and headless mode, but lacks critical details: whether authentication persists across sessions, what happens on failure (e.g., error responses), rate limits, or security implications. For a sensitive authentication tool, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It front-loads the core purpose ('Authenticate with Costco account') and includes essential method details without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of authentication (sensitive operation with browser automation) and no annotations or output schema, the description is insufficient. It omits behavioral traits like session persistence, error handling, or security warnings, leaving critical gaps for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no additional meaning beyond implying email/password are for Costco accounts, which the schema already states. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Authenticate'), target resource ('Costco account'), and method ('using email and password via browser automation'). It distinguishes from siblings like 'logout' or 'get_membership' by focusing on initial authentication rather than session management or data retrieval.
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 this tool should be used for initial authentication, but provides no explicit guidance on when to use it versus alternatives (e.g., whether it's required before other tools like 'add_to_cart'), nor any prerequisites or exclusions. Usage context is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Check' implies a read-only operation, it doesn't specify whether this requires authentication, what specific information is returned (beyond 'status and session info'), or any rate limits/constraints. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the essential information. Every word earns its place - 'Check' (action), 'Costco' (context), 'authentication status and session info' (what's checked). No wasted words or unnecessary elaboration.
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 simplicity (0 parameters, no output schema, no annotations), the description is reasonably complete for a status-checking operation. However, it doesn't specify what information is actually returned or any authentication requirements, which would be helpful context. The absence of an output schema means the description should ideally hint at return values.
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 with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist. Baseline for zero parameters is 4, as there's no parameter information to add beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Check') and target resources ('Costco authentication status and session info'). It distinguishes itself from siblings like login/logout by focusing on status verification rather than authentication actions. However, it doesn't explicitly differentiate from potential status-checking siblings that might exist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (checking authentication/session status) but doesn't provide explicit guidance on when to use this versus alternatives like login or get_membership. No when-not-to-use scenarios or prerequisite conditions are mentioned, leaving usage decisions to inference rather than explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions updating or removing items, implying a mutation operation, but does not disclose critical traits such as authentication requirements, error handling (e.g., if item not in cart), or side effects (e.g., cart total changes). This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality ('update item quantities or remove items') and specifies the resource ('Costco cart'). There is no wasted text, and every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., auth needs, error cases), return values, or interactions with sibling tools. For a cart update tool, this leaves the agent with insufficient context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for both parameters (item_number and quantity). The description adds minimal value beyond the schema by implying the action context, but it does not provide additional syntax, format details, or examples. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('update item quantities or remove items') and the target resource ('Costco cart'), distinguishing it from siblings like 'add_to_cart' (which adds items) and 'view_cart' (which only reads). It precisely defines the tool's function without being vague or tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for modifying existing cart items, but it does not explicitly state when to use this tool versus alternatives like 'add_to_cart' (for new items) or 'view_cart' (for checking contents). It provides basic context but lacks explicit guidance on exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool views cart contents, implying a read-only operation, but doesn't specify if it requires authentication, returns real-time data, or handles errors. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('View current Costco cart contents and totals') with zero wasted words. It's appropriately sized for a simple, parameterless tool.
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 simplicity (0 parameters, no output schema) and lack of annotations, the description is minimally adequate but incomplete. It doesn't address authentication needs, return format, or error handling, which are relevant for a cart-viewing tool in an e-commerce context with sibling tools like 'login'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, earning a baseline score above 3 due to the lack of parameters.
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 ('View') and resource ('current Costco cart contents and totals'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'update_cart' or 'checkout', which might also involve cart interactions, so it doesn't reach the highest score.
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 needing to see cart contents, but provides no explicit guidance on when to use this versus alternatives like 'update_cart' or 'checkout', nor any prerequisites (e.g., login status). This leaves usage contextually implied rather than clearly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the preview/completion behavior and the confirm parameter's effect, which is useful. However, it lacks critical details: whether this requires authentication (vs. 'login'), what happens on completion (e.g., payment, confirmation), error conditions, or side effects. For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded: two sentences that directly state the purpose and key usage guideline. Every word earns its place, with no redundancy or fluff, making it efficient for an AI agent to parse quickly.
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 (order processing with potential mutations), lack of annotations, and no output schema, the description is minimally adequate. It covers the core action and parameter guidance but omits details on authentication needs, return values, error handling, or integration with siblings like 'view_cart'. This leaves gaps for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'confirm' fully documented in the schema. The description adds minimal value beyond the schema by reiterating the preview/completion logic ('Use confirm=false to preview first'), but doesn't provide additional syntax, format, or contextual nuances. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Preview or complete a Costco order.' It specifies the verb ('preview or complete') and resource ('Costco order'), making the action unambiguous. However, it doesn't explicitly differentiate from siblings like 'add_to_cart' or 'update_cart' in terms of order lifecycle stage, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: 'Use confirm=false to preview first.' This implies a two-step workflow (preview then complete) and suggests default behavior. However, it doesn't explicitly state when NOT to use it or name alternatives among siblings (e.g., vs. 'add_to_cart' for earlier stages), missing full differentiation.
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. It states the tool clears session and cookies, which implies a destructive action, but does not disclose behavioral traits like whether this logs out all devices, requires re-authentication, or affects other tools. More context on the impact would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is front-loaded with the core action and resource, 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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but could be more complete. It lacks details on behavioral outcomes (e.g., what happens after logout) or error cases, which would enhance agent understanding in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, earning a baseline score of 4 for this context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Clear') and target resources ('Costco session and stored cookies'), distinguishing it from siblings like login or status. It precisely communicates what the tool does without being tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (ending a session) but does not explicitly state when to use it versus alternatives like simply closing the browser. It clearly distinguishes from siblings like login, but lacks explicit when-not or alternative guidance.
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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