wonderkraftz-mcp
Allows AI assistants to search products, get details, browse collections, receive recommendations, manage cart, and generate checkout URLs through the Shopify Storefront API.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@wonderkraftz-mcpFind me premium wedding gift hampers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Wonderkraftz MCP Server
An MCP (Model Context Protocol) server that connects AI assistants to the Wonderkraftz Premium Gifting Studio. Browse products, get personalized gift recommendations, manage your cart, and checkout — all through natural language in your AI assistant.
Features
Product Search — Search the catalog by keyword, occasion, or gift type
Product Details — Get full product info including variants, pricing, and images
Collections — Browse curated gift collections (Corporate Gifts, Wedding Hampers, etc.)
Recommendations — Get product suggestions based on a product you like
Cart Management — Create carts, add/update/remove items
Checkout — Get a checkout URL to complete your purchase in a browser
Store Policies — View shipping, returns, and privacy policies
Related MCP server: FakeStore MCP
Quick Start
Option 1: npx (no install needed)
SHOPIFY_STORE_DOMAIN=64cd5c-2.myshopify.com \
SHOPIFY_STOREFRONT_ACCESS_TOKEN=aeeec5ab77309d1c339d2971f56b6506 \
npx wonderkraftz-mcpOption 2: Install globally
npm install -g wonderkraftz-mcpSetup
Cursor IDE
Add to your project's .cursor/mcp.json:
{
"mcpServers": {
"wonderkraftz": {
"command": "npx",
"args": ["-y", "wonderkraftz-mcp"],
"env": {
"SHOPIFY_STORE_DOMAIN": "64cd5c-2.myshopify.com",
"SHOPIFY_STOREFRONT_ACCESS_TOKEN": "aeeec5ab77309d1c339d2971f56b6506"
}
}
}
}Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"wonderkraftz": {
"command": "npx",
"args": ["-y", "wonderkraftz-mcp"],
"env": {
"SHOPIFY_STORE_DOMAIN": "64cd5c-2.myshopify.com",
"SHOPIFY_STOREFRONT_ACCESS_TOKEN": "aeeec5ab77309d1c339d2971f56b6506"
}
}
}
}ChatGPT / Grok / Remote AI Tools
Use the hosted HTTP endpoint -- no install needed:
https://wonderkraftz-mcp.onrender.com/mcpPoint your MCP client to this URL. It supports Streamable HTTP transport.
Self-Hosted HTTP (optional)
To run the HTTP transport yourself:
SHOPIFY_STORE_DOMAIN=64cd5c-2.myshopify.com \
SHOPIFY_STOREFRONT_ACCESS_TOKEN=aeeec5ab77309d1c339d2971f56b6506 \
npx wonderkraftz-mcp-httpThe server starts on http://localhost:3000/mcp (or set PORT env var).
Transports
Transport | Entry Point | Use Case |
stdio |
| Cursor, Claude Desktop, local AI tools |
Streamable HTTP |
| ChatGPT, Grok, remote/cloud AI tools |
Environment Variables
Variable | Description | Required |
| Shopify store domain (e.g., | Yes |
| Public Storefront API access token | Yes |
| HTTP server port (default: 3000, HTTP transport only) | No |
Available Tools
Tool | Description |
| Search the product catalog by keyword |
| Get full details for a product by handle or ID |
| List all product collections |
| Browse products in a specific collection |
| Get product recommendations based on a product |
| Create a new shopping cart with items |
| Add items to an existing cart |
| Update item quantities in a cart |
| Remove items from a cart |
| View cart contents and totals |
| Get checkout URL to complete purchase |
| View store shipping, return, and privacy policies |
Available Resources
URI | Description |
| Store information, branding, and payment settings |
| List of all product collections |
Example Conversations
"Show me corporate gift options under 2000 rupees"
"I need a wedding gift hamper. What do you recommend?"
"Add the luxury gift box to my cart and give me the checkout link"
"What's your return policy?"
Development
git clone https://github.com/rachit1987/wonderkraftz-mcp.git
cd wonderkraftz-mcp
npm install
cp .env.example .env # Add your Shopify credentials
npm run build
npm start # stdio transport
npm run start:http # HTTP transportLicense
MIT
Available Tools
12 toolsadd_to_cartA
Add products to an existing Wonderkraftz shopping cart.
| Name | Required | Description | Default |
|---|---|---|---|
| cartId | Yes | Cart ID (e.g., 'gid://shopify/Cart/...') | |
| items | Yes | Items to add |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavior. It only states it adds products, missing details on mutation consequences, limits, authentication needs, or return value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb and object, no redundancy or unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Low complexity tool but lacks details on error handling and return value; adequate for basic use but incomplete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for both parameters. The description adds no extra parameter info beyond 'existing cart' context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'Add' and resource 'products to an existing Wonderkraftz shopping cart', clearly distinguishing it from siblings like create_cart and remove_from_cart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for existing carts but does not explicitly state when to use this vs alternatives, nor does it mention prerequisites or error conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_cartB
Create a new shopping cart with one or more Wonderkraftz products. Returns cart ID and checkout URL.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Items to add to the new cart |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses creation and return values but does not mention side effects (e.g., overwriting existing carts), authentication needs, rate limits, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences and front-loaded with purpose. No wasted words, but could be slightly improved by integrating usage guidance without increasing length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a single well-described parameter, the description is adequate but leaves out prerequisites, permissions, and error handling. For a simple creation tool, it's minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no extra meaning beyond what the schema already provides for the items parameter. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action (create), the resource (a new shopping cart), and the return values (cart ID and checkout URL). It distinguishes from siblings like add_to_cart by implying creation of new carts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description does not explicitly state when to use this tool versus alternatives, such as when to create a new cart vs. adding to an existing one with add_to_cart. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_cartA
View the current contents of a Wonderkraftz shopping cart including items, quantities, totals, and checkout URL.
| Name | Required | Description | Default |
|---|---|---|---|
| cartId | Yes | Cart ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description only states that it 'View's contents, implying a read operation. It does not disclose any behavioral traits such as authentication needs, rate limits, or side effects, but for a simple read 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 16 words, front-loaded with the action and resource, with no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description adequately covers what the tool returns (items, quantities, totals, checkout URL). Slightly more detail on structure could improve completeness, but it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single parameter (cartId: 'Cart ID'). The tool description adds no additional meaning beyond that, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'View' and clearly identifies the resource as the current contents of a Wonderkraftz shopping cart, listing specific return elements (items, quantities, totals, checkout URL). This differentiates it from sibling tools like add_to_cart or remove_from_cart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for viewing cart contents but provides no explicit guidance on when to use it versus alternatives like get_checkout_url, nor does it state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_checkout_urlB
Get the checkout URL for a Wonderkraftz shopping cart to complete the purchase in a browser.
| Name | Required | Description | Default |
|---|---|---|---|
| cartId | Yes | Cart ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey all behavioral traits. It only states that a checkout URL is retrieved, omitting potential side effects (e.g., whether the cart state changes), prerequisites (e.g., cart must have items), or any limitation like single-use URLs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that instantly conveys the tool's purpose. Every word is essential, with no redundancies or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should clarify the return value (a URL). It also fails to mention whether the cart must be in a valid state. For a simple one-parameter tool, these omissions make it less complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes 'cartId' as 'Cart ID' with 100% coverage. The description adds 'Wonderkraftz shopping cart' for brand context, but does not explain the expected format or any constraints beyond that. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Get'), the resource ('checkout URL'), and the context (for a Wonderkraftz shopping cart to complete a purchase). It distinguishes itself from sibling tools like get_cart or add_to_cart by focusing on the checkout step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a checkout URL is needed, but does not explicitly state when to use or not use it, nor does it mention alternatives. It provides implicit context 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.
get_collection_productsB
Browse products within a specific Wonderkraftz collection by its handle/slug.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | Collection handle/slug (e.g., 'corporate-gifts') | |
| limit | No | Number of products to return |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description uses 'Browse' implying a read operation, but does not explicitly state it is non-destructive or disclose behavioral traits like authentication needs, rate limits, or pagination behavior. Since no annotations are provided, the description should cover these, but it does not.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It efficiently conveys the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with two well-documented parameters and no output schema or annotations, the description is minimally adequate. However, it lacks details on ordering, field selection, and whether it returns all products or only a subset beyond the limit parameter. Completeness is average.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already explains both parameters. The description adds no new semantic information beyond what is in the schema (the term 'handle/slug' is echoed). Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's action ('Browse products') and the resource ('products within a specific collection'), specifying the key input ('handle/slug'). It is distinct from sibling tools like 'get_collections' (list collections) and 'get_product_details' (single product), though not explicitly differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention exclusions or contexts, such as preferring this over 'search_products' when the collection is known.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_collectionsA
List all product collections/categories in the Wonderkraftz store (e.g., Corporate Gifts, Wedding Gifts, Festival Hampers).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of collections to return |
TDQS
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 only states the function without mentioning any behavioral traits like idempotency, rate limits, authentication needs, or return behavior beyond listing. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with examples, highly efficient and front-loaded with the core purpose. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with one optional parameter and no output schema, the description is largely complete. It could mention the return format (e.g., list of collection objects) but the examples imply the kind of data. It is adequate for the given complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the limit parameter is fully described in the input schema (min, max, default). The description adds no additional meaning beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses 'list all product collections/categories' as a specific verb+resource, provides concrete examples (e.g., Corporate Gifts), and implicitly distinguishes from sibling tools like get_collection_products.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states what the tool does but does not explicitly specify when to use it over alternatives or when not to use it. The context of sibling tools provides implicit differentiation, but no explicit usage guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_product_detailsA
Get full details for a specific Wonderkraftz product including all variants, pricing, images, and options. Use handle (slug) or product ID.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | No | Product handle/slug (e.g., 'luxury-gift-hamper') | |
| id | No | Shopify product ID (e.g., 'gid://shopify/Product/12345') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It fails to state that this is a read-only operation, mention auth requirements, rate limits, error handling, or what happens if the product is not found. The description only lists output scope without safety or side-effect disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and scope, second specifies identifiers. No redundant words, front-loaded with key information. Very concise and effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately lists return contents (variants, pricing, images, options). However, it does not mention return format (single object vs array) or error behavior. Still reasonably complete for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds 'Use handle (slug) or product ID,' which aligns with schema but does not clarify which parameter to prefer or provide additional semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets full details for a specific product, listing variants, pricing, images, and options. It also mentions using handle or product ID, which distinguishes it from sibling tools like search_products that return lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says to use handle or product ID, implying prerequisites but does not explicitly state when to use this tool versus siblings like search_products or get_collection_products. No exclusions or alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recommendationsA
Get product recommendations based on a specific Wonderkraftz product. Useful for suggesting similar or complementary gifts.
| Name | Required | Description | Default |
|---|---|---|---|
| productId | Yes | Shopify product ID to get recommendations for (e.g., 'gid://shopify/Product/12345') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description must cover behavior. It indicates a read operation but lacks details on output format, pagination, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences with no redundant information, front-loading the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple one-parameter tool but missing details about recommendation type or count, given lack of output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema provides full description of productId parameter; description does not add extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Get product recommendations' and specifies input 'based on a specific Wonderkraftz product', clearly distinguishing from sibling tools like search_products and get_product_details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States usefulness for suggesting similar or complementary gifts, providing clear context but no explicit when-not-to-use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_store_policiesA
Get Wonderkraftz store policies including shipping, returns, privacy, and terms of service.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It only states the tool gets policies, but does not disclose any behavioral traits like authentication needs, rate limits, or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short, well-structured sentence that is front-loaded and contains no unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with no parameters and no output schema, the description is adequate. It lists policy types but does not specify output format or structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters (schema coverage 100%), so baseline is 4. The description adds value by naming the policy categories included in the response.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves store policies and lists specific types (shipping, returns, privacy, terms of service). It distinguishes from sibling tools which focus on cart, products, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use versus alternatives. However, the tool has no parameters and is straightforward, making its usage obvious. Implied usage for retrieving policies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remove_from_cartB
Remove specific items from a Wonderkraftz shopping cart by their line item IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| cartId | Yes | Cart ID | |
| lineIds | Yes | Cart line item IDs to remove |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral details such as idempotency, error handling for non-existent line IDs, or side effects on cart totals.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no unnecessary words. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no output schema, the description does not clarify what the tool returns (e.g., updated cart or success status) or handle potential errors. Incomplete for practical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers both parameters (cartId and lineIds) with descriptions, and the tool description adds no additional meaning beyond the schema. With 100% schema coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (remove), the resource (items from a Wonderkraftz shopping cart), and the method (by line item IDs). It is specific and distinguishes from sibling tools like add_to_cart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for removing specific items but lacks explicit guidance on when not to use or alternatives. No prerequisites or caveats are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_productsA
Search the Wonderkraftz product catalog by keyword, occasion, or gift type. Returns product names, prices, availability, and IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query (e.g., 'corporate gifts', 'wedding hamper', 'chocolate box') | |
| limit | No | Number of results to return (max 20) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses output fields (names, prices, availability, IDs) but omits behavioral traits like read-only nature, pagination behavior, or any side effects. With no annotations, the description provides some transparency but not full 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two clear, front-loaded sentences with no excess words. Every sentence adds value: first states action and scope, second details return information. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with 2 parameters and no output schema, the description adequately covers purpose and return fields. Missing details like ordering or empty result behavior, but overall complete enough given low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minor context (search by keyword, occasion, gift type) that aligns with the 'query' parameter description, but does not significantly enhance param understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches the product catalog with specific search dimensions (keyword, occasion, gift type) and lists returned fields. It distinguishes from sibling tools like get_product_details or get_recommendations by focusing on general search rather than single product retrieval or recommendations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for broad catalog searches, but does not explicitly guide when to use this tool versus alternatives (e.g., when to use get_recommendations instead). No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_cartA
Update quantities of items in a Wonderkraftz shopping cart. Set quantity to 0 to remove an item.
| Name | Required | Description | Default |
|---|---|---|---|
| cartId | Yes | Cart ID | |
| items | Yes | Line items to update |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses the key behavior of removing items by setting quantity to 0, but lacks information on idempotency, error handling, or permissions. Since no annotations exist, the description carries the full burden but is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no fluff. The main action is front-loaded, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no output schema, the description covers the core function and the special removal behavior. It lacks mention of return value or error conditions, but these are partially covered by common REST conventions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description adds semantic value by explaining that quantity 0 means removal, which is not obvious from the schema alone. However, it doesn't add further detail about the items array structure beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb (update) and resource (quantities of items in shopping cart). It explicitly mentions setting quantity to 0 for removal, distinguishing from add_to_cart and remove_from_cart siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. For example, it doesn't clarify whether to use update_cart vs remove_from_cart for removing items, or when to use update_cart vs add_to_cart for increasing quantities.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool has a distinct and unambiguous purpose: cart management, product browsing, recommendations, and store policies. There is no overlap or potential for confusion.
All tool names follow a consistent verb_noun pattern with snake_case (e.g., add_to_cart, get_collections). The naming is predictable and clear.
12 tools is well-scoped for an e-commerce server, covering essential operations without being too sparse or overwhelming.
The tool set covers the full shopping workflow: cart CRUD, product search and discovery, recommendations, and store policies. A minor gap is the lack of a tool to browse all products without a collection search, but search_products effectively fills that role.
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