mcp-kroger

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct action/resource: login, store selection, product search/details, cart operations, coupons, fuel points, slots, checkout, order history/reorder. There is no meaningful overlap between any two tools.
Naming Consistency5/5
All tools follow the kroger_verb_noun pattern with snake_case. Verbs are consistent (login, set, search, get, add, view, update, clip, checkout, reorder) and the prefix is uniform.
Tool Count5/5
15 tools cover the full grocery shopping workflow without excess. The count is well within the 3-15 typical range and each tool earns its place for a cohesive experience.
Completeness4/5
The surface covers login through checkout, including order history and reorder. Minor gaps exist (e.g., no explicit account management, no coupon removal), but the core lifecycle is fully represented.
Average 3.6/5 across 15 of 15 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 for behavioral disclosure. The verb 'get' implies a read-only operation, but the description does not explicitly state that it has no side effects, nor does it mention authentication requirements or how the returned data is structured. This is a significant gap for a tool that accesses account 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, focused sentence that earns its place. It conveys the essential purpose without unnecessary detail, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one optional parameter, no output schema), but the description omits usage guidelines and behavioral details such as login requirements or return value shape. It is minimally viable but leaves clear gaps in context that could affect correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes the only parameter `limit` as 'Number of orders to retrieve', so schema coverage is 100%. The description adds no additional parameter context. Per guidelines, baseline 3 is appropriate when the schema handles 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: 'Get recent order history from Kroger account.' It identifies the verb (get) and resource (recent order history), which distinguishes it from sibling tools like kroger_view_cart and kroger_get_coupons. However, it does not explicitly call out alternatives, hence not a 5.
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 does not mention prerequisites (e.g., needing to log in first) or scenarios where this tool is preferred. This lack of usage context means the agent must infer 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?
With no annotations, the description carries the full burden of behavioral disclosure, but it merely states an action without revealing consequences. It is unclear whether reorder adds items to the current cart, replaces the cart, or immediately creates a new order, and no mention is made of the effect on the existing cart or confirmation steps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, effectively communicating the core action. While it is terse, it is appropriately sized for a simple tool and does not contain unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It fails to explain the outcome (add to cart vs. direct order), prerequisites such as login, or its relationship to sibling tools like checkout or cart management, leaving significant gaps for an agent to navigate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the only parameter (orderId) as 'Previous order ID to reorder' with 100% coverage. The description adds no further meaning, such as where to find the order ID or any expected format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly names the action (Reorder) and the target resource (items from a previous order), making its purpose immediately understandable. It distinguishes itself from sibling tools like kroger_get_order_history (viewing orders) and kroger_checkout (processing current cart).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not mention prerequisites (e.g., being logged in), where to obtain the orderId (e.g., from kroger_get_order_history), or when to use this tool versus alternatives like adding items manually or going directly to checkout.
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 disclosing behavior. It only states that a product is added, without addressing authentication needs, side effects on existing cart items, error behavior, or whether the operation is idempotent. For a mutating 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, front-loaded sentence with no filler. It states the operation, object, destination, and quantity parameter efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but there is no output schema and no annotations. The description omits important context such as whether login is required, how duplicate additions are handled, how to obtain product IDs, or what the return value looks like. It is adequate for a basic operation but has clear 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?
The input schema already describes both parameters (productId as 'Kroger product ID' and quantity as 'Quantity to add') with 100% coverage. The description adds little beyond the schema, merely repeating the notion of a specified quantity.
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 verb 'Add', the object 'product', and the destination 'Kroger shopping cart', while also mentioning quantity. This distinguishes it from sibling cart tools like view_cart or update_cart_item.
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?
There is no explicit guidance on when to use this tool versus alternatives, nor any mention of prerequisites like logging in or searching for products first. The usage is implied by the name and verb 'Add', but not elaborated.
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 behavioral burden. It states that coupons 'can be clipped' but does not disclose whether login is required, whether the operation is read-only or modifies state, or what 'available' means. It also omits output format and potential pagination or personalization 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, front-loaded sentence containing only the essential purpose. It has no filler, redundancy, or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter with no output schema and no annotations, the description covers the core action but leaves gaps around authentication requirements, return shape, and the relationship between 'clipped' coupons and the Plus card. Schema coverage helps parameter understanding, but the description alone is not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes both parameters with 100% coverage, so the baseline is 3. The description does not add any meaning beyond the schema, such as how category filtering or personalizedOnly affects results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a verb and resource: 'Get available digital coupons' and adds a meaningful qualifier 'that can be clipped to the Kroger Plus card,' which distinguishes it from sibling tools like kroger_clip_coupon. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a read/browse usage before clipping but does not explicitly state when to use this tool versus alternatives such as kroger_clip_coupon. No when/when-not conditions or exclusions are provided, leaving usage guidance implicit.
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?
There are no annotations, so the description must carry full weight. It states what data is returned, but does not disclose whether authentication is required, whether the call is read-only, or what happens for invalid/unknown product IDs. This leaves the agent without a clear safety or error-handling profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It concisely answers what the tool does and what info it returns, earning every word.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter getter with no annotations and no output schema, the description covers the core purpose and return content. However, it lacks guidance on prerequisites (e.g., login) and any behavioral caveats (e.g., availability of nutrition data varies by product), leaving some gaps for full contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single parameter, describing 'productId' as 'Kroger product ID'. The description adds no additional parameter context beyond implying it refers to a specific product, so it neither improves nor degrades the semantic clarity offered by the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and identifies a clear resource ('detailed information about a specific product'). It lists concrete fields (nutrition facts, ingredients, availability) and implicitly distinguishes itself from sibling tools like search_products, which returns a list rather than details for a single product.
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 is used when a specific product is already known, contrasting with search_products. However, it does not explicitly state that the productId comes from a preceding search, nor when not to use it. There is no explicit mention of alternatives 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?
No annotations are provided, so the description bears full responsibility for disclosing side effects. It mentions 'Returns order summary for confirmation' but does not clarify whether the order is actually placed, whether payment is processed, or what happens to the cart after checkout. There is no mention of prerequisites like authentication or having items in the cart, nor any warning about irreversible side effects. This lack of transparency is significant for a checkout action.
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 consists of two short sentences that immediately state the purpose and output. There is no redundant information or filler, making it appropriately concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a checkout tool with 3 parameters, no output schema, and no annotations, the description is too sparse. It does not mention prerequisites (e.g., logged in, items in cart, slot selected), failure conditions, or whether the order is finalized. The return value is mentioned only vaguely as an 'order summary for confirmation,' which is insufficient for an agent to fully understand the tool's behavior in a complex workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides a description for every parameter (100% coverage), so the description adds minimal value beyond that. It does not explain inter-parameter dependencies (e.g., slotId depends on fulfillmentType) or provide any additional formatting or selection guidance. With full schema coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Proceed to checkout with the current cart.' This uses a specific verb ('proceed to checkout') and resource ('current cart'), and it distinguishes itself from sibling tools like add_to_cart or view_cart. It also mentions the return value, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is used after cart preparation and slot selection (it references 'current cart' and takes slotId/fulfillmentType as inputs). However, it does not explicitly state when not to use it or name alternative tools like update_cart_item or get_delivery_slots. The context is clear but exclusions are absent.
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, the description carries the full burden. It discloses the primary effect (automatic discount at checkout) but omits prerequisites (e.g., login, store selection) and any side effects like idempotency or failure behavior. This is a minimal disclosure for a state-changing action.
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?
A single, well-structured sentence that front-loads the verb and resource, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description covers the core action and result. It lacks explicit mention of dependencies, but the sibling context (login, set_store) provides some context. Overall fairly complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes couponId as 'Coupon ID to clip' (100% coverage). The description adds no additional parameter semantics beyond the schema, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'clip' and identifies the resource 'digital coupon to the Kroger Plus card', clearly distinguishing from sibling tools like kroger_get_coupons (listing coupons) and kroger_add_to_cart (adding products to cart).
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 you want to clip a coupon for checkout discount) but does not explicitly mention alternatives or prerequisites like logging in or selecting a store. It lacks clear when-to-use vs. when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It indicates a read-only operation via 'Get', but does not disclose any prerequisites (e.g., items in cart, active session) or side effects. It adds minimal behavioral context beyond the obvious action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no fluff. Every word contributes: 'Get', 'delivery time slots', 'current cart and store' are all essential. It is appropriately sized for a simple getter 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?
No output schema exists, so the description should clarify return expectations. It does not explain what happens when no date is provided, the range of slots returned, or the response structure. For a simple tool it is minimally adequate but lacks these details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the optional 'date' parameter. The description does not add extra meaning about the parameter, just restates the cart/store context. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'available delivery time slots' for the current cart and store. It explicitly specifies 'delivery', distinguishing it from the sibling tool 'kroger_get_pickup_slots'.
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 (for the current cart and store) but does not explicitly state when to use delivery slots vs pickup slots or mention alternatives. It gives no exclusions or conditions, so guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 only states the outcome (available slots) but does not disclose behavioral traits such as dependency on a selected store, network/real-time behavior, error cases, or what the response contains. The minimal text offers little beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no filler. Every word contributes to clarity and it is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single optional parameter, no output schema, and no annotations, the description is minimal but not entirely inadequate. It misses prerequisite context (login, store selection) and does not indicate the return format. Adequate for a simple getter, but leaves gaps for an agent relying solely on 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% (the 'date' parameter has a clear format and optional flag). The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('available pickup time slots') with context ('current cart and store'). It clearly distinguishes from the sibling 'kroger_get_delivery_slots' by specifying 'pickup'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for pickup slots, naturally differentiating from delivery slots via the fulfillment type. However, it does not explicitly state when to use this tool over the delivery alternative or mention prerequisites like login or store selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the prerequisite nature and the action itself, but does not describe session handling, authentication outcomes, error behavior, or any security implications. This is a significant gap for a state-changing 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 extremely concise: two short sentences that front-load the action and then add the prerequisite context. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple login tool, the description covers the core purpose, required parameters, and the important prerequisite status. However, with no output schema, it does not explain what a successful login returns or how the agent confirms success, nor does it mention session duration or logout-related behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with descriptions for both parameters ('Kroger account email' and 'Kroger account password'). The description only echoes these fields without adding format, constraints, or additional context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Log in to Kroger account with email and password.' It identifies the specific resource (Kroger account) and distinguishes itself from sibling tools (all other operations are post-login actions).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Required before most operations' provides clear context for when to use the tool—before using other Kroger tools. It implies using this first but does not explicitly name alternatives or exclusions, which would be unnecessary given the sibling list.
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 must fully disclose behavior. It only states that it returns product details with prices, but omits whether authentication, store selection, or other prerequisites are needed. It also doesn't mention any side effects or limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. The primary action and key output are stated up front, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple search operation, and the description covers the core purpose and result type. However, it lacks contextual details like dependency on store selection (sibling set_store) or any pagination/result structure, which would improve completeness given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents all four parameters with descriptions (100% coverage). The description adds a small clarification that 'query' refers to product name, but does not elaborate on onSale or category beyond the schema, so it adds minimal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search for products on Kroger by name, brand, or category.' This distinguishes it from siblings like get_product_details by indicating it's a general search, not a detail lookup.
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 gives clear context for when to use it: to find products by query, brand, or category. However, it does not explicitly mention alternatives or when not to use it, so it earns a 4 rather than 5.
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?
Without annotations, the description carries the full burden for behavioral disclosure. It states a mutating action ('Set') and a consequence (affects availability/prices), but it omits important details such as whether login is required, what happens when both or neither parameters are provided, error handling, or the response format. This is insufficient for a state-changing 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no redundant information. The first sentence states the action and method, the second explains the impact. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple tool with only two optional parameters and no output schema, so the description is somewhat adequate. However, it does not mention what happens when a zip code is provided (auto-select nearest vs. return options), the return value, or prerequisites like login. These gaps reduce completeness for a tool in a complex integration context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already explains both parameters. The description only paraphrases the schema ('by zip code or store ID') and adds no extra semantic detail such as parameter precedence, format, or whether they are mutually exclusive. 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 a specific action ('Set the preferred Kroger store location') with a defined resource and method ('by zip code or store ID'). It also explains the consequence ('determines product availability and prices'), making its purpose distinct from sibling tools like search or cart operations.
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: this tool is for setting the preferred store, which is distinct from other sibling tools. It implies it should be used before product searches or cart operations to affect availability and pricing. However, it does not explicitly mention when not to use it or alternatives, though none seem necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a key behavioral trait: setting quantity to 0 removes the item entirely. However, with no annotations, the description carries the full burden and does not mention prerequisites (e.g., item must already be in the cart) or potential failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the action and gets straight to the point. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mutation tool with two well-documented parameters and no output schema, the description is largely sufficient. It covers the core actions but could benefit from noting assumptions like the item already being in the cart.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with 100% coverage. The description adds no new semantic information beyond what is in the schema; it only reiterates that removing is possible.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with specific verbs ('Update quantity' and 'remove') tied to a resource ('an item in the cart'). It distinguishes itself from sibling tools like add_to_cart (which adds new items) and view_cart (which lists items).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied but not explicit. The description indicates this tool is for changing the quantity of an existing item or removing it, but it does not mention alternatives (e.g., add_to_cart for adding new items) or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The verb 'check' strongly implies a read-only operation, which is a useful behavioral hint. However, it does not disclose prerequisites like authentication (e.g., requiring login) or what exactly is returned, leaving some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant information. It is immediately clear and front-loaded with the action and subject.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema tool, the description is largely sufficient. It names both the balance and rewards as outputs. However, it omits mention of any authentication requirements or whether the tool is usable before logging in, which is relevant given the existence of a login sibling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty with 100% coverage. Baseline for zero parameters is 4, and the description adds no further parameter details, which is acceptable since there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Check') and resource ('current fuel points balance and available fuel point rewards'). It is easily distinguishable from sibling tools, which focus on shopping, cart, or checkout operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to retrieve fuel points status but provides no explicit context on when to use it (e.g., before checkout) or any alternatives. Given the sibling list, no other tool covers fuel points, so usage is self-evident but not explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. The word 'view' correctly implies a read-only operation with no side effects. However, it does not disclose whether authentication is required, whether the cart must be initialized, or what exact data the response contains (beyond items, prices, totals). It is minimally transparent but not deeply informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that immediately conveys the tool's purpose. Every word earns its place, with no filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, no-parameter view tool, the description adequately covers the core function. It mentions the key outputs (items, prices, totals). It doesn't specify the exact response format or potential prerequisites (like login), but given the low complexity and no output schema, the description is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, which makes parameter documentation unnecessary. Per the baseline for 0-param tools, a score of 4 is appropriate. The description adds nothing about parameters because there are none to describe.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('View') and clearly identifies the resource ('current items in the Kroger shopping cart') and the key details shown (prices and totals). It is immediately distinct from sibling tools like kroger_add_to_cart or kroger_checkout, which have different actions.
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 the tool is for reading the cart contents (inspect before checkout), and the verb 'view' clearly signals a non-modifying operation. It does not explicitly name alternatives or exclusions, but the context of sibling tools makes the usage obvious.
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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