Family Grocery MCP

by KyleKaminky

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation3/5
Several tools have overlapping purposes, particularly preview_shopping vs preview_live_shopping, which both generate shopping previews but differ only in data source. search_kroger and preview_live_shopping also both involve live product search, creating potential misselection. However, the core workflow tools (auth, cart, planning) are distinct.
Naming Consistency2/5
Tool names mix verb-first patterns (plan_week, search_kroger), gerund forms (preview_shopping), lengthy prepositional phrases (add_approved_items_to_kroger_cart), and one noun-phrase status (kroger_cart_auth_status). No consistent verb_noun convention is followed, making the set feel ad hoc.
Tool Count5/5
12 tools is well within the ideal 3-15 range for a grocery planning and Kroger integration server. Each tool maps to a distinct step in the workflow (plan, preview, search, auth, cart), and none feel redundant or unnecessary.
Completeness4/5
The tool set covers the full journey from meal planning to adding items to a real Kroger cart, including authentication and preview stages. Minor gaps exist: no tool to view or modify the generated meal plan, and no way to list current cart contents or remove items, but these are likely out of scope.
Average 3.3/5 across 12 of 12 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided; the description does not disclose whether the tool mutates state, requires authentication, or has side effects. The phrase 'prepare' is ambiguous regarding whether it actually adds items to the cart.
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 sentence with no fluff, but it sacrifices clarity for brevity.
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?
With 2 parameters and an output schema, the description is too thin to understand the tool's role in the Kroger cart workflow. It lacks context about what 'prepare' means and how it relates to 'add_approved_items_to_kroger_cart'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not mention 'location_id' or 'dinner_count' at all, leaving their purpose and defaults unexplained.
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 uses the verb 'prepare' with resource 'approved cart items' and mentions a secondary output of skipped allergy-review items. It gives a specific purpose but does not define what 'prepare' entails, though it distinguishes from sibling 'add_approved_items_to_kroger_cart' by implying a pre-step.
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 given on when to use this tool vs. the many sibling cart tools. It doesn't state whether this is a dry run or a necessary precursor to adding items.
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 mentions 'mock product matches' which hints at non-real data, but it does not disclose whether this tool performs side effects, requires authentication, or is a read-only preview. The behavior remains ambiguous.
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, albeit informative, sentence. It front-loads the primary action and lists key outputs without wasted words, though it sacrifices detail for brevity.
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 presence of an output schema, return values are covered, but the description still lacks essential context about the role of dinner_count, the exact meaning of 'mock product matches', and the relationship to the live preview sibling. Overall, it is insufficient for a tool with 0% schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, dinner_count, has a default but no description in the schema or in the tool description. The description does not explain how this parameter affects the shopping list or budget, leaving the agent without guidance.
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 uses the verb 'generate' and lists specific outputs (shopping list, mock product matches, allergy review flags, and budget), making the core function clear. However, it does not explicitly differentiate from the sibling preview_live_shopping, leaving ambiguity about when this specific variant is appropriate.
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 about when to use this tool versus alternatives like preview_live_shopping or plan_week. The description gives no context for 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 must carry the full burden of behavioral disclosure. It only states that a preview is generated, but does not disclose whether the operation is read-only, whether it requires authentication, or what side effects (if any) it has. This is a significant gap for a tool that could be assumed to be safe.
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, front-loaded sentence with no wasted words. It clearly states the primary action and resource. However, it is perhaps too sparse, sacrificing valuable usage and parameter information for brevity. Still, it earns a high score for directness.
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 presence of many sibling tools (plan_week, preview_shopping, search_kroger, etc.), the description lacks essential context for an agent to effectively choose this tool. It doesn't explain when to use 'live' preview over other options, nor does it clarify the meaning of its parameters. The low parameter count and output schema help, but the description remains insufficient for confident tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions for its parameters (location_id and dinner_count), and the description does not mention either parameter. With 0% schema description coverage, the description needed to provide context, but it fails entirely, leaving the agent uninformed about what these parameters control.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action and scope: 'Generate shopping preview using live Kroger product search.' It uses a specific verb ('generate'), names the resource ('shopping preview'), and adds 'live' to distinguish from the sibling tool 'preview_shopping', which likely uses non-live data. This differentiates it well.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like preview_shopping or plan_week. The description does not mention exclusions, prerequisites, or typical use cases. The agent is left to infer based solely on the name and the word 'live'.
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 carries the full burden for behavioral transparency. It only states that it 'creates' a plan, but does not disclose side effects, whether it modifies stored data, authentication requirements, rate limits, or any potential risks. The use of 'household profile' hints at an input dependency, but this is minimal context and does not clarify what actually happens when invoked.
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 is front-loaded with the action and object. Every word earns its place: 'Create' is the verb, 'starter weekly meal plan' is the deliverable, and 'using the household profile' adds essential context. There is no redundancy or filler.
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) and has an output schema, so the description does not need to explain return values. However, the complete lack of parameter semantics and usage guidance leaves gaps. An agent might understand the tool's purpose but would not know how to configure 'dinner_count' or when to call it relative to shopping workflows. This is adequate for a minimal viable description but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one optional parameter 'dinner_count' with a default of 5, but the description does not mention it at all. Schema description coverage is 0%, so the description fully fails to explain the meaning or usage of the parameter. The agent is left to guess what 'dinner_count' represents in the context of a weekly meal plan.
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: 'Create a starter weekly meal plan using the household profile.' It names a specific verb ('create'), a concrete resource ('weekly meal plan'), and a data source ('household profile'). The sibling tools are all shopping/Kroger-related, so this is clearly distinct in purpose.
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 any prerequisites, exclusions, or mention of sibling tools. The existence of sibling shopping tools implies a different use case, but the description itself offers no explicit usage context or decision criteria.
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 'live' products but does not disclose any safety profile, authentication needs, rate limits, error behavior, or data freshness. For a search tool that might have side effects or prerequisites (e.g., authentication as implied by some sibling tools), 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, front-loaded sentence with no redundant words. It efficiently communicates the core function 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 tool's simplicity and the existence of an output schema, the description is still incomplete. It does not address potential authentication requirements (implied by sibling tools like start_kroger_cart_auth), any location validation, or what happens if no products are found. The description leaves too much unstated for an agent to invoke the tool confidently in all contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only vaguely references 'selected location' to hint at location_id, but provides no clarification for 'term' or 'limit' beyond their obvious names. The description does not explain the meaning of 'limit' or its default behavior, and 'term' is undefined.
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 ('Search'), the resource ('live Kroger products'), and the scope ('at a selected location'). It distinguishes from the sibling tool search_kroger_locations, which searches for locations, not products.
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, nor does it mention exclusions or prerequisites. It merely states what the tool does, leaving the agent to infer usage context from the tool name and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden for behavioral disclosure. It discloses that the tool affects the real Kroger cart and that the confirm flag gates execution. However, it does not mention required authentication (sibling tools indicate auth), what constitutes 'approved' items, or what happens when confirm is false.
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 words. It front-loads the primary action and the key constraint, making it easy to parse.
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 that modifies a real cart, the description is incomplete. It lacks information about prerequisites (e.g., authentication), the meaning of 'approved' items, the role of all parameters, and potential side effects. Although an output schema exists, the description still needs to cover these critical contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and no parameter descriptions are provided. The description explicitly explains the role of 'confirm' ('when confirm is true'), but it does not clarify the meaning or purpose of 'location_id' or 'dinner_count', leaving two of three parameters unexplained.
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: 'Add only approved, non-review items to the real Kroger cart when confirm is true.' It specifies the verb ('Add'), the resource ('approved, non-review items to the real Kroger cart'), and a condition ('when confirm is true'), which distinguishes it from sibling tools like add_single_item_to_kroger_cart and preview_shopping.
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 explicit guidance on when to use this tool versus alternatives. The condition 'when confirm is true' provides some context for execution, but the description does not mention when this tool should be preferred over add_single_item_to_kroger_cart or preview_live_shopping, nor does it state any 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 bears the full burden of behavioral disclosure. It only states that it searches locations near a zip code, but doesn't disclose what the response contains, whether results are sorted or limited, or any other behavioral traits. This is a significant transparency gap for a search 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, compact sentence that front-loads the essential information. There is no unnecessary detail or repetition, making it highly efficient and easy to parse.
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 (one optional parameter and an output schema), the description is somewhat complete for a basic location search. However, it lacks context about usage timing, relationship to sibling tools, and any limitations or special behavior. The output schema covers return values, so that omission is acceptable, but the overall guidance is thin.
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 0% description coverage, so the description must compensate. It does mention 'near a zip code', which gives meaning to the single parameter 'zip_code'. However, it doesn't elaborate on format, optionality, or the default value (though the schema shows a default). The description provides basic but sufficient context for the parameter.
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 ('Search') and resource ('locations'), naming both Kroger and King Soopers. It also indicates the search criterion (near a zip code), which distinguishes it from the sibling 'search_kroger' that likely searches other entities like products.
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 gives no explicit guidance on when to use this tool versus alternatives like 'search_kroger' or other location-related tools. There are no prerequisites, exclusions, or alternative recommendations, leaving the agent to infer usage solely from the name and minimal description.
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 that the tool checks token existence but does not explicitly note read-only behavior, potential error conditions, or prerequisites like an active session, leaving the agent to infer safety and side effects.
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 redundant or verbose language. Every word contributes to understanding, making it appropriately concise for a simple status-check 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 low complexity (zero parameters, output schema present), the description covers the core functionality adequately. However, it lacks contextual placement within the broader cart authentication workflow, such as when to call this status check relative to sibling tools like start_kroger_cart_auth or complete_kroger_cart_auth, leaving an incomplete picture for an agent navigating the process.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline is 4. The description adds meaningful context by introducing the concept of a 'local user cart token,' which is absent from the empty schema, though no parameter-specific details are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and resource ('local user cart token'), clearly distinguishing this status-check tool from sibling auth flow tools like start_kroger_cart_auth and complete_kroger_cart_auth. It directly answers what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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. It does not mention placement in the auth workflow (e.g., before starting or after completing auth) or any conditions that would trigger its use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It does reveal that the add only happens when confirm is true and that it targets the real cart, but it omits other critical behavioral details such as authentication requirements, side effects of adding to a live cart, and what happens if confirm is false.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core purpose and key condition without any unnecessary words. It is 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 tool with 4 parameters and an output schema, the description is too sparse. It does not mention the default confirm=false, which means the tool will not add by default, nor does it address prerequisites like auth. These omissions hinder an agent's ability to use the tool correctly without relying on external context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage and includes 4 parameters, but the description only clarifies 'upc' and 'confirm'. The parameters 'modality' and 'quantity' are left unexplained, leaving a significant gap in parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Add') and resource ('real Kroger cart'), and specifies 'one explicit UPC', which distinguishes it from the sibling tool for bulk-adding approved items. The meaning is unambiguous and directly conveys the tool's function.
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 a clear condition ('when confirm is true') that indicates when the tool actually performs the add operation. However, it does not explicitly reference alternative tools or state when not to use this tool, so it stops short of full usage guidance.
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 returning an authorization URL and cart write access, but does not disclose side effects like initiating an external OAuth flow, requiring user interaction, or invalidating prior auth states. This is a significant transparency gap for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the verb 'Start' and contains no filler words. Every word contributes to the meaning, 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?
For a no-parameter tool with an output schema, the description is minimally sufficient. However, it does not mention the broader OAuth flow context—e.g., that the user must visit the authorization URL and then use complete_kroger_cart_auth to finish. Given the sibling tools, adding this context would improve completeness for an AI agent.
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 schema description coverage is 100%. Per the rubric, a zero-parameter tool receives a baseline of 4. The description adds no unnecessary parameter information, which 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?
Description uses the specific verb 'Start' with the resource 'Kroger OAuth' and clearly states the purpose (cart write access) and output (authorization URL). It distinguishes from sibling tools like complete_kroger_cart_auth by indicating this is the initialization step.
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 OAuth authorization for cart write access is needed, but does not explicitly state when to use this tool versus alternatives such as complete_kroger_cart_auth or kroger_cart_auth_status. No exclusions or prerequisites are mentioned, leaving usage 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?
With no annotations, the description carries the full burden. It states the action 'Complete' but does not disclose side effects (e.g., token storage, session state changes), prerequisites, or failure behavior. The phrase 'using the full redirect URL' adds input context but no details about what happens during or after the operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 11 words, front-loading the action and providing the essential input context. Every word earns its place, with no redundancy or filler.
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?
Despite being a simple one-parameter tool with an output schema, the description omits usage prerequisites (e.g., need to start auth first) and any behavioral side effects. It is minimally adequate but leaves gaps that could confuse an agent unfamiliar with the OAuth flow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only the parameter name 'redirect_url' with no description (0% coverage). The description adds meaning by specifying it should be the 'full redirect URL from the browser,' which clarifies format and source. This meaningfully compensates for the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Complete Kroger OAuth using the full redirect URL from the browser' clearly states the specific action (complete) and resource (Kroger OAuth). It distinguishes from siblings like start_kroger_cart_auth (which initiates the flow) and kroger_cart_auth_status (which checks status), 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 when to use this tool: after the browser redirect, with the full redirect URL. It does not explicitly name alternatives or exclusions, but the context from sibling tools (start_kroger_cart_auth, kroger_cart_auth_status) and the conditional 'using the full redirect URL' provide clear guidance on the usage situation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavioral traits. It does add one meaningful safety guarantee ('without exposing secrets'), but it does not disclose whether the operation is read-only, performs network calls, or has any side effects. This is a modest but incomplete disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded with the action and resource. Every word adds value, and there is no fluff 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 tool with no parameters and a simple validation purpose, the description is nearly complete. The presence of an output schema covers return-value details, so the description's lack of output explanation is acceptable. However, it could be slightly richer in explaining how this fits into the broader Kroger auth workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and the baseline for zero-parameter tools is 4. The description correctly avoids inventing parameter details and does not contradict the schema, so the score remains at the baseline.
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 ('Validate') and resource ('local Kroger credentials'), with an additional qualifier ('without exposing secrets') that distinguishes it from sibling auth tools. This is a precise, non-tautological statement.
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 validate Kroger credentials, but it does not explicitly state when to use it versus the sibling auth-flow tools (e.g., start_kroger_cart_auth, kroger_cart_auth_status). There is no mention of alternatives or when-not-to-use, leaving the usage context implied.
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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