Open Food Facts MCP Server

Server Quality Checklist

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Latest release: v1.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: search tools differ by scope (general, brand, category, advanced filters), nutritional/environmental checks are separate, AI insight tools are well-differentiated (questions vs. insights, per-product vs. random), and price tools cover different query patterns. No two tools are easily confused.
Naming Consistency5/5
All tool names follow a consistent camelCase verb-noun pattern (e.g., 'searchByBrand', 'getEcoScore', 'analyzeProduct'). The verbs vary logically by action, and there is no mixing of naming conventions like snake_case or underscores.
Tool Count4/5
With 21 tools, the set is slightly larger than typical but still well-scoped. Each tool covers a specific feature of the Open Food Facts database (search, nutrition, environment, allergens, AI insights, prices, recipes) without significant overlap or redundancy.
Completeness4/5
For a read-only query server, the tool set is comprehensive: it covers product lookup, multiple search dimensions, nutritional and environmental ratings, allergen checking, AI-driven insights, and pricing data. Missing write operations (create/update/delete) are outside the apparent scope, so only minor gaps exist (e.g., no direct list of all categories or brands, but autocomplete covers that).
Average 3/5 across 21 of 21 tools scored. Lowest: 1.8/5.
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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as whether the tool is read-only, requires authentication, or has rate limits. For an AI analysis tool, this is a significant omission.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), but it is under-specified. Conciseness should not come at the cost of missing essential information. The description fails to earn its place by not providing enough guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and the presence of many sibling tools, the description is woefully incomplete. It does not describe what the analysis returns, how to format the input, or when this tool is appropriate.
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 single parameter nameOrBarcode has no description coverage in the schema (0%). The tool description does not explain its format, examples, or constraints. The parameter semantics are entirely missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it provides 'AI nutritional analysis of a product', which is a specific purpose. However, it does not distinguish this from sibling tools like getNutriScore, which also provide nutritional assessments. The purpose is clear but lacks unique differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use analyzeProduct vs. siblings like getNutriScore, getAllergenCheck, or searchProducts. There is no guidance on prerequisites or limitations.
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 behavioral disclosure burden. It only says 'using AI' without explaining the process, output format, or any side effects, leaving significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence), which is under-specified for a tool with two parameters. It sacrifices helpfulness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description fails to provide essential context. It does not describe return value, error behavior, or how the AI comparison works, making it insufficient for correct usage.
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 adds no information about the parameters 'nameOrBarcode1' and 'nameOrBarcode2'. The agent receives no guidance on input format, accepted values, or meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'compare' and resource 'two products' using AI. It distinguishes from siblings like analyzeProduct or getProductByBarcode by being the only comparison tool. However, it lacks specifics on what aspects are compared.
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 on when to use this tool versus alternatives. The description does not provide context for when comparison is preferred over analysis or other operations.
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 full burden. It indicates a read operation but does not disclose pagination, data limits, sorting, or whether results are from community submissions. Minimal behavioral context is added.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks structure. It front-loads the purpose but omits important details, making it under-informative.
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?
The description does not explain what 'recent' means, the return format, or the scope of data. Sibling tools hint at more specific price tools, but this tool's context is left incomplete.
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 description does not mention the 'page' or 'pageSize' parameters. Schema description coverage is 0%, so the agent gets no additional meaning beyond the schema defaults. This is a significant gap.
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', the resource 'price data', and qualifies it as 'most recently added' and 'from the community'. This distinguishes it from sibling tools like 'getProductPrices' which may target specific 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?
No guidance is provided on when to use this tool versus alternatives like 'searchPrices' or 'getProductPrices'. There is no mention of use cases, prerequisites, or scope of data.
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 should disclose behavioral traits. It only states the search action but omits details like pagination, sorting, or authentication requirements.
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?
A single, well-structured sentence that is front-loaded. However, it could be slightly more informative without adding length.
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 3 parameters, many sibling tools, no output schema, and no annotations, the description is too minimal. It lacks details on return format, pagination behavior, and when to prefer this over alternatives.
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 coverage is 0%, so the description must compensate. It mentions searchable attributes but does not explain that 'query' should contain name/brand/category, nor does it detail 'page' and 'pageSize' beyond defaults.
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 explicitly states the tool searches products by name, brand, or category. It uses a clear verb and resource, but does not differentiate from sibling tools like searchByBrand or searchByCategory.
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 on when to use this tool vs siblings such as advancedSearch or searchByBrand. The description lacks context about appropriate use cases or exclusions.
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, and the description does not disclose how the AI suggestion works, data sources, or limitations. Very minimal transparency.
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 redundancy. However, it is too brief to be fully informative.
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 one required parameter, no output schema, and no annotations, the description is insufficient. It does not explain return format, error handling, or behavior beyond the basic action.
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 the description only says 'using a product' without clarifying that nameOrBarcode can be a product name or barcode. Does not compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get AI recipe suggestions') and the input ('using a product'). It is specific but does not differentiate from similar tools like getProductAIQuestions.
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 on when to use this tool compared to siblings such as getProductAIQuestions or searchByCategory. The agent must infer usage from the name.
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 provided, and description only lists filters. It does not disclose important behavioral traits such as read-only nature, rate limits, authentication needs, or pagination behavior beyond what is in the schema.
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?
Extremely concise single sentence, front-loaded with purpose. No unnecessary words, but could be slightly more structured with bullet points for readability.
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 12 parameters, no output schema, and no annotations, the description is insufficient. It omits pagination, sorting, and result format, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75%, so most parameters are already described. Description lists several filter parameters but adds no new meaning beyond repeating names. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Advanced product search' and lists multiple filter categories, distinguishing it from single-filter siblings like searchByBrand or searchByCategory. However, 'advanced' is somewhat vague; could be more specific about combining filters.
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 on when to use this tool vs. alternatives. It does not mention when to prefer this over simpler searches or provide exclusions.
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 should disclose all behavioral traits. It only states what the tool does, but omits what happens if the product is not found, if the Eco-Score is unavailable, or any side effects. As a simple read tool, more transparency on edge cases is needed.
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 that conveys the essential function. It is concise, but could be slightly improved by front-loading the rating scale or type of product.
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 simplicity of the tool (one parameter, no output schema, no nested objects), the description is minimally adequate. However, it lacks details on return format and error behavior, which could be necessary for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a description for the single parameter. The tool description adds no additional meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets the Eco-Score rating (A-E) for a product. It specifies the rating scale and environmental context, which is distinct from siblings like getNutriScore. However, it does not explicitly differentiate itself from other similar tools.
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 getNutriScore, nor are there any prerequisites or exclusions mentioned. The agent has no context to decide if Eco-Score is appropriate for the scenario.
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 full burden for behavioral disclosure. It only lists what the tool does (retrieve insights) without addressing how it behaves (e.g., real-time vs cached, pagination, error handling, or scope like barcode validity). This is minimal transparency.
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 that efficiently conveys the core purpose. No wasted words, though it could include more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters, no output schema, many siblings), the description is insufficient. It does not specify the return format, pagination behavior, or how to use the insight types, leaving the agent with gaps for effective 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?
Schema coverage is 100%, so the schema documents all parameters. The description adds no additional meaning beyond the schema examples; it mentions some insight types but does not explain parameter semantics or constraints beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves AI-generated insights about products, listing examples like labels, categories, and ingredients. However, it does not explicitly distinguish this tool from siblings like 'analyzeProduct' or 'getInsightTypes'.
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 guidelines are provided. The description does not indicate when to use this tool over alternatives, nor does it specify any prerequisites or 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description fails to disclose behavioral traits such as pagination, limits, or side effects. For a search tool, it is excessively minimal.
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?
Single sentence is concise and front-loaded, but could be more structured to include key details like pagination behavior.
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 no annotations, no output schema, and low parameter description coverage, the description is incomplete. It does not mention output format or pagination details.
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 33%, with only 'brand' having a description. The description does not explain 'page' or 'pageSize' beyond what the schema provides, failing to compensate for low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Find all products from a specific brand', using a specific verb and resource. It distinguishes from sibling tools like searchByCategory and searchProducts.
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 on when to use this tool versus alternatives. The sibling list includes many similar search tools, but the description lacks context or exclusions.
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 provided, so description must disclose behavior. It does not mention pagination, ordering (though orderBy param exists), rate limits, or that it returns a list. The brief description leaves agents uninformed about key behaviors.
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?
Single sentence is concise and front-loaded. However, the sentence structure could be improved by separating key filters from additional details.
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 no output schema, no annotations, and 6 parameters (3 filterable), the description is too sparse. It does not explain return format, error handling, or default behavior (e.g., if no filters are provided). Incomplete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67% (4 of 6 params have descriptions). Description adds value by listing example filters (barcode, currency) but does not fully explain all parameters like page and pageSize beyond defaults. Adequate but not excellent.
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?
Description specifies verb 'Search' and resource 'crowd-sourced price data' with example filters (barcode, currency). Clearly distinguishes from siblings like getProductPrices or getRecentPrices, which are more specific. Could be more explicit about the scope (e.g., 'all prices' vs 'filtered results').
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 on when to use searchPrices vs siblings like advancedSearch, getProductPrices, or getRecentPrices. The description lacks context for choosing this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It fails to mention whether the tool is read-only, has rate limits, or how it handles partial matches. Basic behavioral traits are absent.
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 wasted words. It efficiently conveys the tool's purpose and scope.
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 absence of an output schema, the description should clarify the return format (e.g., array of suggestions). It does not, leaving ambiguity about what the agent will receive. For a simple autocomplete, this is acceptable but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are fully documented in the input schema. The description adds minimal value by listing the taxonomy types, but the schema already defines them via enum. The description does not provide additional meaning beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides autocomplete suggestions for multiple taxonomy types. It uses a specific verb ('Get autocomplete suggestions') and lists the resource types. However, it does not explicitly distinguish from sibling tools like 'searchByCategory' or 'searchByBrand', which might be confused with autocomplete.
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 versus alternatives such as 'searchProducts' or 'advancedSearch'. The description only states what it does, leaving the agent to infer usage context.
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, description must fully disclose behavior. It only states 'check if contains allergen' without clarifying return format (e.g., boolean), accuracy, error handling, or scope (e.g., based on ingredient list only).
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?
Single sentence, no redundant words, front-loaded with key information. Maximum efficiency.
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?
No output schema, so description should explain return values (e.g., boolean, allergen status). It omits this, and also lacks error handling info or performance notes. Incomplete for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described. The description adds example allergen values, slightly extending the schema. Baseline is 3 due to high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'check' and the resource 'product allergen', listing common allergens. It effectively distinguishes from siblings like checkMultipleAllergens by indicating single allergen checking.
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 on when to use this tool vs alternatives (e.g., checkMultipleAllergens for multiple checks, or searchProducts for general lookup). Missing context on prerequisites or exclusions.
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 exist, so description must fully disclose behavior. It does not mention side effects, permissions, or whether the operation is read-only. The examples hint at the type of questions but not the response structure.
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?
Single sentence with examples, no redundant words. Front-loaded with action and context.
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 no output schema and no annotations, the description lacks details like return format, number of questions, or any pagination. It leaves the agent guessing about the response.
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?
Only one parameter 'barcode' with full schema description. The tool description adds examples of questions, which gives context to the output but not the parameter itself. Schema coverage is 100%, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool gets AI-generated questions about a product needing verification, with examples. It implies specificity to a product via barcode, partially distinguishing from sibling getRandomAIQuestions.
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?
No explicit when-to-use or when-not-to-use guidance, but the purpose and input parameter implicitly suggest usage for a specific product barcode. No comparison with sibling tools.
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 full burden. It only states the data is crowd-sourced but fails to disclose behavioral traits such as read-only nature, rate limits, data freshness, or return format. This is insufficient for an agent to understand tool behavior.
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 14 words, no wasted text, and front-loads the action. It is appropriately concise, though additional structure (e.g., stating the output format) could enhance clarity without harming conciseness.
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 has 3 parameters (including pagination) and no output schema or annotations, the description is incomplete. It fails to explain pagination, output structure, or any constraints. A complete description would mention pagination details and return data format.
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 33% (only barcode described). The description does not add any meaning for page or pageSize parameters, which are left undocumented. The description should explain that page and pageSize control pagination, but it does not.
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 'crowd-sourced price data for a specific product', and adds a benefit 'see where it costs less'. This effectively communicates the tool's purpose and distinguishes it from siblings like getProductByBarcode and searchPrices.
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 use for a specific product via barcode, but does not explicitly state when to use this tool versus alternatives like searchPrices or getRecentPrices. No exclusions or alternative tool names are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It accurately indicates a read operation but does not disclose any behavioral traits such as pagination behavior, result format, or potential errors. The description is minimally adequate for a straightforward 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.
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 efficiently conveys the core purpose, though it could be expanded slightly without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and low schema coverage, the description is incomplete. It omits information about pagination, result count, and how results relate to siblings. For a simple tool this is borderline, but missing pagination details is a notable gap.
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 coverage is low (33%): only the 'category' parameter has a description in the schema, which the description reinforces with examples. However, 'page' and 'pageSize' lack any description in the schema or the tool description, leaving their semantics unclear.
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 'search' and the resource 'products within a specific food category', with concrete examples like beverages, snacks, etc. This distinguishes it from sibling tools such as searchByBrand or searchProducts, which serve different filtering purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like searchProducts or advancedSearch. There is no mention of prerequisites, limitations, or cases where this tool is not appropriate.
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 must convey behavioral traits. It states the tool 'checks' but does not explicitly confirm it is read-only, nor does it mention what happens on missing products, empty allergen lists, or error conditions. The behavior is implied but insufficiently detailed.
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 unnecessary words. It efficiently communicates the core function without 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?
The tool has low complexity (2 required params, no output schema). The description covers the basic purpose but omits output details (e.g., boolean vs. list) and error handling. For a simple tool, it is minimally adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds little beyond the schema. It reinforces the 'multiple at once' aspect but does not clarify parameter format or constraints not already in the schema. Baseline of 3 is appropriate given full schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the function: 'Check if a product contains any of multiple allergens at once.' It uses a specific verb (check) and resource (product allergens) and explicitly distinguishes from single-allergen checks by mentioning 'multiple allergens at once', differentiating it from siblings like getAllergenCheck.
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 (e.g., getAllergenCheck for single allergen, getAdditivesInfo). The description lacks context on prerequisites, limitations, or exclusions, leaving the agent to infer usage independently.
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 must disclose behavioral traits. It only states 'get product details' but does not explain behavior on invalid barcodes, rate limits, data freshness, or whether partial results are possible. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no filler. Every word is necessary and directly conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description lacks information about what product details are returned and how errors are handled. The brevity leaves gaps in completeness.
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 should add meaning for the 'barcode' parameter. It mentions 'barcode (EAN/UPC)' but provides no format, examples, or constraints beyond the schema. The description adds little 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?
Description clearly states the action ('Get product details') and the resource ('by barcode (EAN/UPC)'). It distinguishes from siblings like searchByBrand or advancedSearch by specifying barcode lookup as the unique identifier.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a barcode is available, but provides no explicit guidance on when to use this tool versus alternatives like searchProducts or analyzeProduct. 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description alone must convey behavioral traits. It states this is a read operation returning a summary, but does not explain what the summary contains (e.g., names, counts, descriptions) or any 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 extraneous information. It efficiently conveys the tool's purpose.
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 zero-parameter tool with no output schema, the description is somewhat incomplete as it does not define what 'summary' entails. However, it covers the basic operation adequately.
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?
There are no parameters, so the description provides more meaning than the empty schema. It clarifies the tool returns a summary of insight types, which is sufficient context for parameter-free invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a summary of AI insight types, using a specific verb and resource. It differentiates from siblings like getProductInsights (which gets insights for a product) and analyzeProduct.
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 versus alternatives. There is no mention of prerequisites, when-not to use, or contrast with other tools like getProductInsights or getRandomAIQuestions.
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 must disclose behavioral traits. It reveals that questions are random and AI-generated, and that human verification is needed. However, it does not mention whether the operation is read-only, any authentication requirements, or rate 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 a single sentence with 14 words, conveying the core purpose efficiently. It is front-loaded with key information, making it easy for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no required parameters, no output schema), the description is adequate but leaves gaps: it does not describe the return format, error handling, or pagination behavior (though the count parameter implies a limit). It lacks completeness for a fully self-contained description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all four parameters. The description adds no additional parameter semantics beyond what is already in the schema, such as default values or enumeration constraints.
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', the resource 'random AI-generated questions from Robotoff', and the purpose 'need human verification'. It distinguishes from sibling tools like getProductAIQuestions by specifying randomness and community contribution.
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 mentions 'great for community contribution' which implies a use case but provides no explicit guidance on when to use this tool versus alternatives like getProductAIQuestions or getInsightTypes. No exclusions or contextual conditions are stated.
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 present, so the description must convey behavioral traits. It describes a read operation but does not specify side effects, error conditions, or whether the result is always an array. The description is adequate but minimal.
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. Every part contributes to understanding the tool's function.
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 tool with one parameter and no output schema, the description covers the main purpose and hints at the return fields (E-numbers, NOVA level). It could mention error handling or format, but it's mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter. The description adds no extra meaning beyond the schema description 'Product name or barcode (EAN/UPC)'. 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 clearly states the action ('list all additives'), the resource ('in a product'), and the specific information returned ('E-numbers and NOVA processing level'). This distinguishes it from sibling tools like getProductByBarcode or analyzeProduct.
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, what constitutes a valid input, or how to handle errors (e.g., product not found).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that the tool returns a single grade (A-E), but does not mention behavior on invalid inputs, rate limits, or whether it makes external calls. For a simple read operation, this is adequate but not thorough.
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 front-loads the core action and result. No redundant words, every part serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and no output schema, the description hints at the return format (A-E grade). It covers input and output adequately, though it could mention error handling or additional details for 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 input schema has one parameter with a clear description. Since schema coverage is 100%, the description adds no extra meaning beyond what's already provided in the schema. Baseline score 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 specific resource 'Nutri-Score grade (A-E)', indicating a quick health assessment. It distinguishes itself from sibling tools like getEcoScore by specifying it's for health, not environmental impact.
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 does not provide any guidance on when to use this tool versus alternatives, such as analyzeProduct for detailed nutritional info or getEcoScore for environmental rating. No when-not or exclusion criteria are given.
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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