Skip to main content
Glama

Frigolog HACCP — French Food Safety Compliance

by io.github.naimterrache-a11y

get_rappels_par_categorie_etablissement

Retourne les rappels produits RappelConso actifs filtrés automatiquement par type d'établissement. Au lieu de chercher manuellement dans toutes les catégories, ce tool identifie les familles de produits pertinentes pour un type d'établissement donné (ex : un boulanger reçoit uniquement les rappels farines, oeufs, beurre, levures, fruits secs, chocolat ; un poissonnier reçoit uniquement les rappels poissons, crustacés, coquillages, produits fumés). Utilise get_rappels_produits_actifs en interne et filtre les résultats. Conçu pour l'automatisation : un agent IA peut appeler ce tool chaque matin pour vérifier si un rappel concerne son établissement.

[EN] Returns active RappelConso product recalls automatically filtered by establishment type. Instead of searching all categories, this tool identifies relevant product families for a given establishment type (e.g., a bakery only receives recalls for flour, eggs, butter, yeast, dried fruits, chocolate; a fishmonger only receives recalls for fish, shellfish, smoked products). Designed for automation: an AI agent can call this tool every morning to check if a recall affects the establishment. Required 'type_etablissement'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
type_etablissementYesType d'établissement. Valeurs : 'restaurant', 'boulangerie', 'boucherie', 'fromagerie', 'poissonnerie', 'traiteur', 'glacier', 'pizzeria', 'patisserie'. 'restaurant' et 'traiteur' surveillent toutes les catégories alimentaires.

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so description carries full burden. It discloses internal use of another tool and filtering logic, but does not cover latency, error handling, or any side effects. For a non-destructive data retrieval tool, 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately concise but has some redundancy (e.g., repeats 'Required 'type_etablissement' at end). It mixes French and English, which may confuse. Structure is logical but could be more streamlined.

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 no output schema, so the description should explain what the output contains. It only mentions returning filtered recalls but omits details on return format, fields, or pagination. This leaves some ambiguity 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?

Schema coverage is 100% for the single parameter. The description adds value by providing concrete mapping examples (bakery, fishmonger) and explaining special cases ('restaurant' and 'traiteur' monitor all categories), going beyond the enum list in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns active RappelConso recalls filtered by establishment type, using specific verbs and resource terms. It distinguishes from sibling tool get_rappels_produits_actifs by noting it internally calls that tool and filters results.

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 explains when to use this tool (instead of searching all categories) and provides examples per establishment type. It suggests automated daily use. However, it doesn't explicitly state when not to use it or mention alternative tools, though the sibling list implies alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Frigolog HACCP — French Food Safety Compliance toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is potential confusion between get_haccp_temperatures and get_temperatures_cuisson (both about temperatures, but one storage/cooling, one cooking) and between get_rappels_produits_actifs and get_rappels_par_categorie_etablissement (the latter is a filtered version of the former). Nonetheless, descriptions clarify the differences.

Naming Consistency4/5

The naming convention is almost entirely 'get_<noun>', which is consistent. The exception is 'compare_solutions_haccp' which uses 'compare_' instead of 'get_', breaking the pattern. This is a minor inconsistency.

Tool Count5/5

19 tools cover a comprehensive range of HACCP-related topics for French catering. Each tool addresses a specific need without excessive overlap, and the number is well within the ideal 3-15 range, earning a high score.

Completeness5/5

The tool set covers all major aspects of HACCP compliance in France: training, temperatures, cleaning plans, recalls, inspection risk, sanctions, allergens, DLC rules, etc. There are no obvious gaps for an informational/retrieval tool of this nature.

Resources