frigolog-haccp-mcp

get_regles_dlc

Renvoie les règles de DLC (Date Limite de Consommation) pour les préparations maison en restauration et métiers de bouche en France, conformément au Guide des Bonnes Pratiques d'Hygiène en Restauration de la DGAL. Couvre viandes cuites/crues, salades composées, sandwiches, pâtisseries à la crème, sauces (émulsionnées et cuites), soupes, plats cuisinés, sous-vide cuisson basse température, produits décongelés, produits entamés. Pour chaque préparation : DLC en jours, température de conservation requise, source réglementaire.

[EN] Returns use-by-date (DLC) rules for in-house preparations in French restaurants and food trades, per the DGAL good-hygiene-practice guide. Optional 'type_preparation' keyword.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`type_preparation`	No	Filtre optionnel par type de préparation. Recherche par mot-clé dans le nom (ex: 'viande', 'salade', 'sauce', 'pâtisserie', 'soupe', 'sous-vide'). Si absent, renvoie toutes les catégories.

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are provided, so the description must carry behavioral disclosure. It does state the output fields (DLC in days, required storage temperature, regulatory source) and lists covered preparation types. However, it omits details about behavior on empty searches, matching logic, or potential variations in output formatting.

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 front-loaded with the main purpose and well-organized. It is somewhat longer than necessary due to the bilingual (FR/EN) repetition, but each sentence contributes useful detail about scope, categories, and output structure.

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 read-only tool with one optional parameter and no output schema, the description covers the essential aspects: purpose, scope, regulatory basis, covered categories, and return fields. It could strengthen completeness by referencing sibling tools for different use cases, but the tool is adequately specified on its own.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% coverage of the single optional parameter 'type_preparation', including examples and default behavior. The description only repeats the parameter's existence and examples, adding no new semantic meaning beyond what the schema already specifies.

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 ('Renvoie' / 'Returns') and a clear resource ('règles de DLC pour les préparations maison'). It specifies the geographic and regulatory scope (France, DGAL guide) and enumerates covered categories, distinguishing it from sibling tools like get_temperatures_cuisson or get_seuils_microbiologiques.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: when needing DLC rules for in-house preparations in French restaurants. It does not explicitly mention alternatives or exclusions, but the scope is well-defined and implicitly differentiates from temperature or allergen tools.

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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TDQS

A3.9/5.0

Disambiguation4/5

Most tools have a clearly distinct purpose, but there are a few potentially confusable pairs: get_haccp_temperatures vs get_temperatures_cuisson, get_score_alimconfiance vs get_alimconfiance_etablissement, and get_rappels_produits_actifs vs get_rappels_par_categorie_etablissement. The descriptions explicitly cross-reference these, reducing ambiguity, but an agent could still misselect without careful reading.

Naming Consistency4/5

18 of 19 tools follow the consistent 'get_' + noun pattern (e.g., get_actions_correctives, get_seuils_microbiologiques). The lone exception is 'compare_solutions_haccp', which uses a different verb but still follows a verb_noun structure. This minor deviation keeps the set mostly predictable.

Tool Count3/5

With 19 tools, the count sits in the borderline-heavy range (16-25). The breadth is justified for a comprehensive HACCP regulatory assistant, but some tools like compare_solutions_haccp feel peripheral to the core compliance theme, making the set feel slightly overstuffed.

Completeness4/5

The set covers the HACCP domain extensively: temperatures, cooking, DLC, allergens, recalls, cleaning plans, checklists, corrective actions, DDPP documents, sanctions, training, and Alim'confiance. Minor gaps exist, such as no tool for generating a full HACCP plan document or tracking ongoing temperature logs, but for an informational/regulatory lookup server, coverage is strong.

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