frigolog-haccp-mcp

get_haccp_temperatures

Renvoie les températures réglementaires françaises de conservation, refroidissement et service des denrées alimentaires par catégorie de produit, conformément à l'arrêté du 21 décembre 2009, au règlement (CE) n° 852/2004 et au règlement (CE) n° 853/2004 (denrées d'origine animale). Couvre viandes, poisson, produits laitiers, œufs, fruits et légumes, plats cuisinés, pâtisseries, surgelés, glaces, températures de service chaud et de refroidissement rapide.

[EN] Returns French regulatory food temperatures (storage, cooling, serving) by product category, per the arrêté of 21 Dec 2009 and Regulations (EC) 852/2004 & 853/2004. Optional 'categorie' filter.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`categorie`	No	Filtre optionnel par catégorie. Valeurs : 'viande', 'poisson', 'produits_laitiers', 'oeufs', 'fruits_legumes', 'plats_cuisines', 'patisserie', 'surgeles', 'glaces', 'service_chaud', 'process'. Si absent, renvoie toutes les catégories.

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the legal basis and covered categories, implying a read-only lookup. However, it does not mention output format, potential errors, authentication needs, or whether the data is static. The description is transparent about what it returns but lacks deeper behavioral context.

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 bilingual and somewhat verbose, but each sentence carries useful information: purpose, legal references, category coverage, and optional filter. It is front-loaded with the main purpose and remains efficient despite the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description could clarify what fields are returned per category (e.g., multiple temperature types, units). It mentions categories and temperature types but not the exact output structure. Given the simple tool nature and rich sibling context, it is adequate but not fully complete.

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

Parameters3/5

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

The schema covers 100% of the parameters, with a full description of the 'categorie' parameter and its allowed values. The description adds regulatory context but does not go beyond the schema in explaining parameter semantics. Baseline 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool returns French regulatory food temperatures for storage, cooling, and service by product category. It uses a specific verb ("Renvoie") and resource, and distinguishes from sibling tools like get_temperatures_cuisson by focusing on non-cooking temperatures.

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

Usage Guidelines3/5

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

Usage context is implied through the scope description (regulatory storage/cooling/service temperatures), but there is no explicit comparison to alternatives or when-not-to-use conditions. The sibling tool get_temperatures_cuisson is not mentioned, so the agent lacks explicit guidance for choosing between them.

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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