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odoo_demo_check

Audit Odoo contacts, employees, leads, and users to detect residual real addresses before demos. Optionally neutralize found addresses using the 'corriger' flag.

Instructions

Verifier qu'aucune adresse reelle ne subsiste avant de demontrer. Audite contacts (res.partner), salaries (hr.employee), pistes (crm.lead) et utilisateurs (res.users), au plus limit enregistrements par modele et par champ ("tronque" le signale). Avec corriger, les adresses trouvees sont neutralisees.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
corrigerNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description discloses several behavioral traits: it audits multiple models, respects a per-model/per-field limit, signals truncation, and can neutralize addresses when corriger=true. However, it omits details about what defines a 'real address', whether correction is permanent, or any permission requirements. The bar is higher without annotations, and this is only partially met.

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 two sentences, front-loads the purpose, and uses no filler. Every sentence adds meaningful information, making it 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?

The description covers the key elements: models, limit, correction option, and truncation signal. However, it leaves ambiguous what exactly constitutes a 'real address' (physical vs. email) and which specific fields are checked. Since output schema exists, return format is not penalized. The gaps are notable for a tool that is meant to audit data.

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

Parameters5/5

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

Schema coverage is 0%, but the description fully explains both parameters: 'au plus limit enregistrements par modele et par champ' defines limit, and 'Avec corriger, les adresses trouvees sont neutralisees' defines corriger. This exceeds the baseline and compensates completely for the lack of schema descriptions.

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 purpose: 'Verifier qu'aucune adresse reelle ne subsiste avant de demontrer' (verify no real address remains before demonstrating). It lists the specific models audited (res.partner, hr.employee, crm.lead, res.users), which distinguishes it from sibling Odoo tools that handle CRUD, search, or other operations.

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 phrase 'avant de demontrer' (before demonstrating) gives a clear situational context for when to use this tool. It doesn't explicitly name alternatives or exclusion conditions, but its distinct purpose relative to sibling tools implies a specific workflow niche.

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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