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odoo_update_where

Bulk update Odoo records matching a domain. Preview affected records with before/after samples, then confirm to apply and record a justification.

Instructions

Modifier en masse les enregistrements d'un domaine.

Sans confirm : ne modifie RIEN, renvoie le nombre concerne et un echantillon avant/apres. Montre-le a l'utilisateur, obtiens son accord, puis confirm=True.

motif justifie la modification dans le rapport.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
motifNo
domainYes
valuesYes
confirmNo
max_recordsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully carries the transparency burden. It discloses the most critical behavior: without `confirm`, nothing is modified, but a count and before/after sample are returned. It also explains the role of `motif` in the report. This is excellent transparency for a mutation tool.

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 concise and front-loaded with the main purpose, followed by a clear explanation of the two-step confirm workflow. Every sentence contributes meaningful information with no fluff.

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 tool's complexity and the presence of an output schema (so return values need not be described), the description covers the essential workflow and safety mechanism. Missing details like domain syntax and value format are minor, but overall the context is sufficient for correct 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 description coverage is 0%, so the description must compensate. It adds meaning for `confirm` (dry-run vs actual write) and `motif` (justification in report), but does not explain the format/expected syntax for `domain`, `values`, or the purpose of `max_records`. Parameter names are self-explanatory, but the description is incomplete.

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: 'Modifier en masse les enregistrements d'un domaine' (mass modify records of a domain). This is a specific verb+resource+scope that distinguishes it from sibling tools like odoo_write (likely single-record update) and odoo_execute.

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 explicit workflow guidance: first call without `confirm` to preview (dry-run), show results to the user, obtain consent, then call with `confirm=True`. It implies this tool is for bulk updates via the phrase 'en masse', but does not explicitly name alternatives or exclusions.

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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