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singleflo

io.github.singleflo/odoo-assistant

by singleflo

required_fields

Check which fields Odoo requires before creating a record, including defaults and live usage, to avoid silent misrouting of new records.

Instructions

List the fields Odoo demands before it will accept a create, with the default it would apply and how existing records actually use it.

Ask this BEFORE create_record on a model you have not written to in this session. The answer is read from the live instance — fields_get plus default_get — never from a table in this file, so a model customised in-house reports its own requirements.

The dangerous required field is the one that already carries a default: the create succeeds without you naming it and the record lands wherever the default points, with no error to notice. crm.lead.type is the standing example — Odoo defaults it to 'lead', and on an instance that works its pipeline as opportunities that record goes straight to a menu nobody opens. That is why the live distribution is printed beside each default.

Args: model: Odoo model, e.g. "crm.lead".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses behavior: it reads from live instance via fields_get/default_get, not from a table. Warns about hidden side effects of defaults. Transparent about data source and output content.

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 relatively long but well-structured: purpose first, then usage, then warning example, then parameter. Every sentence adds value, though some could be tightened slightly without losing context.

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

Completeness5/5

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, the description covers purpose, usage, behavioral details, and parameter. No critical gaps remain; it provides sufficient context for an agent to use it correctly.

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 0% (no parameter description in schema). The description compensates by explaining the 'model' parameter with an example ('crm.lead') and context about Odoo models, adding meaning beyond the raw 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 lists required fields for a create operation, including defaults and usage distribution. It uses specific verbs ('List', 'demands') and distinguishes itself from siblings like create_record by emphasizing it as a pre-check.

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

Usage Guidelines5/5

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

Explicitly instructs to ask this tool BEFORE create_record for unfamiliar models. Explains the rationale with a concrete example of dangerous defaults, providing clear when-to-use guidance.

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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