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search_records

Read-onlyIdempotent

Search for records in Odoo 19 models using flexible domain filters, specify return fields, and control pagination with sorting options.

Instructions

Search for records in an Odoo model.

Args: model: Model name (e.g., 'res.partner') domain: Odoo search domain (list of conditions). Examples: - Simple: [["name", "=", "John"]] - Multiple (AND): [["is_company", "=", True], ["active", "=", True]] - OR condition: ["|", ["name", "ilike", "test"], ["email", "ilike", "test"]] - any (Odoo 19+): [["order_line", "any", [["product_uom_qty", ">", 5]]]] - Operators: =, !=, >, >=, <, <=, like, ilike, in, not in, child_of, any fields: Fields to return (None = auto-exclude dangerous fields like binary/image/html) limit: Maximum number of records offset: Number of records to skip order: Sort order (e.g., 'name asc', 'create_date desc')

Returns: JSON with records, total count, limit, and offset. Each record includes a '_url' field for direct browser access.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
domainNo
fieldsNo
limitNo
offsetNo
orderNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

While annotations declare readOnlyHint and idempotentHint, the description adds valuable behavioral context: auto-exclusion of dangerous fields (binary/image/html) when fields is null, the inclusion of '_url' fields in results, and pagination metadata (total count) in returns. It does not contradict annotations.

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?

Uses structured docstring format (Args/Returns) with zero waste. Every element serves a purpose: the domain examples are essential given Odoo's complex syntax, and the Returns section clarifies output structure despite the existence of an output schema.

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 6 parameters with 0% schema coverage, the description provides complete guidance for an AI agent to invoke the tool correctly. It covers parameter semantics, return structure, pagination behavior (limit/offset/total), and safety features (dangerous field exclusion).

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?

With 0% schema description coverage, the description carries the full burden of parameter documentation. It comprehensively defines all 6 parameters, providing extensive examples for the complex 'domain' parameter (AND/OR operators, Odoo 19+ 'any' syntax) and clear syntax guidance for 'order'. This fully compensates for the schema deficiency.

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 opens with a specific verb ('Search') and clear resource ('records in an Odoo model'), distinguishing it from siblings like read_records (ID-based retrieval), count_records (aggregation), and mutation tools. The scope is precisely defined.

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 through extensive domain examples showing complex filtering capabilities, implying when to use this tool (conditional queries). However, it does not explicitly name sibling alternatives like 'Use count_records if you only need totals' or contrast with read_records for ID-based lookups.

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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