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deeprunnerai

Odoo MCP Server

by deeprunnerai

inventory_list_operations

List pending inventory operations like receipts, deliveries, and transfers in Odoo. Filter by operation type or state to manage stock movements.

Instructions

List pending inventory operations (receipts, deliveries, transfers)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operation_typeNoFilter by operation type
stateNoFilter by state
limitNoMaximum number of operations to return
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'pending' operations, implying a filter, but doesn't clarify what 'pending' means (e.g., all non-canceled states), whether results are paginated, sorted, or include metadata. For a list tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that front-loads the core purpose ('List pending inventory operations') and provides clarifying examples. Every word earns its place with no redundancy or unnecessary elaboration.

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?

For a list tool with 3 parameters, 100% schema coverage, and no output schema, the description is minimally adequate. It states what the tool does but lacks details on behavior (e.g., return format, pagination) and usage context. Given the complexity and absence of annotations, it should do more to be 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?

Schema description coverage is 100%, so the schema fully documents all three parameters with enums and defaults. The description adds no additional parameter semantics beyond implying 'pending' might relate to the 'state' filter, but this is vague. Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the verb ('List') and resource ('pending inventory operations') with specific examples ('receipts, deliveries, transfers'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'inventory_list_products' or 'inventory_list_warehouses', which prevents a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'inventory_create_transfer' for creating operations or 'inventory_get_stock' for stock data, nor does it specify prerequisites or contextual constraints for listing operations.

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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