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deeprunnerai

Odoo MCP Server

by deeprunnerai

manufacturing_create_order

Create manufacturing orders in Odoo ERP by specifying product, quantity, and schedule to initiate production workflows.

Instructions

Create a new manufacturing order

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYesProduct ID to manufacture
quantityYesQuantity to produce
bom_idNoBill of Materials ID (optional, uses default if not specified)
scheduled_dateNoScheduled start date (YYYY-MM-DD)
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Create a new manufacturing order' implies a write operation but doesn't address permissions, side effects, error conditions, or what happens upon success. For a mutation tool with zero annotation coverage, this leaves critical behavioral aspects unspecified.

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 directly states the tool's purpose without unnecessary words. It's appropriately front-loaded and wastes no space on redundant information.

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

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a creation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what a 'manufacturing order' entails in this system, what happens after creation, or how it differs from other order types. Given the complexity implied by 4 parameters and mutation nature, more context is needed.

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 all parameters are documented in the schema itself. The description adds no additional parameter context beyond what's in the schema (e.g., no examples, format clarifications, or business rules). This meets the baseline for high schema coverage.

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 action ('Create') and resource ('manufacturing order'), making the purpose immediately understandable. However, it doesn't differentiate this tool from similar creation tools like 'sales_create_order' or 'purchase_create_order', which would require mentioning it's specifically for manufacturing workflows.

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. With sibling tools like 'manufacturing_list_orders' and 'sales_create_order', there's no indication of prerequisites, appropriate contexts, or distinctions between manufacturing and other order types.

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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