# Odoo Inventory Optimizer

> Expert guide for Odoo Inventory: stock valuation (FIFO/AVCO), reordering rules, putaway strategies, routes, and multi-warehouse configuration.

- Skill: `techwavedev/odoo-inventory-optimizer` (Agent Skill)
- Install (CLI): `npx skillmds@latest add techwavedev/odoo-inventory-optimizer`
- Raw SKILL.md: https://api.skillmd.com/api/skills/techwavedev/odoo-inventory-optimizer/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: techwavedev (https://skillmd.com/u/techwavedev)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/techwavedev/odoo-inventory-optimizer

---


# Odoo Inventory Optimizer

## Overview

This skill helps you configure and optimize Odoo Inventory for accuracy, efficiency, and traceability. It covers stock valuation methods, reordering rules, putaway strategies, warehouse routes, and multi-step flows (receive → quality → store).

## When to Use This Skill

- Choosing and configuring FIFO vs AVCO stock valuation.
- Setting up minimum stock reordering rules to avoid stockouts.
- Designing a multi-step warehouse flow (2-step receipt, 3-step delivery).
- Configuring putaway rules to direct products to specific storage locations.
- Troubleshooting negative stock, incorrect valuation, or missing moves.

## How It Works

1. **Activate**: Mention `@odoo-inventory-optimizer` and describe your warehouse scenario.
2. **Configure**: Receive step-by-step configuration instructions with exact Odoo menu paths.
3. **Optimize**: Get recommendations for reordering rules and stock accuracy improvements.

## Examples

### Example 1: Enable FIFO Stock Valuation

```text
Menu: Inventory → Configuration → Settings

Enable: Storage Locations
Enable: Multi-Step Routes
Costing Method: (set per Product Category, not globally)

Menu: Inventory → Configuration → Product Categories → Edit

  Category: All / Physical Goods
  Costing Method: First In First Out (FIFO)
  Inventory Valuation: Automated
  Account Stock Valuation: [Balance Sheet inventory account]
  Account Stock Input:   [Stock Received Not Billed]
  Account Stock Output:  [Stock Delivered Not Invoiced]
```

### Example 2: Set Up a Min/Max Reordering Rule

```text
Menu: Inventory → Operations → Replenishment → New

Product: Office Paper A4
Location: WH/Stock
Min Qty: 100   (trigger reorder when stock falls below this)
Max Qty: 500   (purchase up to this quantity)
Multiple Qty: 50  (always order in multiples of 50)
Route: Buy    (triggers a Purchase Order automatically)
       or Manufacture (triggers a Manufacturing Order)
```

### Example 3: Configure Putaway Rules

```text
Menu: Inventory → Configuration → Putaway Rules → New

Purpose: Direct products from WH/Input to specific bin locations

Rules:
  Product Category: Refrigerated Goods
    → Location: WH/Stock/Cold Storage

  Product: Laptop Model X
    → Location: WH/Stock/Electronics/Shelf A

  (leave Product blank to apply the rule to an entire category)

Result: When a receipt is validated, Odoo automatically suggests
the correct destination location per product or category.
```

### Example 4: Configure 3-Step Warehouse Delivery

```text
Menu: Inventory → Configuration → Warehouses → [Your Warehouse]

Outgoing Shipments: Pick + Pack + Ship (3 steps)

Operations created automatically:
  PICK  — Move goods from storage shelf to packing area
  PACK  — Package items and print shipping label
  OUT   — Hand off to carrier / mark as shipped
```

## Best Practices

- ✅ **Do:** Use **Lots/Serial Numbers** for high-value or regulated items (medical devices, electronics).
- ✅ **Do:** Run a **physical inventory adjustment** at least quarterly (Inventory → Operations → Physical Inventory) to correct drift.
- ✅ **Do:** Set reordering rules on fast-moving items so purchase orders are generated automatically.
- ✅ **Do:** Enable **Putaway Rules** on warehouses with multiple storage zones — it eliminates manual location selection errors.
- ❌ **Don't:** Switch stock valuation method (FIFO ↔ AVCO) after recording transactions — it produces incorrect historical cost data.
- ❌ **Don't:** Use "Update Quantity" to fix stock errors — always use Inventory Adjustments to maintain a proper audit trail.
- ❌ **Don't:** Mix product categories with different costing methods in the same storage location without understanding the valuation impact.

## Limitations

- **Serial number tracking** at the individual unit level (SN per line) adds significant UI overhead; test performance with large volumes before enabling.
- Does not cover **landed costs** (import duties, freight allocation to product cost) — that requires the `stock_landed_costs` module.
- **Cross-warehouse stock transfers** have routing complexities (transit locations, intercompany invoicing) not fully covered here.
- Automated inventory valuation requires the **Accounting** module; Community Edition installations without it cannot post stock journal entries.

---

<!-- AGI-INTEGRATION-START -->

## AGI Framework Integration

> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)

### Memory-First Protocol

Retrieve prior design decisions (color palettes, typography, spacing scales) to maintain visual consistency across sessions. Cache generated design tokens.

```bash
# Check for prior frontend/design context before starting
python3 execution/memory_manager.py auto --query "design system decisions and component patterns for Odoo Inventory Optimizer"
```

### Storing Results

After completing work, store frontend/design decisions for future sessions:

```bash
python3 execution/memory_manager.py store \
  --content "Design system: adopted 8px grid, Inter font family, HSL color tokens with dark mode support" \
  --type decision --project <project> \
  --tags odoo-inventory-optimizer frontend
```

### Multi-Agent Collaboration

Share design decisions with backend agents (API contract changes) and QA agents (visual regression baselines).

```bash
python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \
  --project <project>
```

### Design Memory Persistence

Store design system tokens and component decisions in Qdrant so any agent on any platform (Claude, Gemini, Cursor) can retrieve and apply consistent styling.

<!-- AGI-INTEGRATION-END -->

