Returns Authorization Processor
SkillDev toolsAutomated return authorization and routing skill optimizing return paths and customer experience
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Returns Authorization Processor skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/business/logistics/skills/returns-authorization-processor/SKILL.md and read by ahel’s review.
Overview
The Returns Authorization Processor automates return authorization and routing decisions to optimize return paths and enhance customer experience. It validates return eligibility, selects optimal return methods, and detects potential fraud while maintaining customer satisfaction.
Capabilities
- Return Eligibility Validation: Verify return eligibility based on policy rules, purchase date, and product condition
- Return Reason Classification: Categorize and analyze return reasons for trend identification
- Return Method Selection: Recommend optimal return method (carrier pickup, store drop-off, scheduled pickup)
- Label Generation Automation: Automatically generate return shipping labels with appropriate routing
- Return Tracking Provision: Provide return tracking capabilities from initiation to processing
- Refund Timing Estimation: Estimate and communicate expected refund processing timelines
- Fraud Detection Screening: Screen returns for fraud indicators and flag suspicious patterns
Tools and Libraries
- OMS APIs
- Return Label Generation Services
- Fraud Detection Tools
- Customer Communication Platforms
Used By Processes
- Reverse Logistics Management
- Returns Processing and Disposition
- Warranty Claims Processing
Usage
skill: returns-authorization-processor
inputs:
return_request:
order_id: "ORD-2026-12345"
customer_id: "CUST-98765"
items:
- sku: "SKU001"
quantity: 1
reason_code: "defective"
description: "Product stopped working after 2 weeks"
original_purchase_date: "2026-01-05"
original_amount: 149.99
customer_profile:
return_history:
returns_last_12_months: 2
return_rate_percent: 8
customer_tier: "gold"
return_policy:
return_window_days: 30
condition_requirements: ["original_packaging", "all_accessories"]
free_return_threshold: 50.00
outputs:
authorization:
rma_number: "RMA-2026-54321"
status: "approved"
eligibility:
within_return_window: true
policy_compliant: true
fraud_risk: "low"
return_method:
recommended_method: "carrier_pickup"
carrier: "UPS"
pickup_date_options: ["2026-01-26", "2026-01-27", "2026-01-28"]
label_url: "https://returns.example.com/label/RMA-2026-54321"
return_location: "Returns Center - Columbus, OH"
refund_estimate:
refund_amount: 149.99
refund_method: "original_payment"
estimated_processing_days: 5
estimated_refund_date: "2026-02-03"
customer_communication:
confirmation_email_sent: true
tracking_url: "https://returns.example.com/track/RMA-2026-54321"
fraud_analysis:
risk_score: 15
risk_level: "low"
flags: []
Integration Points
- Order Management Systems (OMS)
- Customer Service Platforms
- Carrier Integration (label generation)
- Fraud Detection Systems
- Refund Processing Systems
Performance Metrics
- Return authorization time
- Customer satisfaction (CSAT)
- Fraud detection rate
- Return processing cycle time
- Return rate by reason
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
returns-authorization-processor- Source
- github.com/a5c-ai/babysitter
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