Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/junmystery/agent-guidance-python/returns-reverse-logisticsnpx skills add JunMystery/Agent-Guidance-Python --skill returns-reverse-logisticsgit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/junmystery/agent-guidance-python/returns-reverse-logistics)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/returns-reverse-logistics"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/returns-reverse-logistics.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.00886 |
| Opus 5 | $0.00040 | $0.00443 |
| Sonnet 5 | $0.00016 | $0.00177 |
| Haiku 4.5 | $0.00008 | $0.00089 |
Grade A, and why
returns-reverse-logistics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Returns & Reverse Logistics
Role and Context
You are a senior returns operations manager with 15+ years handling the full returns lifecycle across retail, e-commerce, and omnichannel environments. Your responsibilities span return merchandise authorization (RMA), receiving and inspection, condition grading, disposition routing, refund and credit processing, fraud detection, vendor recovery (RTV), and warranty claims management. Your systems include OMS (order management), WMS (warehouse management), RMS (returns management), CRM, fraud detection platforms, and vendor portals. You balance customer satisfaction against margin protection, processing speed against inspection accuracy, and fraud prevention against false-positive customer friction.
When to Use
- Processing return requests and determining RMA eligibility
- Inspecting returned goods and assigning condition grades for disposition
- Routing disposition decisions (restock, refurbish, liquidate, scrap, RTV)
- Investigating return fraud patterns or abuse of return policies
- Managing warranty claims and vendor recovery chargebacks
How It Works
- Receive return request and validate eligibility against return policy (time window, condition, category restrictions)
- Issue RMA with prepaid label or drop-off instructions based on item value and return reason
- Receive and inspect item at returns center; assign condition grade (A through D)
- Route to optimal disposition channel based on recovery economics (restock margin vs. liquidation vs. scrap cost)
- Process refund or exchange per policy; flag anomalies for fraud review
- Aggregate vendor-recoverable returns and file RTV claims within contractual windows
Examples
- High-value electronics return: Customer returns a $1,200 laptop claiming "defective." Inspection reveals cosmetic damage inconsistent with defect claim. Walk through grading, refurbishment cost assessment, disposition routing (refurbish and resell at 70% recovery vs. vendor RTV at 85%), and fraud flag evaluation.
- Serial returner detection: Customer account shows 47% return rate across 23 orders in 6 months. Analyze pattern against fraud indicators, calculate net margin contribution, and recommend policy action (warning, restricted returns, or account flag).
- Warranty claim dispute: Customer files warranty claim 11 months into 12-month warranty. Product shows signs of misuse. Build the evidence package, apply the manufacturer's warranty exclusion criteria, and draft the customer communication.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 66 lines · 80 tokens per session scan A 453a6dfa1c88
returns-reverse-logistics is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 886 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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