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.
git clone --depth 1 https://github.com/jbwashington/ebay-mcpWrote 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/commands/jbwashington/ebay-mcp/ebay-fraud-analysis)<a href="https://agentmods.dev/commands/jbwashington/ebay-mcp/ebay-fraud-analysis"><img src="https://agentmods.dev/badge/commands/jbwashington/ebay-mcp/ebay-fraud-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/jbwashington/ebay-mcp/ebay-fraud-analysis"><img src="https://agentmods.dev/badge/commands/jbwashington/ebay-mcp/ebay-fraud-analysis.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00010 | $0.01310 |
| Opus 5 | $0.00005 | $0.00655 |
| Sonnet 5 | $0.00002 | $0.00262 |
| Haiku 4.5 | $0.00001 | $0.00131 |
Grade A, and why
ebay-fraud-analysis 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 10d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
eBay Fraud Analysis
Analyze a buyer's account to assess fraud risk, identify deadbeat bidder patterns, and help you make informed decisions about transactions.
Task
-
Get buyer information from argument
$1:- If it's a username: analyze that user directly
- If it's an order ID: extract buyer from order first
- If not provided: ask user for username or order ID
-
Use eBay MCP tools to gather buyer data:
- Get buyer account information
- Fetch feedback history (positive, neutral, negative)
- Get recent transaction history
- Check account age
- Verify shipping address if available
-
Calculate Risk Score (0-100) based on:
Account Age (30% weight):
- < 7 days: 30 points
- 7-30 days: 20 points
- 30-90 days: 10 points
- 90+ days: 0 points
Feedback Score (25% weight):
- 0 feedback: 25 points
- 1-5 feedback: 15 points
- 6-25 feedback: 5 points
- 26+ feedback: 0 points
Feedback Percentage (20% weight):
- < 95%: 20 points
- 95-97%: 10 points
- 98-99%: 5 points
- 100% (but < 10 transactions): 10 points
- 100% (10+ transactions): 0 points
Recent Negative Feedback (15% weight):
- Negative in last 30 days: 15 points
- Negative in last 90 days: 10 points
- Negative in last year: 5 points
- No negatives: 0 points
Geographic Risk (10% weight):
- International high-risk country: 10 points
- International standard risk: 5 points
- Domestic: 0 points
-
Identify Red Flags:
- ⚠️ Zero or minimal feedback (< 5)
- ⚠️ Account age < 30 days
- ⚠️ Negative feedback as buyer
- ⚠️ Unpaid item cases in history
- ⚠️ International shipping to high-risk countries
- ⚠️ Multiple recent negative feedbacks
- ⚠️ Suspicious bidding patterns
- ⚠️ Private feedback settings
-
Generate Risk Assessment:
- Risk Score: X/100
- Risk Level: Low (0-25) | Medium (26-50) | High (51-75) | Critical (76-100)
- Red Flags: List all identified issues
- Account Summary: Age, feedback, history
- Recommendation: Accept | Caution | Require Payment | Cancel
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.
- 10d ago First seen · 174 lines · 10 tokens per session scan A c6278a2d1fb3
ebay-fraud-analysis is a command published in the GitHub repository jbwashington/ebay-mcp (14 stars, last pushed 6mo ago), licensed MIT. It adds 10 tokens to every session and 1,310 once invoked, about $0.0001 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 2026-08-30.
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