Detects and investigates traffic spoofing violations in affiliate marketing to determine enforcement actions.
Detects and investigates traffic spoofing violations in affiliate marketing to determine enforcement actions.
npx skills add https://github.com/vivekhaldar/proceda --skill traffic-spoofing-detection复制此命令并粘贴到 Claude Code 中以安装该技能
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| name | traffic-spoofing-detection |
| description | Detects and investigates traffic spoofing violations in affiliate marketing to determine enforcement actions. |
| required_tools | ["InvestigateViolations","AnalyzeTrafficPatterns","ValidateReferralSources","CalculateRiskScore","GenerateEvidenceReport","ExecuteEnforcementAction"] |
| output_fields | ["enforcement_action"] |
Execute the Traffic Attribution Validation Matrix (TAVM) by calling the InvestigateViolations tool. Use the partner_id, registered_websites, and earnings_amount to cross-reference authenticity parameters and validate the unique users to total orders ratio (minimum 0.4 ratio required for legitimacy).
Analyze the traffic data for suspicious patterns using the AnalyzeTrafficPatterns tool. Input the partner_id, engagement_score, conversion_rate, and bounce_rate. Verify if the engagement score is below 1.0, if the conversion rate is below 0.05%, and if the bounce rate exceeds 90%. Document any click spikes exceeding 10x the baseline and check if device traffic distribution is skewed (>80% single device type).
Perform a source verification sequence using the ValidateReferralSources tool. Provide the partner_id, unattributed_clicks, and top_referral_source. Evaluate if unattributed clicks exceed 50% and if visit durations are suspiciously short (less than 30 seconds).
Determine the specific violation type (e.g., traffic cloaking, spoofing traffic, redirect traffic, or blank source) based on the gathered data. Use the CalculateRiskScore tool with the partner_id, violation_type, engagement_score, and conversion_rate to determine the severity of the violation.
[APPROVAL REQUIRED]
Generate a comprehensive evidence report for the Partner Violation Documentation System (PVDS) using the GenerateEvidenceReport tool. Include the partner_id, the determined violation_type, and a detailed list of evidence_collected from the previous analysis steps.
Based on the risk level and violation type, determine the final enforcement action: "Account Closure" (High risk), "Temporary Suspension" (Medium risk), "Warning Issued" (Low risk with evidence), or "No Action" (Low risk without evidence). Execute the action using the ExecuteEnforcementAction tool with the partner_id, risk_level, and violation_type.
Update the digital violation records and partner lifecycle tracking data. Provide the final enforcement action in the summary using the required XML format: <enforcement_action>value</enforcement_action>.
