Skill UI

Python CLI trio for multi-touch attribution, funnel conversion diagnostics, and ROI/ROAS/CPA benchmarking to optimize marketing campaigns without external dependencies.

This skill provides comprehensive governance for multi-user API deployments using OpenRouter. It covers key provisioning, including creating, listing, and revoking individual user keys. Users can set per-user budget limits and track usage costs programmatically. It is designed for corporate or team environments that require strict cost control, usage attribution, and detailed usage reporting.

Designs content-led go-to-market systems that reverse-engineer distribution, repurpose pillar content, and track attribution so every post, video, or newsletter feeds measurable revenue and pipeline growth.

Guides GTM measurement for AI products by outlining revenue, efficiency, pipeline, retention, and funnel metrics, aligning dashboards with attribution models and weekly reviews so founders and revenue leaders monitor ARR, CAC, TTFV, NRR, and cost signals without implementation detail.

Systematically evaluates cyber-campaign evidence to attribute a cyber operation to a specific threat actor. This skill utilizes advanced analytical frameworks like the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh multiple indicators, including infrastructure overlaps, TTP consistency, malware similarity, and operational patterns, providing confidence-weighted attribution assessments for incident response.

This tool provides a comprehensive framework for analyzing web server logs (Apache/Nginx) to detect various security threats. It uses advanced regex matching against OWASP attack signatures to identify SQL injection, Local File Inclusion, and Directory Traversal attempts, alongside behavioral analysis for brute-force attacks and web scanner fingerprints. The system also enriches data using GeoIP for source attribution, generating a prioritized report for SOC analysts.

A comprehensive skill for building detailed threat actor profiles. It systematically collects and correlates intelligence from diverse open-source sources, including vendor reports, dark web forums, social media, and code repositories. The resulting structured dossiers map adversary motivations, capabilities, infrastructure, and Tactics, Techniques, and Procedures (TTPs), enabling robust attribution and defensive planning.

Structures completed intrusion investigations with the Diamond Model by documenting adversaries, capabilities, infrastructure, and victims plus their relationships, metadata, and pivots to cluster incidents and support campaign attribution, confidence scoring, and analytic write-ups.

Develops comprehensive profiles for Advanced Persistent Threat (APT) groups, criminal organizations, and hacktivist collectivities. This tool aggregates TTP documentation, campaign data, and attribution indicators from major intelligence sources (MITRE ATT&CK, Mandiant, CrowdStrike) to help organizations update threat models, prioritize defensive controls, and prepare executive briefings on sector-specific risks.

This skill provides comprehensive forensic analysis of cryptocurrency payment flows stemming from ransomware attacks. It leverages blockchain APIs and advanced techniques to identify wallet clusters, track fund movement through obfuscation methods like mixers and peel chains, and map funds to exchanges. It is crucial for law enforcement, incident responders, and threat intelligence analysts conducting ransomware attribution.

This skill covers using the SHAP library to explain and audit machine learning predictions. It guides users on selecting explainers, computing feature attributions, and validating results. It includes workflows for local and global visualizations, handling multi-output models, and ensuring model behavior descriptions are accurate without implying causality. Requires Python 3.12+ and specific SHAP versions.

This skill allows for the generation and execution of complex, optimized SQL queries to derive deep business insights. It supports sophisticated data workflows, including multi-table joins, multi-dimensional analysis (e.g., trend analysis, attribution modeling, comparative analysis), and subsequent recommendations for appropriate data visualizations (e.g., line charts, waterfall charts). It goes beyond simple SELECT statements by planning the query structure, handling schema relationships, and ensuring adherence to best practices.