Skill UI

Deploy DefectDojo as a centralized vulnerability dashboard that aggregates scanner results, deduplicates findings, tracks metrics, and feeds Jira/CI/CD workflows for security teams.

Structured facilitation of post-incident reviews that captures timelines, successes, failures, root causes, response metrics, and actionable improvements to strengthen future incident response.

Analyzes Zeek conn.log intervals with ZAT to compute jitter metrics and flag low-variance periodic connections, helping SOC analysts hunt for command-and-control callbacks and validate monitoring coverage.

Apply frequency analysis, jitter metrics, and coefficient-of-variation scoring to Zeek/proxy logs and SIEM data to surface periodic C2 beaconing, enrich with threat intelligence, correlate endpoints, and prioritize high-risk callbacks during threat hunting.

This skill automates the execution of red team phishing campaigns using the Python gophish library. It enables users to create sophisticated email templates with tracking pixels, configure SMTP profiles, import target lists from CSV, and launch full-scale simulations. The system tracks key metrics, including open rates, click rates, and submitted credentials, providing essential data for security awareness training and vulnerability assessments.

AgentHub spawns parallel git worktree agents that compete on tasks, evaluates their outputs via metrics or LLM judges, and merges the top branch for optimizations, research, or content variations.

Executes a structured VC valuation workflow that ingests SaaS or startup metrics, runs DCF, comparable revenue multiples, and SaaS health models via Python, and synthesizes a defensible valuation, runway, and capital-efficiency narrative for users planning fundraising or benchmarking.

Agent Eval Benchmarking orchestrates repeatable CLI comparisons of coding agents like Claude Code, Aider, and Codex, collecting pass rate, cost, time, and consistency metrics on your repository tasks so you can pick the right assistant with data.

Canary Watch keeps a deployed URL under continual surveillance after production/staging deploys, risky merges, or dependency upgrades, checking HTTP status, console/network errors, performance metrics, content, and API health with configurable alerts and digestible reports.

Guides multi-round investigation of any GitHub repository, combining API queries, discovery searches, and deep dives to produce structured markdown reports with summaries, timelines, metrics tables, and Mermaid diagrams for executive-ready briefs.

Guides Go developers through writing, running, and profiling benchmarks, interpreting pprof outputs, comparing regressions with benchstat, and tying results to CI or Prometheus metrics so you can make statistically sound performance decisions.

Guides Go engineers through production observability by covering structured logging with slog, Prometheus metrics, OpenTelemetry tracing, continuous profiling, RUM event tracking, alerting, and Grafana dashboards for observable services.