Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.

Assists R&D teams with patent technical disclosure drafting and patent/novelty search analysis; use when users ask to write a patent disclosure, structure an invention description, search related patents, or assess novelty.

Autonomously work on Jira backlog tickets, creating PRs and shepherding them to merge

Use when you need a deep-dive explanation of a specific file, function, or module in the codebase

A discipline for designing experiments (A/B tests, multivariate, holdouts) so the results actually answer the question you asked. Hypothesis writing, sample size, duration, segment analysis, interpretation, decision-making, and the common failure modes that produce confidently wrong shipping decisions.

Test environment system (DomeGradient, IBLGradient, default lighting, component schemas) against the poke example using the iwsdk CLI.

Test UI system (PanelUI, ScreenSpace) against the poke example using the iwsdk CLI.

Test level system (LevelRoot, LevelTag, default lighting, scene hierarchy) against the poke example using the iwsdk CLI.

Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.

Add Olakai monitoring to existing AI code — wrap your LLM client, configure custom KPIs, and validate the integration end-to-end

Build a new AI agent with Olakai monitoring from scratch — project setup, SDK integration, KPI configuration, and end-to-end validation

Build production-ready Tavily integrations with best practices for web search, content extraction, crawling, and research in agentic workflows, RAG systems, and autonomous agents

Monitor and analyze ransomware group data leak sites (DLS) to track victim postings, extract threat intelligence on group tactics, and assess sector-specific ransomware risk for proactive defense.

Use the Malpedia platform and API to research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages.

Find failing PR checks, inspect logs or external check links, and apply focused fixes

Stage files, run pre-commit, fix failures, loop until clean

Discord archive: search, sync freshness, DMs, summaries, TUI, repo/release work.

Threat modeling and risk audit for code changes and system designs. Walk the new attack surface, identify specific threats grounded in the change, propose security tests. Adversarial about assumptions, specific about risks.

This skill should be used when the user says "set up monitoring", "arn infra monitor", "infra monitor", "configure monitoring", "set up observability", "add logging", "configure alerting", "set up alerts", "infrastructure monitoring", "add metrics", "set up cloudwatch", "configure grafana", "observability setup", "logging setup", "alerting setup", "health checks", "monitor infrastructure", "arn-infra-monitor", "set up cloud monitoring", "configure notifications", "prometheus", "datadog", "new relic", "sentry", or wants to set up logging, metrics collection, and alerting for their deployed infrastructure.

Backend Reviewer Agent. 코드 리뷰, PR 검토, 코드 품질 평가를 담당합니다. 리뷰, 검토, PR, 코드 품질 관련 요청 시 사용됩니다.