Skill UI

This skill uses advanced AI and LLM capabilities to correlate fragmented Open Source Intelligence (OSINT) data. It ingests findings from diverse sources—including username enumeration, email lookups, social media, domain records, and breach databases—to generate unified, intelligence-grade profiles. It provides link analysis and confidence scoring, transforming raw data into actionable threat intelligence for target profiling.

This skill provides a comprehensive guide and structured SQL templates for performing deep forensic investigations on AWS cloud logs. It utilizes AWS Athena to query massive datasets from CloudTrail, VPC Flow Logs, S3 access logs, and ALB logs. Ideal for detecting unauthorized access, data exfiltration, and privilege escalation during security incident response.

This comprehensive skill provides a systematic framework for performing deep security assessments on iOS applications. It covers static analysis of IPA packages, dynamic instrumentation using Frida and Objection, SSL pinning bypass for traffic interception, extraction and auditing of sensitive data from the Keychain, and runtime method hooking. Use this for authorized penetration testing against standards like OWASP MASTG.

This skill automates the entire SOC 2 Type II audit lifecycle. It facilitates gap assessment against AICPA Trust Services Criteria (CC1-CC9) and collects continuous evidence from major cloud providers (AWS, Azure, GCP) and identity systems (Okta, Jira). It supports validating control effectiveness, remediation tracking, and overall compliance monitoring for Security, Availability, Processing Integrity, Confidentiality, and Privacy.

This file serves as a Japanese translation placeholder for the 'product-lens' skill. It indicates that the localization process is currently in progress. Users should refer to the original source file for the complete English version and functionality.

This skill manages the entire academic rebuttal cycle. It parses external reviews from major conferences (like ICML/OpenReview), drafts safe, text-only responses while strictly enforcing grounding (no fabrication) and full issue coverage. It supports multi-round follow-ups and adheres to venue-specific constraints, ensuring every claim is provable.

This critical skill serves as a gate between completed experiments and final research conclusions. It systematically evaluates collected experimental results (e.g., W&B metrics, logs) against predefined research claims. It performs deterministic evidence pre-checks to verify if cited data points exist, and utilizes an advanced AI model (Codex) to judge whether the results support, contradict, or lack evidence for the intended claims, guiding the next action (pivot, supplement, or confirm).

The Safety Guard skill is designed to prevent destructive actions when working in production systems or when autonomous agents are executing tasks. It offers three protection modes (Careful, Freeze, and Guard) to monitor dangerous commands, lock specific directories, and ensure code changes are confined to intended areas, enhancing system stability and security.

This skill searches for published academic papers from major venues like IEEE, ACM, and Springer via the Semantic Scholar API. It is ideal for finding peer-reviewed journal articles and conference proceedings, providing crucial metadata such as citation counts, venue details, and TLDR summaries. Use it when you need verified, published literature beyond raw arXiv preprints.

This tool assesses whether coding agents adhere to defined skills, rules, or agent definitions. It automatically generates scenarios with varying prompt strictness, executes the agent, and generates a comprehensive report detailing the compliance rate of tool calls against predefined workflow specifications using advanced LLM classification.

This skill provides a comprehensive framework for simulating and testing disaster recovery plans against ransomware threats. It guides users through measuring Recovery Time Objective (RTO) and Recovery Point Objective (RPO), validating clean backup restores, and hardening security controls to ensure organizational resilience. It is designed for tabletop exercises and compliance auditing, not for active incident response.

This skill intercepts the response flow before generation, allowing the user to explicitly control the desired depth, length, and token usage of the AI's answer. It estimates the complexity of the input prompt and presents multiple options (e.g., 25%, 50%, 75%, 100%), ensuring the output matches the user's need, whether they require a brief summary or a comprehensive, detailed analysis.