Skill UI

This skill initializes an autonomous, scheduled loop for running complex research or engineering experiments. Users specify the target experiment and select a recurring interval (e.g., 10 minutes, daily, weekly). It utilizes cron scheduling to ensure continuous research, guiding iterative changes, evaluating metrics, and committing results automatically until manually stopped.

This command executes the entire AgentHub lifecycle in a single, chained invocation. It automates complex development tasks by sequentially handling initialization, capturing performance baselines, spawning multiple specialized agents, evaluating the results (via metrics or LLM judging), and finally presenting a winner for merging. Use this when running an end-to-end competition or complex refactoring task.

Guides founders and GTM teams through video-first cold outreach, personalized AI deliverables, async selling, and demo-led prospecting so you can research, build, record, and deliver compelling video touchpoints that cut through inbox noise.

A forensic tool for performing post-mortem analysis on AI-assisted coding sessions. It goes beyond simply stating what was done, determining *why* work deviated (e.g., spec ambiguity, repo friction, agent error), identifying scope creep, and classifying rework patterns. It provides evidence-backed recommendations to improve prompts, codebase health, and future development workflows.

This skill automates the complex and tedious process of porting academic papers written in LaTeX from one publisher's journal template (e.g., Springer) to another (e.g., MDPI, IEEE). It executes a structured multi-stage workflow, including content extraction, structural mapping, systematic fixing of common LaTeX issues (like float placement and math environments), and final compilation to ensure the output adheres to the target journal's specifications.

A comprehensive guide for creating forensically sound, bit-for-bit disk images of suspect drives using standard tools like dd and specialized forensic tools like dcfldd. It emphasizes best practices including hardware write-blocking, pre-acquisition hashing, and post-acquisition integrity verification to maintain the chain of custody for legal evidence.

A comprehensive design specification detailing 98 rules for building Command Line Interface (CLI) tools that are safe, reliable, and easily consumable by AI agents. It covers structured JSON output formats, standardized error handling (to stderr), robust input contracts, safety guardrails (e.g., preventing path traversal), and tiered compliance levels (Agent-Friendly, Agent-Ready, Agent-Native) for seamless integration into AI workflows.

This comprehensive guide details advanced forensic techniques for detecting and analyzing sophisticated malware that operates at the system's deepest levels, such as the Master Boot Record (MBR), Volume Boot Record (VBR), and UEFI firmware. It covers boot sector disassembly, UEFI module inspection, and memory forensics (SSDT/DKOM). Use this when standard security tools fail or when investigating nation-state level compromises.

A specialized tool designed for incident responders and threat hunters. It extracts critical configuration data—such as C2 server addresses, malleable profiles, watermarks, and communication settings—from Cobalt Strike beacon payloads found in PE files or memory dumps. This analysis is crucial for mapping attacker infrastructure and improving defensive detection rules.

Parses Cobalt Strike malleable C2 profiles via pyMalleableC2 to pull beacon configs, HTTP communication patterns, sleep/jitter settings, and combines JARM scans for C2 detection when hunting suspected infrastructure or building IDS signatures.

This skill provides a comprehensive workflow for reverse engineering Go-compiled malware using Ghidra. It focuses on overcoming Go-specific binary challenges, such as non-null-terminated strings, complex metadata structures (pclntab), and function name recovery in stripped binaries. Users can extract build information, reconstruct dependencies, and analyze malicious capabilities essential for threat intelligence and incident response.

A powerful toolkit utilizing Objection and Frida for authorized mobile penetration testing. It enables deep runtime analysis of iOS applications, allowing users to inspect sensitive data in the keychain, filesystem, and memory. Key capabilities include bypassing client-side protections such as SSL pinning and jailbreak detection without requiring source code access.