Skill UI

This skill covers predictable performance degradation patterns in language models as context length increases, including lost-in-middle effects, context poisoning, and distraction. It helps diagnose agent failures and design resilient systems by understanding attention mechanics and context engineering strategies for production environments.

This skill covers the core concepts of context engineering for language models, including system prompts, tool definitions, retrieved documents, message history, and tool outputs. It explains attention mechanisms, context windows, and strategies like progressive disclosure to optimize token usage and agent performance.

This skill specializes in advanced AI context engineering, managing dynamic information flows, vector databases, and knowledge graphs. It assists in building intelligent memory systems, optimizing context windows, and orchestrating multi-agent workflows. Ideal for enterprise-scale AI applications requiring coherent state management, RAG implementation, and semantic retrieval strategies to enhance system performance and reliability.

Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation. This skill covers exploratory data analysis, hypothesis development, experiment design, feature architecture, analytics instrumentation, and implementation with integrated tracking and monitoring.

This skill converts complex, narrative technical documents, research excerpts, or natural language problem descriptions into a highly structured Mathematical Problem Specification (MPS). It systematically extracts variables, constraints, objectives, and uncertainty parameters. By adhering to a strict Zero-Inference Protocol, it ensures all extracted elements are strictly grounded in the source text, making it invaluable for formalizing real-world optimization, data science, and engineering problems.

This skill covers .NET/C# binary reverse engineering, including managed PE analysis, debugging with dnSpyEx, deobfuscation using de4dot for tools like ConfuserEx, and IL patching. It supports analyzing red-team Sharp* tooling and distinguishing between managed and native binaries.

This skill focuses on reversing JavaScript-based custom DSL and Virtual Machine interpreters, commonly found in risk-control and captcha engines. It involves identifying IIFE and switch-based opcode dispatch patterns, extracting opcode tables, and capturing runtime semantics. The workflow includes static analysis for variable mapping and opcode classification, as well as runtime injection techniques to understand exported functions. It excludes standard WASM and typical Webpack bundles.

Reverse engineer EDR internals including user-mode hook tables, ETW, and AMSI to study bypass techniques like direct syscalls, Hell's Gate, and call-stack spoofing. This skill is designed for authorized red-team research and security assessments within controlled lab environments, focusing on Windows endpoint protection evasion.

This skill maps engineering changes (code diffs, architecture designs, IaC) to specific financial compliance controls, such as PCI-DSS v4.0 and MAS TRM. It generates an auditable report detailing compliance gaps, required evidence, and concrete remediation steps, helping teams catch violations before formal audits.

This skill detects when AI agents exploit human trust through social engineering, deceptive guidance, or false assurances. It identifies prompts that induce unsafe actions, request sensitive credentials, or impersonate authority figures. Use this when evaluating agent safety, security advice, or decision-influencing workflows. Skip for static information.

This skill provides expert guidance for Site Reliability Engineering (SRE) incident response. It covers rapid problem resolution, modern observability practices, and comprehensive incident management workflows. Use it for assessing severity, establishing command structures, stabilizing systems, investigating root causes using distributed tracing and metrics, communicating with stakeholders, and conducting blameless post-mortems to improve system resilience.

A skill for reverse engineering front-end web applications. It helps locate API signature chains, analyze encrypted request parameters, sample runtime behavior, and reproduce logic locally in Node.js for evidence-based output. Suitable for security assessments and understanding client-side encryption.