Skill UI

A comprehensive methodology for deep security testing of both Android (APK) and iOS (IPA) applications. This guide covers the entire workflow, from initial information gathering and static analysis (decompilation, code structure analysis) to advanced dynamic instrumentation, network interception, and bypassing modern security measures like SSL Pinning, Root/Jailbreak detection, and anti-debugging.

A comprehensive guide for installing, configuring, and validating the local long-term memory plugin (`memory-tencentdb`) within the OpenClaw environment. This guide covers everything from environment pre-checks to advanced configuration for data capture, information extraction, context recall, and vector embedding, ensuring robust, self-contained memory capabilities for RAG applications.

Guides users to select a local, on-device Personally Identifiable Information (PII) detection model from a committed registry. It filters models based on language, required runtime environment (e.g., PyTorch, MLX), and size constraints. The process emphasizes building an offline shortlist and mandates rigorous pre-deployment recall validation and performance benchmarking to ensure secure, privacy-preserving deployment.

An advanced orchestrator that manages the entire software development lifecycle (SDLC) from initial concept vetting to final code deployment. It guides the process through distinct, sequential stages: Product Direction Review (CEO), Technical Architecture Review (Engineering), Detailed Planning, Validation, and final Execution (PR). This tool ensures all critical gates are passed before writing code, minimizing risks and ensuring alignment.

This command acts as a crucial product gate, forcing a deep, strategic review before any code is written. Instead of simply fulfilling the request, it guides users through three structured roles: Scope Expansion (finding the 10x vision), Hold Scope (stress-testing assumptions and failure modes), or Scope Reduction (defining the true MVP). It ensures that the developed solution solves the user's real job-to-be-done, not just the explicit feature request.

This robust pipeline guides development teams through a rigorous, five-phase planning process *before* writing any code. It systematically analyzes PRDs, design specifications (UX, accessibility), and existing architecture to produce a comprehensive implementation plan. Key outputs include Architecture Decision Records (ADRs), detailed task breakdowns, and verification strategies, ensuring all technical and design decisions are documented and scoped.

Performs comprehensive, two-layer validation on generated plans. Layer 1 executes instant structural checks (format, dependencies, compliance) while Layer 2 triggers specialist agents (e.g., security, DB, performance) based on plan content. The system forces resolution of all identified issues before allowing execution, supporting auto-fixes and guided human input.

A comprehensive guide for auditing and polishing original long-form manuscripts intended for submission to high-level Pattern Recognition and AI journals. It details mandatory components, formatting standards, anti-plagiarism checks, and ethical guidelines, ensuring the paper meets rigorous peer-review standards for publication.

This skill manages complex, stateful proof projects as a local-first pipeline. It guides the user through drafting, rigorous verification, and source bookkeeping. It systematically handles proof continuation across runs, maintaining a full audit trail. When local attempts stall, it orchestrates handoffs to external AI models (like GPT Pro) or performs optional deep audits (DeepSeek), ensuring a structured, traceable, and verifiable output suitable for academic or technical submission.

A comprehensive, multi-phase workflow guide for authorized reverse engineering of complex network protocols. Ideal for analyzing proprietary formats such as custom TCP/UDP binary protocols, Protobuf, gRPC, WebSocket frames, and reconstructing state machines from raw PCAP data. This guide covers data collection, field layout restoration, serialization recovery, and secure replaying.

A comprehensive, multi-step framework for conducting systematic QA testing on web applications. This guide covers scope detection (diff-aware), tiered testing depth (Quick, Standard, Exhaustive), detailed issue taxonomy (Functional, Visual, UX, etc.), structured bug documentation, and the critical fix-and-verify loop, ensuring high code quality throughout the development cycle.

This skill guides a thorough, adversarial review of development plans across four key dimensions: Architecture, Code Quality, Testing, and Performance. It forces explicit consideration of trade-offs, risks, and user approval before any code is written, ensuring robust and well-engineered solutions for complex systems.