Skill UI

A comprehensive security tool designed to detect and defend against subtle prompt injection attacks hidden within untrusted multi-modal content, such as web pages, PDFs, and images. It scans for obfuscated payloads (e.g., hidden CSS, metadata, zero-width characters) by combining content normalization, heuristic analysis, and dedicated ML detectors, ensuring that LLM agents only consume sanitized, trustworthy input.

This skill provides a comprehensive workflow for verifying the integrity of a system's boot chain using Trusted Platform Module (TPM 2.0). It covers local validation (event log replay against PCRs) and remote attestation (generating signed, nonce-bound quotes). Use this to detect bootkits, unauthorized firmware changes, or establish device posture for Zero Trust architectures.

A comprehensive guide on designing, building, and optimizing interactive developer playgrounds. Learn principles covering instant gratification, progressive complexity, and zero friction to maximize developer engagement, demonstrate core value, and convert curious visitors into active users.

A guide to designing friction-free developer onboarding experiences. Learn best practices for implementing GitHub OAuth, generating immediate API keys, and utilizing progressive profiling to maximize signup conversion rates while respecting the developer's time. Focuses on moving users from zero to coding as fast as possible.

Create highly aesthetic, animation-rich HTML presentations from scratch or convert existing PowerPoint files (PPT/PPTX). This tool focuses on generating distinctive, professional web decks with fixed 16:9 ratios. It supports low-density for keynote talks or high-density for detailed reports, ensuring visual impact and zero dependencies.

This skill guides users through building, deploying, and maintaining machine learning applications on Hugging Face Spaces. It provides comprehensive knowledge on selecting the optimal SDK (Gradio, Docker, Static), choosing appropriate hardware resources (ZeroGPU, dedicated GPUs, CPU-basic), and following best practices to ensure ML applications are deployed efficiently and successfully on the platform.

A comprehensive guide for developers building AI demos and GPU compute tasks on Hugging Face Spaces using ZeroGPU hardware. It covers best practices for writing and reviewing code that utilizes the `@spaces.GPU` decorator, managing runtime duration and quota, and understanding the specific CUDA availability model and process isolation rules required for reliable ML deployment.

This skill performs a deep comparison of two code versions to verify semantic equivalence, going beyond simple syntax diffing. It uses semi-formal tracing techniques to trace both versions against shared specifications and boundary conditions (e.g., null, zero, max/min). Ideal for confirming if a refactor, rewrite, or migration has unintentionally altered the code's behavior, answering the question: "Did I break anything?"

This skill enforces a rigorous, multi-phase coding workflow (Discuss -> Map -> Decompose -> Execute -> Verify) to ensure code is structurally grounded, complete, and free from invented APIs or assumptions. It is designed for high-stakes, complex, or multi-file engineering tasks, acting as a senior, disciplined coding partner that plans meticulously before writing code.