Raptor turns Claude Code into a general-purpose AI offensive/defensive security agent. By using Claude.md and creating rules, sub-agents, and skills, and orchestrating security tool usage, we configure the agent for adversarial thinking, and perform research or attack/defense operations.
Annuaire de skills
Découvrez des skills réutilisables pour les AI agents.
Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.
Résultats de recherche: adversarial
Annuaire en anglaisA tool to convert a Wallpaper's color scheme / palette, OCR with VLM's Traditional & Hybrid, Image Compression ,color palette extraction, image upsacling with Adversarial Networks and more image processing features.
A Claude Code plugin that provides a universal radial-tree exploration engine with swappable presets for divergent ideation, adversarial critique, design-space exploration, and code audit.
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Image-to-image translation with conditional adversarial nets
Automated Cherry Studio review for local branches, PRs, commits, files, architecture docs, and repository skills. Use for code or documentation reviews that need project-specific naming, main/renderer/shared placement and dependency rules, IpcApi and DataApi boundaries, lifecycle/service ownership, renderer hooks, React/UI conventions, and tests. Supports single-agent review with interactive fix selection or multi-agent reviewer-verifier review with risk-based auto-fix. To diagnose gaps in the skill after a review session, run `/gh-pr-review diag`.
Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through hostile reviewer personas that catch blind spots the author's mental model shares with the reviewer.
VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
An adversarial example library for constructing attacks, building defenses, and benchmarking both
StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
Interactive Image Generation via Generative Adversarial Networks
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement