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This skill maps identified security threats to appropriate controls and mitigation strategies. It is essential for prioritizing security investments, building comprehensive remediation roadmaps, validating existing control coverage, and performing detailed risk treatment planning. It helps organizations design robust, defense-in-depth security architectures.

Automates threat modeling guidance within Security Advanced: step-by-step best practices, compliance-ready code, and validation for enterprise security workflows.

A specialized skill for conducting comprehensive security architecture reviews, risk assessments, and threat identification. It masters advanced methodologies like STRIDE, PASTA, and attack tree construction. Use this to build secure-by-design systems, identify potential attack vectors, and strengthen system resilience before deployment.

This comprehensive skill provides advanced architectural patterns for implementing robust API throttling and rate limiting policies. It covers critical concepts like concurrency limiting, priority queuing, circuit breakers, and adaptive throttling that adjust limits based on real-time backend health metrics (p95/p99 latency). Use this when designing resilient, scalable backend services that must protect themselves from overload and maintain stability under high load.

A comprehensive, adaptive framework for managing the entire software development lifecycle, from initial project specification to final execution. It automatically sizes the depth of the workflow (Specify, Design, Tasks, Execute) based on the complexity and scope of the feature or project. Ideal for starting new projects, mapping existing codebases, implementing complex features with atomic verification, and maintaining persistent state across sessions.

Analyzes token implementations and integrations with ERC20/ERC721 standards, checks 20+ weird token patterns, assesses owner privileges, contract composition, and on-chain scarcity to highlight risks before deployment.

Scans FunC-based TON smart contracts for boolean, Jetton, and gas handling vulnerabilities, reporting critical issues with file references and offering remediation guidance for auditors and secure dApp launches.

This skill provides advanced guidelines for designing robust and effective tools specifically for autonomous AI agents. It shifts the focus from traditional developer APIs to contracts optimized for Language Models (LLMs). Key topics covered include treating tool descriptions as prompt engineering, implementing namespacing, applying the Consolidation Principle, and utilizing Architectural Reduction patterns (like file system access) to maximize agent reliability and workflow complexity.

Provides a structured reference of the 100 most critical web application vulnerabilities organized by category, helping security teams identify attack vectors, assess impacts, and follow remediation guidance during audits or penetration tests.

torchforge is Meta's advanced PyTorch-native library designed for agentic Reinforcement Learning (RL). It fundamentally separates core RL algorithms from complex distributed infrastructure concerns. This allows researchers to rapidly prototype and experiment with novel RL methods (like GRPO) using clean, PyTorch-native abstractions, while automatically handling large-scale tasks like distributed training across thousands of GPUs using Monarch and TorchTitan.

Tracks and runs regression suites, automating execution of critical tests and analyzing outcomes so Claude highlights failures, flaky checks, and stability impacts before deployments.

Defines and monitors SLAs, SLIs, and SLOs so teams can set performance targets, track metrics like error budgets and availability, and react before issues impact customers.