constant-time-analysis
Detects timing side-channel vulnerabilities in cryptographic code through static and dynamic analysis across multiple programming languages.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
162 skills found
Detects timing side-channel vulnerabilities in cryptographic code through static and dynamic analysis across multiple programming languages.
Symbol-level code understanding and navigation agent toolkit using LSP for precise code analysis, reference tracking, and surgical refactoring across 30+ programming languages.
AI-driven GitHub Actions automation featuring swarm-based workflow orchestration, intelligent CI/CD pipeline management, and autonomous repository maintenance.
Expert guidance for building production-ready applications with Anthropic's Claude API. Covers SDKs, prompt caching, batch processing, streaming, tool use, and cost optimization strategies.
Pre-execution security guardrails for AI agents. Validates shell commands and file reads against 400+ security patterns to block destructive operations, credential theft, and unauthorized system access.
Anthropic Claude AI models for high-performance coding, large-context analysis, and GUI interaction.
An advanced research intelligence skill for content creators and marketers that analyzes trends across 10+ platforms to generate data-driven content outlines based on user intent.
Search and analyze X (Twitter) trends, hashtags, and tweet data by location using custom CLI tools.
Analyze YouTube videos with automated transcript extraction, AI-powered summarization, Korean translation, and interactive multi-level comprehension quizzes.
Access Y Combinator’s library of 443+ startup resources for expert advice on fundraising, co-founders, product development, growth, and scaling your business.
Token-efficient codebase analysis skill for call graphs, semantic search, impact analysis, and data flow. Saves ~95% tokens vs. raw reads.
Identify and document Customer Problems (CP) from business context. Use when starting requirements engineering or when stakeholders describe solutions instead of problems. Step 1 of Problem-Based SRS methodology.