reverse-engineering-api
Reverse engineer web APIs by capturing browser traffic (HAR files) and generating production-ready Python API clients for automation and data extraction.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
512 skills found
Reverse engineer web APIs by capturing browser traffic (HAR files) and generating production-ready Python API clients for automation and data extraction.
Manage AWS Lambda serverless functions: deploy code, configure event triggers, debug invocations, optimize cold starts, and maintain layers.
Manage your Anki flashcards effortlessly via the AnkiConnect REST API. Create, update, search, and organize decks, notes, and cards directly through your AI agent.
Expert advisor for implementing Anthropic's structured outputs. Choose between JSON mode and strict tool use for guaranteed schema compliance and validated agentic workflows.
Automate iOS development workflows using XcodeBuildMCP: build, run, test, inspect UI, and capture logs on local simulators.
Monitor Claude Code usage, token consumption, productivity streaks, and skill effectiveness metrics to optimize your development workflow.
Manage YNAB budgets, track spending, and automate financial reports via API. Features include transaction logging, goal monitoring, and automated budget analysis.
Integrates browser-native Proofreader API into web applications for AI-powered text correction, grammar checking, and language support with managed model lifecycle.
Build distinctive, high-end React Native Expo interfaces using liquid glass design and iOS Human Interface Guidelines for production-grade mobile apps.
Method-driven planning workflow that intelligently decomposes tasks into structured plan.md files using zen-mcp tools, adapting to user clarity and automation needs.
Optimize agent performance and token usage through advanced context compression, structured summarization, and task-oriented state management for long-running sessions.
Analyze local system hardware (RAM, CPU, GPU/VRAM) to receive expert recommendations for optimized local LLM models, quantization settings, and performance estimates.