Delegating to AWS Agent
Implement an AI agent delegation architecture to keep your main context clean, reduce token costs, and isolate specialized infrastructure or API tasks.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
368 skills found
Implement an AI agent delegation architecture to keep your main context clean, reduce token costs, and isolate specialized infrastructure or API tasks.
Retrieve current, source-backed technical information using MCP tools to resolve queries about libraries, APIs, SDKs, and evolving tech ecosystems.
Generates comprehensive API references, user manuals, and architectural system documentation directly from your codebase and technical specifications.
A toolkit for writing high-quality agent skills (SKILL.md files) for ClawdHub/MoltHub, covering structure, frontmatter schemas, content patterns, and agent-consumable documentation best practices.
Enriches vague prompts by performing codebase research and asking targeted questions to clarify user intent before execution.
Generate a structured academic paper outline from research narrative, experiment data, and review conclusions.
Package entire code repositories into single, AI-optimized files. Ideal for providing codebase context to LLMs like Claude, ChatGPT, and Gemini for analysis, security audits, and bug investigations.
Retrieve real-time library documentation, code examples, and technical guidance using the Context7 API for frameworks like React, FastAPI, and Next.js.
Convert SRT subtitle files into structured Markdown notes with punctuation, paragraph formatting, and automated video screenshot placeholders.
Comprehensive reference for GrepAI configuration, detailing the .grepai/config.yaml schema, embedder settings, storage backends, and optimization parameters.
Build and orchestrate end-to-end MLOps pipelines covering data preparation, training, validation, and automated deployment.
Orchestrates multi-agent iterative refinement for high-quality OpenClaw skill development, ensuring rigorous testing and lifecycle management.