linkedin-post-generator
AI-powered LinkedIn post generator for professionals. Create engaging thought leadership, career updates, and industry-specific content using the Sloan agent.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
468 skills found
AI-powered LinkedIn post generator for professionals. Create engaging thought leadership, career updates, and industry-specific content using the Sloan agent.
Designs and implements professional, interactive filtering UX for data tables based on column data types.
Augmented cognition layer that connects conversations to a persistent knowledge tree, enabling long-term memory, recall, and contextual reasoning across projects.
Persistent, semantic long-term memory for AI agents. Save, query, and retrieve cross-session dialogues, decisions, and multimodal context using semantic compression.
GitHub operations via gh CLI. Use for repository inspection, issues, PRs, releases, and deep codebase analysis including cloning for architectural insights.
Connect your AI agent to the Hugging Face Hub via MCP. Search models, datasets, and papers, manage repos, run cloud compute jobs, and invoke Gradio Spaces as functional AI tools.
A nested plugin architecture for Claude Code that optimizes context by dynamically loading playbooks, skills, and agents to save over 90% in token usage.
Implement production-ready AI chat interfaces using OpenAI ChatKit React components. Features include hook configuration, streaming, theming, conversation history, and custom tool integration for Next.js applications.
Build distinctive, high-end React Native Expo interfaces using liquid glass design and iOS Human Interface Guidelines for production-grade mobile apps.
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Perform internet searches using the Zhipu AI web search API to retrieve real-time information, news, and current data.
Epistemic safety analysis for JSON data in prompts to prevent LLM hallucinations and reasoning errors when handling incomplete or large-scale datasets.