openrouter-trending-models
Fetch and analyze current trending programming models from OpenRouter. Ideal for selecting models for reviews, optimizing AI costs, and staying updated on AI coding trends with real-time pricing and context window data.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
446 skills found
Fetch and analyze current trending programming models from OpenRouter. Ideal for selecting models for reviews, optimizing AI costs, and staying updated on AI coding trends with real-time pricing and context window data.
Reference for all MCP tools exposed by the CCOS server, enabling capability discovery, session management, and governed RTFS execution for autonomous agent workflows.
AI-powered lead generation pipeline: intelligent lead scoring (0-100) and context-aware follow-up generation for sales, cold outreach, and CRM integration.
A comprehensive Python library for querying, parsing, and analyzing SEC EDGAR filings, financial statements, and institutional holdings as structured data objects.
A structured personal operating system for managing digital presence, knowledge, relationships, and goals with AI assistance for founders, creators, and professionals.
GoHighLevel workflow automation expert. Integrates with Hylo GHL API to manage workflows, API endpoints, UI navigation, and automation planning.
Evidence-first literature collector for automated research pipelines. Scales paper pools to 1200+ with metadata normalization, provenance tracking, and multi-source ingestion.
Automated text-to-image rendering engine for social media posts, article covers, and long-form threads. Supports X-style, WeChat, and poster templates with high-precision text formatting and highlights.
A structured prompting framework to transform casual inputs into professional, modular LLM prompts with persona, context, task, format, and guardrails.
Audit Packmind documentation by cross-referencing MDX files against the codebase to detect broken links, outdated CLI references, and missing coverage.
Classical machine learning with scikit-learn. Use for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building robust ML pipelines in Python.
A suite of professional tools for auditing, evaluating, chunking, and scaffolding production-ready RAG pipelines within Claude Code.