model-registry-maintainer
Maintain and update the MassGen model registry, including backend capabilities, model metadata, pricing structures, and context window configurations for new and existing AI models.
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483 skills found
Maintain and update the MassGen model registry, including backend capabilities, model metadata, pricing structures, and context window configurations for new and existing AI models.
Create and configure Hookify rules to watch for specific patterns in files, bash commands, or user prompts.
Find, connect, and use over 100,000 MCP tools and skills via the Smithery CLI to integrate external services, manage agent workspaces, and automate workflows.
Manage screenpipe pipes (AI-driven automations) and integrations via CLI. Create, run, schedule, and debug local agents to automate tasks based on your computer activity.
Multi-model LLM integration patterns for Claude, GPT, Gemini, and Ollama. Features API handling, prompt engineering, token management, and model-agnostic orchestration.
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.
Performs end-to-end OT/ICS threat modeling using Microsoft TMT exports and model files, mapping threats to MITRE ATT&CK for ICS, CWE, and CVSS v4.0 with automated risk-based prioritization.
A comprehensive library of 305+ modular instruction packages, Python CLI tools, and agent workflows designed to extend the capabilities of AI coding assistants like Claude Code, Cursor, Aider, and Gemini CLI.
Execute implementation plans in separate sessions with review checkpoints, ensuring task-by-task verification and robust code quality.
Seamlessly toggle between live and mocked external dependencies using the Model Context Protocol (MCP) for autonomous development environments.
Trace Rspack Rust function calls using LLVM XRay for performance analysis, troubleshooting, and visualization of execution flow.
Safely execute, test, and verify commands discovered in documentation with real output capture, performance tracking, and git-aware safety protocols.