Agent Skills Hub

plan

Structured 6-phase workflow for planning and implementing features, skills, and architectural changes with automated tool discovery and safety verification.

k0ntext

RPI Plan Phase: Create chunk-based, dependency-aware implementation plans from research documents for structured, atomic development.

prp-ralph-loop

Autonomous iteration loop for AI software development. Executes tasks, validates code, and manages state until completion. Ideal for implementing complex PRP plans.

cross-plugin-detective

Standardized detective skill integration for agent roles. Maps agents to code-analysis skills and enforces claudemem usage for memory-indexed code investigation.

mind

Persistent, Git-friendly memory for Claude. Automatically store and retrieve project decisions, bug fixes, and coding patterns in a local .mv2 file.

looped-builder

Scaffold complex, multi-step coding tasks into actionable implementation plans and execute them autonomously using a Claude-driven bash loop.

skill-repo

Standardize, validate, and manage Netresearch AI agent skill repositories with automated structure enforcement, distribution workflows, and licensing compliance tools.

context-cascade

A nested plugin architecture for Claude Code that optimizes context by dynamically loading playbooks, skills, and agents to save over 90% in token usage.

git-commit-formatter

Standardize git commits with conventional formatting, signatures, and automated context gathering for better project history.

tool-use-structured-output

Enforce structured JSON output from Claude models using Bedrock tool_use to eliminate parsing failures and ensure schema compliance.

lsp-setup

Automated LSP detection, installation, and configuration for intelligent code analysis, navigation, and diagnostics.

using-sdlc-engineering

CMMI-based SDLC router providing process guidance, requirements management, architectural decision support, quality assurance, and governance for GitHub and Azure DevOps workflows.