Agent Skills Hub

deep-thinking

A deep reasoning protocol that ensures systematic analysis, multi-hypothesis generation, and rigorous verification for complex architectural, debugging, and high-stakes tasks.

k0ntext

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

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.

User Story Writing

Create well-structured user stories with clear acceptance criteria using the standard As a/I want/So that framework for agile team alignment.

customer-research

Multi-source research tool for customer inquiries, bug investigations, and account history synthesis with source attribution and confidence scoring.

github-navigator

GitHub operations via gh CLI. Use for repository inspection, issues, PRs, releases, and deep codebase analysis including cloning for architectural insights.

customer-problems

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.

help

Interactive guide for workspace discovery, providing access to specialist agents, automated workflows, CLI tools, and active lifecycle hooks.

mcaf-architecture-overview

Maintains a centralized architecture overview with Mermaid diagrams to document system boundaries, module dependencies, and interface contracts for onboarding and refactoring.

jira-assistant

Manage Jira issues via Atlassian MCP. Search, create, update, transition status, and handle sprint tasks with auto-detected workspace configuration.

sparc-methodology

SPARC methodology for multi-agent development: systematic Specification, Pseudocode, Architecture, Refinement, and Completion workflows via Claude Flow orchestration.

context-optimization

Optimize agent context windows through KV-caching, observation masking, summarization-based compaction, and context partitioning to reduce costs and latency.