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.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
253 skills found
CMMI-based SDLC router providing process guidance, requirements management, architectural decision support, quality assurance, and governance for GitHub and Azure DevOps workflows.
Manage project SSOT, memory, and cross-tool search. Guardian of decisions.md and patterns.md for Claude Code. Use for context retention, memory synchronization, and decision tracking.
Generate, validate, and refine Mermaid diagrams including flowcharts, sequence diagrams, ERDs, and architecture maps to visualize complex software systems and workflows.
Automates the synchronization of new infographic templates by updating project documentation, gallery mappings, and AI playground prompts.
Implementation and verification patterns for JWT (JSON Web Token) authentication using Better Auth and FastAPI.
Autonomous research specialist for verified information gathering, source evaluation, and structured synthesis.
Automated security validation, RLS enforcement, OWASP compliance, and vulnerability scanning for AI-assisted development workflows.
MIKE-FIRST v6.0: An enterprise multi-cloud resilience platform for compliance auditing, security intelligence, and zero-downtime cloud migration.
Proactive context window management for AI agents via intelligent token monitoring, snapshot creation, and selective state rehydration to maintain continuity during long sessions.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.
Comprehensive Google Docs and Drive management tool. Supports document creation via Markdown, text formatting, structure analysis, and full file operations including upload, download, and sharing.
Aggressively prune grammatical scaffolding and filler text from inputs to optimize LLM token usage while retaining core semantic content.