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.
531 skills found
CMMI-based SDLC router providing process guidance, requirements management, architectural decision support, quality assurance, and governance for GitHub and Azure DevOps workflows.
AI-powered coach for Xiaohongshu (XHS) note writing. Generate viral, platform-optimized content with storytelling templates, engagement hacks, and automated compliance tagging.
Create and manage TikTok image carousels via the ViralBaby API. Automate image search, text overlays, and draft uploads for social media content creation.
Query Microsoft 365 Copilot for workplace intelligence—emails, meetings, documents, and team communication—to ground your AI agent in organizational context.
A design system and anti-pattern guide to make AI-generated UI look human-crafted. Ensures professional aesthetics by managing color, typography, spacing, and animations for the Toh Framework.
Comprehensive biosignal processing toolkit for ECG, EEG, EDA, RSP, PPG, EMG, and EOG signal analysis, enabling psychophysiology research and multi-modal integration.
Orchestrates multi-agent development workflows, managing task decomposition, requirement analysis, and quality assurance for complex software projects.
Converts PRDs into structured task beads for autonomous execution with ralph-tui, including quality gates and dependency management.
Toolkit for applying consistent, professional styling to artifacts like slides, documents, and web pages using pre-set or custom-generated themes.
Autonomous, parallel-safe development workflow using kanban-md. Coordinates multi-agent and human efforts with atomic claims, worktrees, and explicit handoffs.
Structured problem-framing tool for design sprints and product strategy. Facilitates collaborative or individual sessions to define goals, stakeholders, constraints, and pain points before solution generation.
Python toolkit for mass spectrometry data processing. Enables spectral file importing (mzML, MGF, MSP), metadata harmonization, peak filtering, and calculating spectral similarity scores (cosine, modified cosine) for metabolomics.