Minimal AI coding agent team skills for the full engineering workflow.
A structured enforcement system for AI-generated code. Turns predictable AI failure modes into architectural gates, static analysis halts, and runtime proof requirements. Preserves engineering intent AI assists, humans decide.
AI-native engineering workflow skills for Claude and Codex — repo-backed PRD-to-code orchestration, milestone delivery, and validation.
Autonomous software delivery with AI agents — your BACKLOG runs itself, guided by encoded engineering discipline. No sprints, no hand-holding.
GitHub Copilot chat modes for planning, implementation, code review, PRDs, and prompt optimization.
A mental framework for cutting through complexity. Establish baseline, isolate what matters, execute one change.
Tool to simplify the C++ development
Think before you build. Universal AI engineering orchestration framework for Claude, Codex, Cursor, and Windsurf.
A practical operating model for AI-assisted software engineering using tools like Cursor, Claude and structured development workflows.
A skill for AI agents that turns repos, requirements, and design state into durable, evidence-backed context — so multi-agent collaboration stops drifting.
Codex skill for cross-session engineering workflow, handoffs, acceptance, and repo coordination.
Streamline your software delivery with a production-ready engineering workflow. Automated semantic versioning, changelog generation (via git-cliff), and aggregated release publishing across GitHub and major package registries.
AI-native engineering workflow system focused on bounded engineering cognition for real-world software development.
Manus Project OS. Structured framework for building large software systems with AI-assisted engineering.
Tool-agnostic engineering workflow plugin for AI coding agents. Surface-first change analysis, source-of-truth discipline, Lean/Full modes, phase-gate discipline, evidence-driven delivery. Works with Claude Code, Cursor, Gemini CLI, Windsurf, Codex, Aider, OpenCode.
Agent operations sprint for engineering teams shipping with AI coding agents
The Autonomous DevOps Engine 2026: Self-Optimizing Backlog for AI-Disciplined Teams
A Human & Machine readable audit trail. Engineers need it because it prevents the two common failure modes of agent driven development: Agents make changes but nobody can quickly tell what changed, why, and whether it passed checks Work cannot be reliably resumed, reviewed, or automated because state and logs are scattered
Structured multi-AI engineering workflow using adversarial review, persistent context, and human-governed development.
Curated Codex skill packs for engineering, self improvement, AI entertainment, and applied media workflows
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