77 RESULTS · “engineering”
v1.19.0 · MIT
GSD Core is a meta-prompting, context engineering, and spec-driven development system for AI coding agents.
v3.4.0 · no license
Claude Code learns from your corrections: self-correcting memory that compounds over 50+ sessions. Context engineering, parallel worktrees, agent teams, and 17 battle-tested skills.
v2.2.0 · MIT
Install engineering discipline into any AI coding assistant. Composable skills for design, implementation, review, and team standards. Better process, not just better prompts.
— · MIT
33 engineering discipline skills for Claude Code, OpenAI Codex & Gemini CLI + a CLI for CI/CD enforcement. Extracted from real-world multi-agent system development. Born from real pain, not theory.
v2.1.2 · MIT
Engineering discipline for AI coding agents: question the request, verify against current docs, plan, build test-first on the cheapest capable model, review with a second model family, prove it before saying done. One repo for Claude Code, Codex, Antigravity, Cursor, Gemini CLI and OpenCode.
— · Apache-2.0
Spec-driven development and context engineering for Claude Code, Cursor, Codex, and GitHub Copilot — backed by project context in Git.
v1.45.10 · Apache-2.0
A platform engineering handbook covering Kubernetes, OpenShift, Argo CD, Flux CD, AWS, Azure, Terraform, and GitHub Actions — with an optional Claude plugin layer for interactive guidance.
v0.30.0 · MIT
Train your AI coders the way you'd train a vine — discover your codebase's actual patterns, then encode them as Claude Code rules, skills, agents, hooks, and a guided pipeline so generated code lands inside your conventions on the first try, not the fifth.
— · no license
A set of Claude Code and GitHub Copilot plugins providing the AI Literacy framework's complete development workflow — harness engineering, agent orchestration, literate programming, CUPID code review, and the three enforcement loops
Agentic Software Engineering (ASE)
Stop agents from over-engineering. Inspired by Ponytail, but without the plugin madness. Just one AGENTS.md file.
v0.1.0 · Apache-2.0
Open-source skills for designing and reviewing software with AI agents
Unbrowse - Reverse engineer any website so that your agents can access its APIs directly
v0.30.2 · MIT
Claude Code plugin: run the Antigravity CLI (Gemini) as a collaborating sub-agent with intelligent model routing across the SDLC. Community project; not affiliated with Google/Anthropic.
Bounded-autonomy plugin harness for agents. Intent to implementation: ready, then go.
v3.0.0 · MIT
RFC-driven development for AI coding agents: idea or existing codebase → verified PRD → features → rules → sequenced RFCs → reviewed code. Agent Skills for Claude Code, Codex, Copilot, Cursor, Gemini CLI, OpenCode, Devin.
Claude Code plugin that generates production-grade Python CLIs for any web app. 20 CLIs and counting.
v0.4.0 · MIT
iOS development ClaudeCode plugin for mindful token and context usage. Contains modular MCPs that group various Xcode/IDB tools based on your current workflow. [deprecated]
v0.7.0 · MIT
Make AI output sound human. Strips AI-isms (sycophancy, stock vocab, hedging stacks, em-dash pileups), preserves code/URLs/headings. Plugin for Claude Code, Cursor, Windsurf, Codex, Cline, Copilot, Gemini.
v0.3.0 · MIT
Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.
UI/UX system for Claude Code: 71 plugins, 93 agents, 74 skills. Design mastery, archetypal design, accessibility, and frontend workflows in one validated plugin marketplace.
Static analysis for AI agent configs, tool descriptions, and system prompts — catches vague tool descriptions, missing stop conditions, and schema gaps before they reach runtime. Zero-LLM, deterministic checks, built for CI.
MCP server for EPLAN Electric P8: ~200 tools to drive EPLAN from Claude Code, Codex, Cursor or any MCP client (actions, scripts, live DataModel, exports). Includes the eplan-tools plugin marketplace.
v3.0.0 · Apache-2.0
Content-aware output compression for AI coding assistants. 36 specialized processors cut CLI output tokens by 60-99% (git, pytest, npm, terraform, kubectl, docker, and more) without losing errors, diffs, or stack traces.