Havuz

An advanced, unified platform for code quality, architectural metrics, and Agile analytics. Features Python AST parsing, Java static analys

A soulful, production-grade PDF reader for Android featuring a "Warm Paper" aesthetic, gesture-driven interface, and a high-performance modu

Turn requirements into UML diagrams, test cases and editable Word specs—with traceability. Self-hosted, bring your own AI model. Built for c

Reusable AI agent skills for software factories: explore ideas, write specs, implement, review, and run autonomous research. Works with Clau

Mini Program Engineering Skill Suite is an Agent Skill suite for evidence‑first mini‑program development. It helps agents bring WeChat or ot

Las empresas tech que más pagan en España y un MCP para que tu agente de IA aplique por ti a sus ofertas. Best-paying tech companies in Spai

12 agent skills for AI-driven software development — a gated idea-to-ship pipeline: 7w3 design, build-ready specs, executable architecture,

LoopArena, uzun süreli yazılım görevlerinde bir coding agent’ı yönlendiren modelleri ortak koşullarda karşılaştırmak için benchmark ve çalıştırma altyapısı sunuyor.

Neden yükseliyor · Coding agents’ın uzun süreli iş akışlarında nasıl yönlendirileceği güncel bir araştırma konusu; LoopArena bu konuya açık protokol, benchmark sonuçları ve bir arXiv paper ile dikkat çekiyor. Ancak 146 yıldız, 28 günlük repo yaşı ve son 28 günde tek farklı yazar, ilginin henüz yaygın benimsemeye dönüştüğünü göstermiyor.

PavedPath Code: reusable Skill for finding proven implementation paths from GitHub and open-source evidence

Agent skills synthesizing years of software engineering discipline into a prescriptive methodology for solo developers

Git-native memory for coding agents. Repo memory before the diff.

Private, self-hosted AI-native software engineering suite — unified identity (GM) plus AI agents, code collaboration, artifact management, t

3x more usage on your coding agent, same quality. Have an multi-agent setup in mind? Bello already supports it. Mix models, run agents in pa

A lightweight annotation standard that helps AI agents navigate codebases faster, with fewer file reads and tool calls

📖 Data Engineering from Raw Corpora

A persistent, reviewed multi-agent runtime for long-horizon research and engineering.

Automatically completes the full workflow from requirement research → research review → planning → plan review → development → development

🐴 Prompt-first harness engineering for safer AI coding agent workflows.

Agentic prompts are the most important code you're not engineering. PromptKit fixes that — composable, version-controlled prompt components

A work-centered runtime for agentic software engineering. Work persists; agents, context, and graphs assemble around it.

Loop engineering for software development. Turn any repository into a self-organizing AI engineering team — 8 specialists, contract-driven,

Rational engineering system prompt for Codex and LLMs — focused on accuracy, software engineering, AI, security research, bug bounty, and re

Production-grade Agent Skills for AI coding agents—composable workflows for planning, TDD, debugging, review, UI/UX, releases, incidents, an

Multi-agent engineering framework: evidence packs, runtime validation, task decomposition, cross-window worker execution, and CI artifact ve

A finite ontology of 115 recurring software elements and a composition framework for LLM-based coding agents

A benchmark for testing whether coding agents can resolve engineering tasks in scientific software

Engineering workflows for AI coding agents or flesh engineers. It helps absorb silent base-model quality drift.

Benchmarking repository-borne prompt injection attacks and lightweight defenses for local coding agents. DL4C @ ICML 2026.

Platform-agnostic AI agent: one Full-Stack Software Engineer brain, compiled into ready-to-paste adapters for ChatGPT, Claude, Copilot, Gemi

A Sovereign Agent Governance Protocol for Deep-Water Workflows

A behavioral governance framework for GitHub Copilot agents — skills.md and instructions to make AI coding agents think like senior engineer

Help your agents find the smoking gun they're looking for. Optimization evidence for agents: find complexity hotspots.

NOW you can let AI agents make code changes without losing engineering control.

AI-Native 通用开发工作流方法论：4-Phase 框架 + 空项目/已有源码两种场景 + 反模式速查。让 Claude Code 等 AI agent 在共享契约下并行干活。

454 standards-grounded Claude Code skills for every PDLC role. 8 roles, 57 plugins, 173 commands. Grounded in SWEBOK, TOGAF, OWASP, ISTQB, N

Your open-source hub for 2027 tech internships and New Grad opportunities across Europe.

Can coding agents build the agent you actually want? A benchmark of 25 agent software engineering tasks across creation, editing and optimiz

Evidence-driven production readiness checklist for shipping web applications with confidence

Benchmark coding agents and agent harnesses on 226 deterministic file-editing tasks with byte-exact verification and a public leaderboard.

Production-grade software delivery for coding-agent teams on Multica — dynamic planning, deterministic execution, verifiable delivery.

A pure-Python system that automatically discovers, verifies, and applies relevant historical requirements for coding agents — no embeddings,

Production-grade vibe coding framework with specs, architecture, AI agents, testing, security, code review, CI/CD, and battle-tested workflo

AI-Native-Code开发工作流方法论：4-Phase 框架 + 空项目/已有源码两种场景 + 反模式速查。让 Claude Code 等 AI agent 在共享契约下并行干活。

Agentic AI development loop that splits Design, Code, Review, and Test into isolated roles with deterministic guardrails

Your coding agent starts every session knowing nothing about your project. One line, and it writes its own memory from your real code, then

Reusable agent skills for end-to-end software delivery, from requirements and implementation to review, testing, and release.

AI agents now operate with authority. Authority without discipline is how complex systems fail. Nuclear’s control loop, ported to AI-assiste

Claude Code skill that applies Naur's Programming as Theory Building to coding-agent workflows.

Structure-first operating process for AI coding agents: Blast / Mid / Inner build altitudes with clear ownership, then T1 structural, T2 bug

Agentic Development Environment (ADE) for the AI era