Build Your Multi-Agent System: Local Docker to Production with AgentOS
6 days ago 高效码农✅ Build Your Own Multi-Agent System: Local Docker Setup to Production Deployment with AgentOS Abstract This guide shows you exactly how to build a production-ready multi-agent system using AgentOS. The system includes learning agents that remember interactions and improve over time, PostgreSQL-backed persistence for state, sessions, and memory, Agentic RAG for intelligent knowledge retrieval, MCP Tools for connecting external services, and full visibility through the AgentOS control plane. You’ll run the complete system locally with Docker in 5 minutes and deploy it to production on Railway in under 20 minutes. The system features three ready-to-use agents—Pal (personal second brain), Knowledge …
SWE-Pruner Breaks the Context Wall: How to Slash AI Coding Agent Costs by 54%
7 days ago 高效码农Breaking the “Context Wall” for Code Agents: A Deep Dive into SWE-Pruner’s Adaptive Context Pruning In the current landscape of software development, Large Language Model (LLM)-based agents are demonstrating remarkable capabilities, navigating codebases, running tests, and submitting patches end-to-end. However, as these capabilities grow, a critical “Context Wall” problem has emerged: the accumulation of long interaction contexts within LLMs is driving up API costs and introducing severe latency. Existing compression methods often compromise code syntax or discard critical debugging details. This article explores SWE-Pruner, a framework that mimics human “selective skimming” to provide task-aware, adaptive context pruning for coding agents. …
PolyMCP Guide: Transform AI Development with Modular Command Platforms
8 days ago 高效码农Comprehensive Guide to PolyMCP: Unlocking AI-Driven Development Efficiency Core Value Analysis What is PolyMCP? PolyMCP represents a groundbreaking toolkit designed to streamline the development of modular command platforms (MCP). It integrates Python functions, third-party services, and large language models (LLMs) through a unified interface supporting HTTP, stdio, and in-process communication. This solution empowers developers to create automated workflows across heterogeneous tools while ensuring production-grade security and observability[^1.1^][^3.2^]. Key Technical Advantages: Dual Language Support: Compatible with both Python and TypeScript ecosystems. LLM Integration: Native support for OpenAI, Anthropic (Claude), Ollama, and other providers. Visual Monitoring: PolyMCP Inspector enables real-time tracking of …
Integrate Feishu into Your Chatbot: The Complete clawd-feishu Plugin Guide
9 days ago 高效码农How to Integrate Feishu into Your Chatbot: The Complete Guide to the clawd-feishu Plugin This guide aims to answer one core question: How can you quickly and securely connect your Clawdbot intelligent assistant to the Feishu (or Lark) workplace platform? We will walk through the entire integration process from zero to one using the official @m1heng-clawd/feishu plugin, and delve into best practices for different configuration scenarios. Why Choose Feishu as a Communication Channel for Your Bot? Before diving into the technical details, it’s valuable to understand the “why.” Feishu, as a collaboration platform integrating instant messaging, calendar, docs, and video …
Qwen3-Max-Thinking: The Breakthrough in AI Reasoning & Autonomous Tool Use
9 days ago 高效码农Qwen3-Max-Thinking: The Next Evolution in Reasoning-Capable Large Language Models Image source: Unsplash What exactly is Qwen3-Max-Thinking, and what tangible breakthroughs does it deliver in the large language model landscape? Qwen3-Max-Thinking represents the latest flagship reasoning model from the Tongyi Lab, engineered through expanded parameter scale and intensive reinforcement learning training to deliver significant performance improvements across factual knowledge, complex reasoning, instruction following, human preference alignment, and agent capabilities. Benchmark evaluations across 19 authoritative tests demonstrate its competitive standing alongside industry leaders including GPT-5.2-Thinking, Claude-Opus-4.5, and Gemini 3 Pro. Beyond raw performance metrics, this model introduces two pivotal innovations that enhance …
Local AI Revolution: How Clawdbot’s 565+ Skills Transform Development Workflows
9 days ago 高效码农# Comprehensive Guide to Clawdbot Skills: How 565+ Local AI Capabilities Revolutionize Development & Workflows Clawdbot is a powerful, locally-hosted AI assistant that runs directly on your machine. Its core strength lies in extending its capabilities through “skills”—mechanisms that allow the AI to interact with external services, automate complex workflows, and execute highly specialized tasks. This article provides an in-depth exploration of this massive, community-built ecosystem, explaining how installing and configuring these tools can transform your local computer into a fully-functional, all-in-one workstation. ## The Core Value of Clawdbot and Its Skill Ecosystem Core Question Answered: What unique value do …
Zero-Cost Claude Code: Unlock Agentic Coding with Ollama & Open-Source Models
9 days ago 高效码农Zero-Cost Claude Code: Unlock the Full Potential of Agentic Coding with a Local Ollama Server Abstract: Anthropic’s Claude Code coding tool is now available for $0 cost. Simply point it to a local Ollama server and pair it with an open-source coding model (e.g., qwen2.5-coder) to retain its original workflow and CLI experience, eliminate API fee constraints, and lower the barrier to using intelligent coding tools. Introduction: The Intelligent Coding Tool Trapped by API Costs If you’re a developer, you’ve likely heard of—if not tried—Claude Code, Anthropic’s intelligent coding tool. With its powerful agentic workflow, it can assist with tasks …
AI Coding Assistant Benchmark: Shocking Data Reveals How to Choose the Most Efficient Programming Partner
9 days ago 高效码农AI Coding Assistant Benchmark Analysis: How to Quantify and Choose Your Intelligent Programming Partner Recently, in discussions with fellow developers about AI programming assistants, our conversations often circled back to “subagents,” system prompt optimization, and various execution frameworks. The much-talked-about “oh-my-opencode” plugin, in particular, raised questions about its practical value and efficiency. Spurred by a friendly challenge to “build a better one,” I decided to act on an idea I had been pondering since summer: creating a system of controllable, steerable subagents, moving away from the “fire-and-forget” text-based approach. As a developer driven by data, I believe “what gets measured, …
Claude-Mem: How to Make AI Remember Your Last Session & Boost Productivity
11 days ago 高效码农Claude-Mem: Turn One-Off Chats into Perpetual Project Memory “ Core question answered in one line: How can Claude remember what we did last time, even after a full restart? Claude-Mem quietly captures every tool call, compresses it into searchable observations, and surfaces the right context when you ask—no manual notes, no copy-paste. Quick Start: Three Commands to Persistent Memory Core question: What is the absolute fastest way to get memory running? Install the plugin, restart Claude Code, and speak naturally—memory appears in under two minutes. Step Command What happens Typical time 1 /plugin marketplace add thedotmack/claude-mem Adds plugin index 8 …
How to Run a Local AI Coding Assistant Like Claude: 100% Free & Private Setup
12 days ago 高效码农How to Run a Claude Code-like AI Programming Assistant Locally (100% Free & Fully Private) Have you ever wished for a powerful AI programming assistant like Claude Code but worried about code privacy, API costs, or simply wanted to work in an offline environment? Today, we’ll walk through the steps to deploy a fully functional AI coding agent entirely on your own computer. The entire process requires no internet connection, incurs no cloud service fees, and guarantees 100% privacy for all your code and data. This article details how to use open-source tools and models to build a local AI …
Bash-First Revolution: How the Claude Agent SDK Builds Autonomous AI That Actually Works
13 days ago 高效码农「The “Bash-First” Revolution: A Deep Dive into the Claude Agent SDK and the Future of Autonomous Agents」 「Snippet/Summary」: The Claude Agent SDK is a developer framework by Anthropic, built on the foundations of Claude Code, designed to create autonomous agents that can manage their own context and trajectories. It advocates for a “Bash-first” philosophy, prioritizing Unix primitives over rigid tool schemas. By utilizing a core loop of gathering context, taking action, and verifying work through deterministic rules and sub-agents, the SDK enables AI to execute complex, multi-step tasks in isolated sandboxes. 「I. Beyond Chatbots: The Shift to Autonomous AI」 If …
How to Use add-skill: Instantly Boost Your AI Coding Agents in 2026
13 days ago 高效码农How to Use add-skill to Instantly Add Powerful Skills to Your AI Coding Agents If you’re working with AI coding assistants like Cursor, Claude Code, OpenCode, Codex, GitHub Copilot, or any of the other 20+ supported tools in 2026, you’ve probably noticed something: they’re incredibly capable generalists, but they often need specific guidance to match your team’s conventions, project standards, or workflow preferences. That’s where Agent Skills come in — a shared, open format that packages reusable instructions into neat, portable modules. Each skill lives in its own folder with one key file: SKILL.md. Inside that file you’ll find clear …
Testing AI Agent Skills: From Vibes to Verdicts with Lightweight Evals
13 days ago 高效码农From Vibes to Verdicts: A Repeatable Workflow for Testing Agent Skills with Lightweight Evals “ What’s the shortest path to know if my AI agent skill actually improved—or just started failing quietly? Run a micro-eval: prompt → capture the trace → score with deterministic checks → lock the behavior in version control. What This Article Answers Why do “vibes” fail when iterating on LLM agent skills? How can I turn “it feels faster” into a repeatable lab experiment? What exact commands and scripts (all in the source file) glue the pipeline together? Where do deterministic checks end and model-graded rubrics …
Claude Code Real-World Guide: 10 Insider Tips & Pitfalls to Avoid
14 days ago 高效码农Claude Code High-Intensity Real-World Experience: Top 10 Takeaways & Pitfall Guide (Part 1) Article Snippet Based on extensive, real-world usage, this article details ten core insights for using Claude Code effectively. It covers account management, bug recovery, context compression, custom Skills creation, SubAgent strategies, background tasks, subscription plan selection, and toolchain configuration (MCP vs. CLI). This guide provides verified, in-depth, and practical advice for developers seeking to integrate Claude Code into their high-intensity workflows efficiently and avoid common frustrations. If you’re looking for a grounded, real-world report on Claude Code—not a surface-level feature list—you’ve found it. This article isn’t based …
Sweep Next-Edit: The 1.5B Parameter Code Autocomplete Model That Outperforms Giants Like Qwen-8B
14 days ago 高效码农Open-Source 1.5B Parameter Next-Edit Code Autocomplete Model: Performance, Design, and Practice For programmers, code autocomplete tools have long been an indispensable part of daily development. An efficient and accurate autocomplete model can significantly reduce repetitive coding work and boost productivity. Conversely, slow, low-accuracy tools or those requiring code to be uploaded to the cloud not only disrupt development workflows but also pose potential data privacy risks. Today, we introduce Sweep Next-Edit—an open-source 1.5B parameter code autocomplete model designed to address these pain points. It runs locally on laptops in under 500ms and outperforms models over 4x its size on core …
Building Production-Grade AI Applications? Mastra TypeScript Framework is Your Ultimate Stack
14 days ago 高效码农Mastra is a TypeScript framework designed for building AI-powered applications and agents. It enables developers to connect to over 40 model providers through a single interface, featuring autonomous agents, graph-based workflows, human-in-the-loop capabilities, and built-in observability for reliable production deployment. Building Production-Grade AI Applications with Mastra: The Ultimate TypeScript Framework In the rapidly evolving landscape of software development, the integration of Artificial Intelligence (AI) has shifted from a competitive advantage to an absolute necessity. Developers today are not just asked to write code; they are asked to orchestrate intelligence. However, the journey from a simple prototype to a robust, production-ready …
Unlock Hidden PostgreSQL Speed: 3 Unconventional Optimization Techniques You’re Missing
14 days ago 高效码农Unlock PostgreSQL Performance: 3 Unconventional Optimization Techniques When it comes to database optimization, most developers rely on the same familiar toolkit—tweaking queries, adding indexes to columns, denormalizing data, and repeating cycles of analyzing, vacuuming, and clustering. Conventional methods work, but thinking outside the box can deliver transformative performance gains for PostgreSQL. In this article, we’ll break down three practical yet underutilized PostgreSQL optimization strategies: eliminating pointless full table scans, optimizing indexes for low-cardinality scenarios, and enforcing uniqueness with hash indexes. Each addresses real-world performance pain points with actionable solutions. I. Eliminate Meaningless Full Table Scans with Check Constraints In daily …
GLM-4.7-Flash: Ultimate Guide to Deploying the 30B MoE AI Model Locally
15 days ago 高效码农GLM-4.7-Flash: A Complete Guide to Local Deployment of the High-Performance 30B Mixture of Experts Model GLM-4.7-Flash model logo In today’s AI landscape, large language models have become indispensable tools for developers and researchers. Among the latest innovations stands GLM-4.7-Flash—a remarkable 30 billion parameter Mixture of Experts (MoE) model designed specifically for local deployment. What makes this model truly stand out is its ability to deliver exceptional performance while requiring surprisingly modest hardware resources. If you’ve been searching for a powerful AI model that can run entirely on your personal hardware without compromising on capabilities, GLM-4.7-Flash might be exactly what you …
Distributed Agent Orchestration & AI: How the Engineering Bottleneck Has Shifted Forever
15 days ago 高效码农AI and Distributed Agent Orchestration: What Jaana Dogan’s Tweet Reveals About the Future of Engineering A few days ago, Jaana Dogan, a Principal Engineer at Google, posted a tweet: “Our team spent an entire year last year building a distributed Agent orchestration system—exploring countless solutions, navigating endless disagreements, and never reaching a final decision. I described the problem to Claude Code, and it generated what we’d been working on for a year in just one hour.” This tweet flooded my Timeline for days. What’s interesting is that almost everyone could find evidence to support their own takeaways from it. Some …
AI-Powered Dependency Management: How Maven Tools MCP Solves JVM Project Upgrades in Seconds
16 days ago 高效码农Maven Tools MCP: Redefining Dependency Management for JVM Projects with AI Intelligence In the rapidly evolving landscape of software development, dependency management has become a critical bottleneck. This blog explores Maven Tools MCP, an AI-powered solution that revolutionizes how developers handle JVM project dependencies. By integrating cutting-edge technology with practical usability, MCP addresses pain points like version conflicts, breaking changes, and security vulnerabilities—all while aligning with modern SEO and AI generation best practices. 🔍 The Problem: Why Traditional Dependency Management Fails Developers often face these challenges when upgrading frameworks: Time-Consuming Research: Manually navigating Maven Central or reading migration guides consumes …