技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: swe-agent

英文目录

SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

20K
Stars
87/100
信任
分类: coding-agents审计

An Open-Source Asynchronous Coding Agent

10.0K
Stars
81/100
信任
分类: coding-agents审计

A simple SWE style browser agent framework that achieves SOTA results on long horizon web tasks.

5.5K
Stars
84/100
信任
分类: agent-frameworks审计

The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no huge configs, no giant monorepo—but scores >74% on SWE-bench verified!

5.3K
Stars
80/100
信任
分类: agent-frameworks审计

A FREE pragmatic DevOps learning to kickstart your DevOps career and knowledge in the Cloud Native era following the Agile MVP style! ⭐ (2026 plans for DevOps, Cloud, Platform, SRE, SWE)

2.4K
Stars
83/100
信任
分类: devops审计

Kodezi Chronos is a debugging-first language model that achieves state-of-the-art results on SWE-bench Lite (80.33%) and 67% real-world fix accuracy, over six times better than GPT-4. Built with Adaptive Graph-Guided Retrieval and Persistent Debug Memory. Model available Q1 2026 via Kodezi OS.

4.9K
Stars
73/100
信任
分类: ml-automation审计

A Claude Code plugin that automates a multi-agent software development pipeline from feature spec to reviewed PR.

136
Stars
75/100
信任
分类: coding-agents审计

Autonomous software engineering fleet of AI agents for production-grade PRs on AgentField: plan, code, test, and ship.

969
Stars
74/100
信任
分类: agent-frameworks审计

Measuring frontier coding agents on original, long-horizon engineering tasks

944
Stars
67/100
信任
分类: coding-agents审计

This repo tracks the opened and merged PRs by the top SWE coding agents by OpenAI, GitHub, and others. Updates regularly.

300
Stars
67/100
信任
分类: coding-agents审计

Official AHE code — Agentic Harness Engineering: observability-driven automatic evolution of coding-agent harnesses (concurrent w/ meta-harness). NexAU-AHE reaches 84.7% ± 2.1 pass@1 on Terminal-Bench 2 (GPT-5.5). Lifts GPT-5.4 69.7→77.0% over 10 iters, beats Codex/ACE/Training-Free GRPO; frozen harness transfers to SWE-bench-Verified.

600
Stars
69/100
信任
分类: coding-agents审计

[ICML 2026] RLAnything & DemyAgent: General and scalable agentic RL algorithms across terminal, GUI, SWE, and tool-call settings

585
Stars
69/100
信任
分类: agent-frameworks审计