DeepSeek Agent
插件市场开发工具Aegis
DEEPSEEK HARNESS PLUGIN

Aegis

Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks.

插件介绍

Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks.

agent-skillsai-agentsai-codingarchitecture-driven-developmentawsome-coding-pluginbaseline-firstclaude-codecodexcoding-agentsdivedsh-pluginevidence-drivenfirst-principlesopencodesoftware-architecturespec-driven-developmentspec-kit

项目详情摘要

Aegis Aegis Method Pack Make your AI coding agent trustworthy: fewer reworks, safer changes, proof before "done". English · 中文 · Fast-Track Playbook · 速通秘籍 **Stop babysitting your agent.** Aegis makes your agent plan against your real baseline before it edits, prove completion with fresh evidence, and leave simple tasks alone — you get **fewer reworks, safer changes, and less blind trust in "done"**. What You Get Aegis is a method pack that makes AI coding agents work like disciplined engineers — so you don't have to watch them. **Fewer reworks.** Your agent aligns with your project's real baseline — owners, contracts, boundaries — before touching code. It stops guessing, and so do you. **Safer changes.** Measured on a frozen held-out A/B benchmark: contract pass rate **61.67% → 93.33%**, unsafe outcomes **13.33% → 0%**. **Proof before "done".** Completion claims ship with fresh verification evidence, covered scope, and residual risk. You read evidence, not vibes. **No ghost code.** Retired fallbacks and old paths are tracked or removed with a retirement trigger — technical debt stops accumulating silently. **Simple tasks stay simple.** Trivial requests stay on the fast path; ceremony only appears when the task genuinely needs it. **One method pack, every host.** The same discipline works across Codex, Claude Code, OpenCode, Kimi, and other skill-aware hosts. The numbers above are bounded advisory evidence from the frozen benchmark below, not a universal-quality or completion-authority claim. Measured Agentic Benchmark A frozen held-out A/B benchmark for Aegis 2.7.6 (2026-08-11) kept the Codex client, prompts, projects, tool policy, and requested the same `gpt-5.6-sol` / `xhigh` setting in both arms; only the Aegis projection differed. Across 120 valid runs on 20 cases,

摘自项目公开 README,可能随上游仓库更新。

安装方法

建议先在测试 Profile 中安装,并检查权限、安装脚本和依赖。

npx -p @deepseek-ai/dsh dsh plugin --profile web add github:GanyuanRan/Aegis

使用前检查

  • 确认项目符合 DSH bundle 规范,而不只是相关仓库。
  • 阅读许可证和安装脚本,检查网络、文件及执行权限。
  • 备份配置,并确保插件能够安全卸载或回滚。