feat(autoresearch): 注册 autoresearch v0.1.0 自主实验循环插件 - #1
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- plugins/autoresearch/: 完整插件（MCP server + hooks + skills + commands，Node 标准库零依赖） - marketplace.json: 注册条目（category developer-tools，author luochang212） - assets/autoresearch/icon.png + icon-sources.json: 原创图标（源 SVG 见贡献者仓库 assets/icon.svg）
- 全部 .mjs → .ts：MCP server、lib（含新增 types.ts 领域类型）、hooks、测试 - 运行时零依赖不变：Node 原生剥离类型，无构建步骤 - README 同步更新（Node ≥24、目录结构、测试命令）
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写给 zcode 的 autoresearch 插件 调研了市面上比较流行的 autoresearch 插件（主要是 pi、codex、claude code），分析它们的原理和生效机制，并让 AI（主要是 glm-5.3 和 deepseek-v4-flash）通过 spec-driven 的方式，开发新功能。为了保证开发出的能力适配 zcode，在开发之前还对 zcode 提供的能力做了调研，并实际调用 zcode 进行验证。目前 zcode-autoresearch 的版本是 v0.1.0。对于这一版，我用多个 AI 验核，确认已经实现主流 autoresearch 提供的功能。后续版本会根据在真实的环境中使用获得的反馈，持续提升 autoresearch 的效率和稳定性。 开源方式：MIT GitHub: https://github.com/luochang212/zcode-autoresearch |
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注册 autoresearch v0.1.0 — ZCode 自主实验循环插件
解决的用户问题
ZCode 缺少「自主实验循环」能力：让 coding agent 在固定机械度量上自主迭代优化（改代码 → 跑基准 → keep / discard → 循环），并内置防作弊护栏。本插件基于 karpathy/autoresearch 与 pi-autoresearch 的调研（见插件 README 与研究记录）做了 ZCode 原生实现。
用户可见行为与测试方式
init_experiment/run_experiment/log_experiment/export_dashboard/clear_experiments）、5 个命令、5 个 hooks 与autoresearchskillnode --test单测（60 个用例全过）；本仓库 CI 的validate.py+build_dist.py+ unittest 套件均已通过版本与市场注册
autoresearchv0.1.0，.zcode-plugin/plugin.json与根marketplace.json条目（name / version / description）一致developer-tools；author:luochang212依赖、网络、权限与副作用
.auto/measure.sh）与正确性门禁（.auto/checks.sh）；自动 git 操作（keep 提交、非 keep 回滚，.auto/豁免）；安装 5 个 ZCode hooks（Stop 续跑、PreToolUse 写保护、PermissionRequest 门禁、UserPromptSubmit/SessionStart 记忆注入）；export_dashboard起本地 127.0.0.1 HTTP 服务；写入项目目录下的.auto/会话状态第三方来源与许可证
assets/icon.svg），已登记于assets/icon-sources.json（附 sha256）