Agent skill

ai-architect-lite

Lightweight playbook distilled from AI Architecture to keep dual-engine memory (.ai_context) and manifest dispatcher with minimal overhead; use when bootstrapping or porting the pattern into Claude Skills format.

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Install this agent skill to your Project

npx add-skill https://github.com/aiskillstore/marketplace/tree/main/skills/carl-312/ai-architect-lite

SKILL.md

AI Architect Lite

精简版「AI Architecture」:保留 .ai_context 记忆协议与 manifest 驱动调度,服务轻量项目或快速移植场景。

适用场景

  • 新建/迁移仓库,希望用最小开销引入 .ai_context + slash-first 调度。
  • 需要统一开发日志格式,但不启用完整 Pro 协议。
  • 想把 AI Architect 的初衷以 Claude Skill 形式交付,供其他会话直接加载。

快速上手

  1. 解析路径:PROJECT_ROOT = 当前仓库;TOOLKIT_PATH = 本技能所在目录(用于引用资源)。
  2. 检查 PROJECT_ROOT/.ai_context/03_ACTIVE_TASK.md;缺失则按 references/lite-protocol.md 模板创建或运行 python skills/project-init/entrypoint.py
  3. 阅读 03_ACTIVE_TASK.md 获取 Current Mission;若存在 01/02 则作为补充规则加载,不强制解析全部细节。
  4. 查看 .ai-manifest.json:优先使用 commands 中的 slash 触发;若无 cognitive_skills 配置,则保持纯命令模式。
  • 新手护栏:若拿不准流程,先快速浏览 references/superpowers-lite.md,按其“迷你 TDD”“快速执行模板”走一遍。
  • 仅本技能加载时的默认动作:先输出友好欢迎语,告诉用户你已启用 AI Architect Lite,并给出 3 个可选下一步(如:① 生成迷你计划 python scripts/plan_helper.py ...;② 填写/创建 .ai_context/03_ACTIVE_TASK.md;③ 用 scripts/append_log.py 记录第一次动作)。

工作流程(Loop)

  • Dispatcher 次序:Slash > Intent(可选)> 普通对话;未命中技能时按当前任务回答。
  • 迷你流程(面向新手):用 3 步走完——① 写目标/约束/<=5 步计划(可直接在回答里列出,或运行 python scripts/plan_helper.py --goal \"...\" --steps \"...\" --validation \"...\" --out - 获取模板);② 先写“会失败”的验证点(命令或检查点),再动手;③ 完成后按验证点复跑并记录结果。
  • 日志写入:优先运行 python scripts/append_log.py --note "..." --action "..." --changes "..." --outcome "..." --next "..."(随技能提供的最小脚本,默认在项目根执行并自动创建 .ai_context/03_ACTIVE_TASK.md)。若项目已有通用 skills/memory-sync/entrypoint.py,可直接复用;两者都不可用时在 03_ACTIVE_TASK.md 手动追加四段式记录。
  • 范围与安全:仅操作 PROJECT_ROOT;执行前用中文说明修改/命令目的与影响,避免写入密钥。
  • 上下文收敛:长文档/规范放入 references/,按需加载;核心指令保持在本文件。

默认问候模板(仅单独加载本技能时使用)

嗨,我是 AI Architect Lite(目前只加载了我)。为了让你轻松上手,我们可以从这三步选一:
1) 想清楚要做什么:用“迷你计划”列出目标、3 步以内的行动、以及如何确认完成(好处:先定方向,少走弯路)。
2) 准备一本“任务笔记”:如果没有 .ai_context/03_ACTIVE_TASK.md,就按 references/lite-protocol.md 的格式建一个,记录当前任务和进展(好处:状态清晰,随时可查)。
3) 留下一条“开工日志”:用 scripts/append_log.py 记下你做的第一步和结果(好处:有迹可循,方便回顾或求助)。
告诉我你的目标,或者直接挑一条开始,我会陪你一步步完成。

资源使用

  • references/lite-protocol.md.ai_context 最小规范、开发日志模板、slash-first 调度要点。
  • references/superpowers-lite.md:超能力精简卡,涵盖迷你 TDD、系统化调试和透明协作的最小做法。
  • scripts/append_log.py:为新手准备的最小日志脚本,自动建文件并按模板追加;可作为示例扩展。
  • scripts/plan_helper.py:生成目标/约束/步骤/验证的极简计划模板,默认输出到终端,避免额外文件。
  • assets/:保留占位,用于未来模板/示例;当前无需加载到上下文。

示例日志片段

markdown
### [2025-11-21 10:00] Action: 初始化 lite 协议
- Changes: 创建 .ai_context/03_ACTIVE_TASK.md;检查 .ai-manifest.json
- Outcome: 完成;未运行测试
- Next: 按当前任务执行并在每步后同步日志

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