搜索

PythonReactSEOPDF
GitHub Skill

memory-keeper

Manages project structure, auto-saves artifacts, and performs recovery protocols. Use this skill at the end of tasks or when encountering errors.

mr-phariyawit☆ 0 仓库 Stars0 仓库 Forks

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

查看来源 ↗使用指南

技能说明

Memory Keeper Skill

Purpose

To ensure the Structural Memory of the agent is preserved, artifacts are backed up, and the agent can recover from context limits.

Trigger Conditions

  • Task completion (finishing a feature).
  • User mentions /retro or "save memory".
  • Agent encounters "Agent terminated due to error" or "Context Limit" errors.

Workflow Rules

1. Structural Integrity Check
  • Verify agent/rules/ exists.
  • Verify docs/ exists.
  • Verify .memory/ exists.
    • Action: If missing, suggest running init-project or creating them.
2. Auto-Save Protocol

When a major task is done:

  1. Format Timestamp: YYMMDD_HHMM.
  2. Target Directory: .memory/[Timestamp]_[TaskName]/.
  3. Action: Copy key artifacts (task.md, implementation_plan.md, spec.md) to this folder.
    • Note: Do not perform the copy yourself if it's too heavy. Just remind the user or create a script.
3. Recovery Protocol (Agent Terminated Handler)

If the Agent is slow, buggy, or hits token limits:

  1. Advise User: "I am hitting context limits. Recommendation: Factory Reset."
  2. Command: Suggest running:
    ./antigravity_toolkit.sh full
    
  3. Post-Reset: Remind user to:
    • "Import rules and workflows" immediately after reset.

使用示例

查看来源仓库中的使用示例与配置说明。

查看来源 ↗

来源历史

收录时间
2026-01-20
索引更新时间
2026-01-26
Branch
main

收录与同步日期属于本站记录。源码修改历史请查看来源仓库。

GitHub ↗

chat Comments (0)

chat_bubble_outline

No comments yet. Be the first to share your thoughts!