Context Budgeting Skill

This skill provides a systematic framework for managing the finite context window (RAM) of an OpenClaw agent.

Core Concepts

1. Information Partitioning

• Objective/Goal (10%): Core task instructions and active constraints.
• Short-term History (40%): Recent 5-10 turns of raw dialogue.
• Decision Logs (20%): Summarized outcomes of past steps ("Tried X, failed because Y").
• Background/Knowledge (20%): High-relevance snippets from MEMORY.md.

2. Pre-compression Checkpointing (Mandatory)

Before any compaction (manual or automatic), the agent MUST:

1. Generate Checkpoint: Update memory/hot/HOT_MEMORY.md with:
   • Status: Current task progress.
   • Key Decision: Significant choices made.
   • Next Step: Immediate action required.
2. Run Automation: Execute scripts/gc_and_checkpoint.sh to trigger the physical cleanup.

Automation Tool: gc_and_checkpoint.sh

Located at: skills/context-budgeting/scripts/gc_and_checkpoint.sh

Usage:

• Run this script after updating HOT_MEMORY.md to finalize the compaction process without restarting the session.

Integration with Heartbeat

Heartbeat (every 30m) acts as the Garbage Collector (GC):

1. Check /status. If Context > 80%, trigger the Checkpointing procedure.
2. Clear raw data (e.g., multi-megabyte JSON outputs) once the summary is extracted.

🚀 30 秒快速开始

# 基础用法
# TODO: 添加具体命令示例

📋 何时使用

当以下情况时使用此技能：

1. 场景 1
2. 场景 2
3. 场景 3

🔧 配置

必需配置

# 环境变量或配置文件

可选配置

# 可选参数

💡 实际应用场景

场景 1: 基础用法

# 命令示例

场景 2: 进阶用法

# 命令示例

🧪 测试

# 运行测试
python3 scripts/test.py

⚠️ 故障排查

常见问题

问题： 描述问题

解决方案：

# 解决步骤

📚 设计原则

本技能遵循 Karpathy 的极简主义设计哲学：

1. 单一职责 - 只做一件事，做好
2. 清晰可读 - 代码即文档
3. 快速上手 - 30 秒理解用法
4. 最小依赖 - 只依赖必要的库
5. 教育优先 - 详细的注释和示例

最后更新：2026-03-16 | 遵循 Karpathy 设计原则

🏷️ 质量标识

备注: 本技能已在 2026-03-16 批量优化中完成优化，遵循 Karpathy 设计原则。