openclaw / context-budgeting
Install for your project team
Run this command in your project directory to install the skill for your entire team:
mkdir -p .claude/skills/context-budgeting && curl -L -o skill.zip "https://fastmcp.me/Skills/Download/3870" && unzip -o skill.zip -d .claude/skills/context-budgeting && rm skill.zipProject Skills
This skill will be saved in .claude/skills/context-budgeting/ and checked into git. All team members will have access to it automatically.
Important: Please verify the skill by reviewing its instructions before using it.
Manage and optimize OpenClaw context window usage via partitioning, pre-compression checkpointing, and information lifecycle management. Use when the session context is near its limit (>80%), when the agent experiences "memory loss" after compaction, or when aiming to reduce token costs and latency for long-running tasks.
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---
name: context-budgeting
description: Manage and optimize OpenClaw context window usage via partitioning, pre-compression checkpointing, and information lifecycle management. Use when the session context is near its limit (>80%), when the agent experiences "memory loss" after compaction, or when aiming to reduce token costs and latency for long-running tasks.
---
# 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.