Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Context Budgeting
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.
skill openclawclawhub Free
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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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/gc_and_checkpoint.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- SarielWang93
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Context Budgeting Skill
This skill provides a systematic framework for managing the finite context window (RAM) of an OpenClaw agent.
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: Generate Checkpoint: Update memory/hot/HOT_MEMORY.md with: Status: Current task progress. Key Decision: Significant choices made. Next Step: Immediate action required. 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): Check /status. If Context > 80%, trigger the Checkpointing procedure. Clear raw data (e.g., multi-megabyte JSON outputs) once the summary is extracted.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/gc_and_checkpoint.sh