Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Session Watchdog
Monitors session context usage and saves checkpoints when approaching limits to prevent data loss before compaction or long tasks.
skill openclawclawhub Free
Monitors session context usage and saves checkpoints when approaching limits to prevent data loss before compaction or long 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
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
- xbillwatsonx
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Session Watchdog
Monitors context levels, warns before compaction, and saves checkpoints to preserve important information.
Context Thresholds
LevelTokensActionSafe0-140kNormal operationWarning140k-160kWarn user, save checkpointCritical160k-197kWarn + stop unless urgentFull197k+Compaction imminent
Check Context
Before each session and periodically during long conversations: session_status Check the contextTokens field from the response.
Checkpoint Protocol
When approaching 80% (160k tokens): Save checkpoint to memory file: Read current memory/YYYY-MM-DD.md Add key context: decisions, pending tasks, important details Write back to memory file Alert user: Say: "β οΈ Approaching context limit (~160k tokens). Saving checkpoint to memory before continuing." Ask user: Continue and accept compaction? Summarize and restart fresh? Pause until ready?
What to Save
Essential information that must survive compaction: Decisions made in this conversation Pending tasks not yet completed Important context (project state, configurations, preferences) Files modified and their paths Unresolved issues requiring follow-up
When to Trigger
At session start After every 30k tokens of conversation Before initiating large tasks (file edits, multiple operations) When user asks "how much context do we have left?"
Memory File Format
- # YYYY-MM-DD
- ## Session Checkpoint (at X% context)
- ### Decisions
- Decision 1
- Decision 2
- ### Pending
- [ ] Task 1
- [ ] Task 2
- ### Important Context
- Project state: ...
- Last file modified: ...
- ### Unresolved
- Issue needing follow-up
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 Docs
- SKILL.md