SkillHub

session-health-monitor

v1.1.0

Context window health monitoring for OpenClaw agents — threshold warnings via Telegram, pre-compaction snapshots, and memory rotation.

Sourced from ClawHub, Authored by assistantheinrich-prog

Installation

Please help me install the skill `session-health-monitor` from SkillHub official store. npx skills add assistantheinrich-prog/session-health-monitor

Session Health Monitor

Monitor your OpenClaw agent context window health, get warnings via Telegram when usage is high, save critical facts before compaction, and keep memory directories clean.

Overview

Four capabilities for OpenClaw agent sessions:

  1. Context Threshold Warnings — Agents append usage footer to Telegram messages and warn at configurable thresholds
  2. Compaction Detection — Track usage drops to infer when context was compacted
  3. Pre-Compaction Snapshots — Save key facts and decisions to daily memory files before they're lost
  4. Memory Rotation — Archive old daily memory files to prevent clutter

Quick Setup (OpenClaw)

1. Add shared skill reference

Add to your shared/INDEX.md:

| Context window health, compaction detection, pre-compaction snapshots | `skill-session-health.md` |

2. Create shared skill doc

Create shared/skill-session-health.md:

# Session Health Monitor

## Context Health Thresholds
| Level  | Condition                          | Action                        |
|--------|------------------------------------|-------------------------------|
| GREEN  | <50% used AND 0 compactions        | Normal operation              |
| YELLOW | >=50% used OR >=1 compaction       | Save key facts via snapshot   |
| RED    | >=75% used OR >=2 compactions      | Save facts NOW, session ending|

## Behavioral Rules
1. When context reaches YELLOW+, extract 3-5 key facts (decisions, files changed, blockers)
2. Run: `bash scripts/snapshot.sh "fact1" "fact2"`
3. Append footer to Telegram messages at YELLOW+: `X% Context Window | Nx compacted`
4. Do this BEFORE session ends or context gets compacted
5. After any detected compaction, immediately snapshot what you remember

3. Add heartbeat step

Add to your agent heartbeat/loop:

**Context health check**: Run `session_status` → always append context % to Telegram messages
as footer: `📊 X% Context Window`. If Context >50% OR Compactions >=1, add:
"⚠️ consider /restart after current task." If Context >75% OR Compactions >=2, flag as urgent.

Context Health Thresholds

Level Condition Action
GREEN <50% used AND 0 compactions Normal operation
YELLOW >=50% used OR >=1 compaction Consider saving key facts
RED >=75% used OR >=2 compactions Save facts NOW, session ending

Agents append a footer to every outgoing Telegram message:

📊 42% Context Window                          # GREEN — no extra warning
📊 63% Context Window | 1x compacted           # YELLOW — consider restart
⚠️ 📊 81% Context Window | 2x compacted        # RED — urgent, save facts

This keeps the user informed about session health without requiring manual checks.

Pre-Compaction Snapshot Protocol

When context reaches YELLOW or above, the agent SHOULD:

  1. Extract 3-5 key facts from the current session (decisions made, files changed, blockers found)
  2. Write them to memory/YYYY-MM-DD.md using scripts/snapshot.sh
  3. Include any unfinished work or next steps
  4. Do this BEFORE the session ends or context is compacted

Example snapshot content:

## Pre-Compaction Snapshot (14:32)
- Refactored auth module to use JWT instead of sessions (files: src/auth.ts, src/middleware.ts)
- Bug found in rate limiter: counter resets on deploy, not on TTL expiry
- Next: write tests for new auth flow, fix rate limiter reset logic
- Decision: using RS256 for JWT signing (user preference)

When to trigger: - Context hits 50%+ for the first time in a session - After any detected compaction - Before ending a long session - When the agent detects it has accumulated significant context

Scripts Reference

context-check.sh

Standalone health check, useful in heartbeat loops.

bash scripts/context-check.sh                    # Human-readable output
bash scripts/context-check.sh --json              # Machine-readable JSON
echo '{"context_window":{"used_percentage":72}}' | bash scripts/context-check.sh
# Exit codes: 0=GREEN, 1=YELLOW, 2=RED

snapshot.sh

Save facts to daily memory file.

bash scripts/snapshot.sh "Fact one" "Fact two" "Fact three"
echo -e "Fact onenFact two" | bash scripts/snapshot.sh -

rotate.sh

Archive old daily memory files.

bash scripts/rotate.sh           # Archives files older than 3 days (default)
KEEP_DAYS=7 bash scripts/rotate.sh  # Keep 7 days instead

Configuration

All configuration is via environment variables with sensible defaults:

Variable Default Description
MEMORY_DIR Auto-detect (see below) Where to write daily memory files
KEEP_DAYS 3 Days to keep before archiving
HEALTH_GREEN_MAX 50 Max % for GREEN status
HEALTH_RED_MIN 75 Min % for RED status
COMPACTION_DROP 30 % drop that indicates compaction

Memory directory auto-detection order: 1. $MEMORY_DIR environment variable 2. ~/.openclaw/workspace/memory (if exists) 3. ~/.claude/memory (fallback)

Troubleshooting

jq not installed

# macOS
brew install jq
# Linux
sudo apt-get install jq

Reset compaction state

rm /tmp/session-health-*.json
  1. Check shared/INDEX.md references skill-session-health.md
  2. Check heartbeat includes the context health step
  3. Verify session_status tool is available to the agent