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OpenClaw

session-health-monitor

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

assistantheinrich-prog0 installations selon la source☆ 0 Étoiles du dépôtv1.1.0

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install assistantheinrich-prog/session-health-monitor

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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%...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/assistantheinrich-prog/session-health-monitor
Version
1.1.0
Commit
c95c65e27ae6556de7d64b4e9c6c03dbe6efa59e
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# 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`:

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

### 2. Create shared skill doc

Create `shared/skill-session-health.md`:

```markdown
# 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:

```markdown
**Context health check**: Run `session_status` → always append context % to Telegram messages
as footer: `📊 X% Context Window`. If Context >50%...

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