How do I install the Clawpressor skill?

Run npx skillmds@latest add johnalbertini14-glitch/clawpressor in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Clawpressor safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Clawpressor?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Clawpressor free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Clawpressor?

johnalbertini14-glitch (@johnalbertini14-glitch) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Clawpressor by johnalbertini14-glitch

Name: Clawpressor
Rating: 4.2 (5 reviews)
Author: johnalbertini14-glitch

Clawpressor

Compress OpenClaw session context to reduce token usage and extend session lifetime. Uses NLP summarization (Sumy) to intelligently compact conversation history while preserving essential context. Triggers on mentions of session compression, token reduction, context cleanup, or when session size exceeds safe thresholds (~300KB). Use when (1) OpenClaw approaches 50% context limit, (2) Sessions are slowing down due to large context, (3) Reducing API costs from excessive token consumption, (4) Extending session lifetime without forced reboots.

File contents

ClawPressor - Session Context Compressor

Intelligently compress OpenClaw session files to reduce token usage by 85-96%.

Author: JARVIS (AI Coder) | Managed by: BeBoX License: MIT | Version: 1.0.0

Quick Start

# Preview compression without changes
python3 scripts/compress.py --dry-run

# Apply compression
python3 scripts/compress.py --apply

# Restore from backup
python3 scripts/compress.py --restore

When to Use

Situation	Action
Context at 30-40%	Plan compression soon
Context at 50%	URGENT — OpenClaw will force compact
Session > 300KB	Compress to restore performance
Slow responses	Large context likely the cause
High API costs	Compress regularly to save tokens

How It Works

Preserves recent context — Keeps last 5 messages intact for immediate context
Summarizes old messages — Uses LexRank algorithm to extract key information
Replaces with compact block — Single system message containing summary
Creates backup — Original preserved as .backup file

Prerequisites

pip install sumy
python -c "import nltk; nltk.download('punkt_tab'); nltk.download('stopwords')"

Command Reference

# Find and compress latest session (dry-run)
python3 scripts/compress.py

# Compress specific session
python3 scripts/compress.py --session /path/to/session.jsonl --apply

# Keep more recent messages (default: 5)
python3 scripts/compress.py --keep 10 --apply

# Restore if something went wrong
python3 scripts/compress.py --restore

# View compression statistics
python3 scripts/compress.py --stats

Typical Results

Metric	Before	After	Gain
Messages	168	6	-96%
Size	347 KB	12 KB	-96%
Context tokens	~50k	~8k	-84%
Session duration	~30 min	~2-3h	+400%

Integration with Workflows

In HEARTBEAT.md:

## Context Maintenance (1x/jour)
- Check session size: `ls -lh ~/.openclaw/agents/main/sessions/*.jsonl`
- If > 200KB: `python3 skills/clawpressor/scripts/compress.py --apply`

Manual check:

# See current session stats
ls -lh ~/.openclaw/agents/main/sessions/*.jsonl | head -1

Safety

Always creates .backup before compressing
--restore recovers original session
Recent messages always preserved intact
Summary stored as system message (visible to model)

Troubleshooting

Issue	Solution
"Sumy not installed"	Run `pip install sumy` and NLTK downloads
No session found	Check `~/.openclaw/agents/main/sessions/` exists
Backup not found	File may have been overwritten; no recovery
Poor summaries	Increase `--keep` to preserve more context

Credits

Coding: JARVIS (AI Assistant)
Project Management: BeBoX
Technique: NLP summarization via Sumy (LexRank algorithm)

See memory/openclaw-context-optimization.md for full strategy
Combine with SOUL_MIN/USER_MIN files for maximum efficiency

---name: clawpressordescription: Compress OpenClaw session context to reduce token usage and extend session lifetime. Uses NLP summarization (Sumy) to intelligently compact conversation history while preserving essential context. Triggers on mentions of session compression, token reduction, context cleanup, or when session size exceeds safe thresholds (~300KB). Use when (1) OpenClaw approaches 50% context limit, (2) Sessions are slowing down due to large context, (3) Reducing API costs from excessive token consumption, (4) Extending session lifetime without forced reboots.--- # ClawPressor - Session Context Compressor Intelligently compress OpenClaw session files to reduce token usage by 85-96%. **Author:** JARVIS (AI Coder) | **Managed by:** BeBoX **License:** MIT | **Version:** 1.0.0 ## Quick Start ```bash # Preview compression without changes python3 scripts/compress.py --dry-run # Apply compression python3 scripts/compress.py --apply # Restore from backup python3 scripts/compress.py --restore ``` ## When to Use | Situation | Action | |-----------|--------| | Context at 30-40% | Plan compression soon | | Context at 50% | **URGENT** — OpenClaw will force compact | | Session > 300KB | Compress to restore performance | | Slow responses | Large context likely the cause | | High API costs | Compress regularly to save tokens | ## How It Works 1. **Preserves recent context** — Keeps last 5 messages intact for immediate context 2. **Summarizes old messages** — Uses LexRank algorithm to extract key information 3. **Replaces with compact block** — Single system message containing summary 4. **Creates backup** — Original preserved as `.backup` file ## Prerequisites ```bash pip install sumy python -c "import nltk; nltk.download('punkt_tab'); nltk.download('stopwords')" ``` ## Command Reference ```bash # Find and compress latest session (dry-run) python3 scripts/compress.py # Compress specific session python3 scripts/compress.py --session /path/to/session.jsonl --apply # Keep more recent messages (default: 5) python3 scripts/compress.py --keep 10 --apply # Restore if something went wrong python3 scripts/compress.py --restore # View compression statistics python3 scripts/compress.py --stats ``` ## Typical Results | Metric | Before | After | Gain | |--------|--------|-------|------| | Messages | 168 | 6 | **-96%** | | Size | 347 KB | 12 KB | **-96%** | | Context tokens | ~50k | ~8k | **-84%** | | Session duration | ~30 min | ~2-3h | **+400%** | ## Integration with Workflows **In HEARTBEAT.md:** ```markdown ## Context Maintenance (1x/jour) - Check session size: `ls -lh ~/.openclaw/agents/main/sessions/*.jsonl` - If > 200KB: `python3 skills/clawpressor/scripts/compress.py --apply` ``` **Manual check:** ```bash # See current session stats ls -lh ~/.openclaw/agents/main/sessions/*.jsonl | head -1 ``` ## Safety - Always creates `.backup` before compressing - `--restore` recovers original session - Recent messages always preserved intact - Summary stored as system message (visible to model) ## Troubleshooting | Issue | Solution | |-------|----------| | "Sumy not installed" | Run `pip install sumy` and NLTK downloads | | No session found | Check `~/.openclaw/agents/main/sessions/` exists | | Backup not found | File may have been overwritten; no recovery | | Poor summaries | Increase `--keep` to preserve more context | ## Credits - **Coding:** JARVIS (AI Assistant) - **Project Management:** BeBoX - **Technique:** NLP summarization via Sumy (LexRank algorithm) ## Related - See `memory/openclaw-context-optimization.md` for full strategy - Combine with SOUL_MIN/USER_MIN files for maximum efficiency

Frequently asked questions