token-saver

Reduce OpenClaw AI costs with model-aware optimization. Features dynamic compaction presets based on your model's context window, intelligent file compression, and robust model detection with fallback. Supports Claude, GPT-4, Gemini, DeepSeek, and more.

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Install skill "token-saver" with this command: npx skills add rubenaquispe/token-saver

Token Saver v3

💡 Did you know? Every API call sends your workspace files (SOUL.md, USER.md, MEMORY.md, AGENTS.md, etc.) along with your message. These files count toward your context window, slowing responses and costing real money on every message.

Token Saver v3 is model-aware — it knows your model's context window and adapts recommendations accordingly. Using Gemini's 1M context? Presets scale up. On GPT-4o's 128K? Presets adjust down.

What's New in v3

Featurev2v3
Compaction presetsFixed (80K/120K/160K)Dynamic (% of model's context)
Model detectionFragile, env-onlyRobust fallback chain
Context windowsNot trackedFull registry (9 models)
Model infoHardcoded pricingJSON registry, easy updates
Already-optimizedRe-compressedSmart bypass

Commands

CommandWhat it does
/optimizeFull dashboard — files, models, context usage %
/optimize tokensCompress workspace files (auto-backup)
/optimize compactionChat compaction control (model-aware)
/optimize compaction balancedApply balanced preset (60% of context)
/optimize compaction 120Custom threshold (compact at 120K)
/optimize modelsDetailed model audit with registry
/optimize revertRestore backups, disable persistent mode

Features

📊 Model-Aware Dashboard

Shows current model, context window, and usage percentage:

🤖 Model: Claude Opus 4.5 (200K context)
   Detected: openclaw.json

📊 Context Usage: [████████░░░░░░░░░░░░] 42% (84K/200K)

📁 Workspace File Compression

Scans all .md files, shows token count and potential savings. Smart bypass skips already-optimized files.

File-aware compression:

  • SOUL.md — Light compression, keeps personality language
  • AGENTS.md — Medium compression, dense instructions
  • USER.md / MEMORY.md — Heavy compression, key:value format
  • PROJECTS.md — No compression (user structure preserved)

💬 Dynamic Compaction Presets

Presets adapt to your model's context window:

Preset% of ContextClaude 200KGPT-4o 128KGemini 1M
Aggressive40%80K51K400K
Balanced60%120K77K600K
Conservative80%160K102K800K
Off95%190K122K950K

🤖 Model Registry

24+ models with context windows, pricing, and aliases:

  • Claude: Opus 4.6 (1M), Opus 4.5, Sonnet 4.5, Sonnet 4, Haiku 4.5, Haiku 3.5 (200K)
  • OpenAI: GPT-5.2, GPT-5.1, GPT-5-mini, GPT-5-nano (256K), GPT-4.1, GPT-4o (128K), o1, o3, o4-mini
  • Gemini: 3 Pro (2M), 2.5 Pro, 2.0 Flash (1M)
  • Others: DeepSeek V3 (64K), Kimi K2.5 (128K), Llama 3.3 70B, Mistral Large

🔍 Robust Model Detection

Detection priority:

  1. Runtime injection (--model=...)
  2. Environment variables (SKILL_MODEL, OPENCLAW_MODEL)
  3. Config file (~/.openclaw/openclaw.json)
  4. File inference (TOOLS.md, MEMORY.md mentions)
  5. Fallback: Claude Sonnet 4 (safe default)

Unknown model handling:

  • Strict version matching — opus-6.5 won't fuzzy-match to opus-4.5
  • Unknown models get safe defaults (200K context) + warning
  • Easy to add new models to scripts/models.json

📝 Persistent Mode

Adds writing guidance to AGENTS.md for continued token efficiency:

FileWriting Style
SOUL.mdEvocative, personality-shaping
AGENTS.mdDense instructions, symbols OK
USER.mdKey:value facts
MEMORY.mdUltra-dense data

Safety

  • Auto-backup — All modified files get .backup extension
  • Integrity > Size — Never sacrifices meaning for smaller tokens
  • Smart bypass — Skips already-optimized files
  • Revert anytime/optimize revert restores everything
  • No external calls — All analysis runs locally

Installation

clawhub install token-saver --registry "https://www.clawhub.ai"

Version History

  • 3.0.0 — Model registry, dynamic presets, robust detection, smart bypass
  • 2.0.1 — Chat compaction, file-aware compression, persistent mode
  • 1.0.0 — Initial release

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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