Token Optimization for OpenClaw

Systematic guide to reduce per-turn token consumption by 70%+ without losing any functionality.

When to Use This Skill

• session_status shows Context > 30% on simple messages
• Cache hit rate is 0% or consistently low
• AGENTS.md > 5KB or MEMORY.md > 3KB
• You want to cut API costs on Anthropic models

Prerequisites

• OpenClaw 2026.3.x or later
• Access to edit openclaw.json
• At least one Anthropic model configured

---

Step 1: Audit Current State

Run session_status and record:

Cache: X% hit · Y cached, Z new
Context: Xk/200k (X%)

Then check file sizes:

wc -c ~/.openclaw/workspace/*.md

Red flags:

• Any single file > 10KB → needs splitting
• Total workspace files > 30KB → bloated
• Cache 0% → caching not enabled
• Context > 40% on simple message → pruning too loose

Step 2: Split Large Files (Layer 1)

AGENTS.md (biggest offender)

Move infrequently-needed content to separate files:

| Content | Move To | Load When | |---------|---------|-----------| | Subagent protocols | AGENTS_SUBAGENT.md | Only when spawning | | Heartbeat rules | AGENTS_HEARTBEAT.md | Only during heartbeat | | Detailed examples | memory/ directory | On demand via read |

Target: AGENTS.md ≤ 5KB

Keep only: session rules, safety, formatting, quick-reference subagent table.

Add references at the top:

> Subagent protocol → `AGENTS_SUBAGENT.md` (read on demand)
> Heartbeat protocol → `AGENTS_HEARTBEAT.md` (read during heartbeat)

MEMORY.md

Move detailed SOPs and procedures to memory/ subdirectory files. Keep only high-frequency referenced items.

Target: MEMORY.md ≤ 3KB

BOOTSTRAP.md

Delete it after initial setup. It loads every turn for zero value.

mv ~/.openclaw/workspace/BOOTSTRAP.md ~/.openclaw/workspace/BOOTSTRAP.md.bak

Verify

# Sum only files that load every turn
cat ~/.openclaw/workspace/{AGENTS,SOUL,TOOLS,IDENTITY,USER,HEARTBEAT,MEMORY}.md | wc -c
# Target: < 15KB total

Step 3: Enable Prompt Caching (Layer 2)

Add cacheRetention to each Anthropic model in openclaw.json:

{
  "agents": {
    "defaults": {
      "models": {
        "anthropic/claude-opus-4-6": {
          "params": { "cacheRetention": "long" }
        },
        "anthropic/claude-sonnet-4-6": {
          "params": { "cacheRetention": "long" }
        },
        "openrouter/anthropic/claude-3.5-sonnet": {
          "params": { "cacheRetention": "short" }
        }
      }
    }
  }
}

Values

| Value | Cache Window | Best For | |-------|-------------|----------| | none | No caching | Bursty/notification agents | | short | ~5 minutes | OpenRouter models | | long | ~1 hour | Main agent (recommended) |

Provider Support

| Provider | Support | |----------|---------| | Anthropic direct API | ✅ Full | | OpenRouter anthropic/* | ✅ Auto cache_control injection | | Bedrock Anthropic Claude | ✅ Pass-through | | Other providers | ❌ No effect |

Keep-Warm Tip

Pair cacheRetention: "long" with heartbeat at ~55 min intervals to keep cache permanently warm:

"heartbeat": {
  "every": "55m",
  "model": "your/cheap-model"
}

Step 4: Tune Context Pruning (Layer 3)

{
  "agents": {
    "defaults": {
      "contextPruning": {
        "mode": "cache-ttl",
        "ttl": "3m",
        "keepLastAssistants": 2,
        "softTrimRatio": 0.25,
        "hardClearRatio": 0.45,
        "tools": {
          "allow": ["exec", "read", "browser"],
          "deny": ["web_search", "web_fetch"]
        }
      }
    }
  }
}

Parameter Guide

| Parameter | Aggressive | Moderate | Conservative | |-----------|-----------|----------|-------------| | ttl | 2m | 3m | 5m | | keepLastAssistants | 1 | 2 | 3 | | softTrimRatio | 0.20 | 0.25 | 0.30 | | hardClearRatio | 0.40 | 0.45 | 0.50 |

Tool Deny List

Move large, one-off tool outputs to deny:

• web_fetch — page content is large and rarely reused
• web_search — search results change every time

Keep frequently reused tools in allow:

• exec — command outputs often referenced in follow-up
• read — file contents may be discussed across turns
• browser — snapshot data may be referenced

Step 5: Optimize Model Routing

Use cheap/free models for low-value tasks:

"heartbeat": {
  "every": "4h",
  "model": "your/free-flash-model"
}

| Task | Model Tier | Why | |------|-----------|-----| | Heartbeat/cron | Free/flash | Simple checks, zero cost | | Simple Q&A | Free/flash | Doesn't need intelligence | | Medium tasks | Mid-tier | Balance cost and quality | | Complex/multi-step | Premium | Worth the investment |

Step 6: Validate & Monitor

After applying all changes, restart gateway and check:

openclaw gateway restart

Then send a simple message and run session_status:

Target KPIs

| Metric | Target | Check Via | |--------|--------|-----------| | Cache Hit Rate | > 80% | Cache: X% hit | | Simple Q&A Input | < 20k tokens | Tokens: X in | | Context (idle) | < 30% | Context: Xk/200k | | Compactions/day | < 2 | Compactions: X |

Troubleshooting

| Symptom | Cause | Fix | |---------|-------|-----| | Cache still 0% | Model doesn't support caching | Check provider is Anthropic | | High cacheWrite every turn | Volatile content in system prompt | Move volatile files to on-demand | | Context > 50% quickly | Pruning too loose | Lower ttl and softTrimRatio | | Compactions > 3/day | Long conversations without pruning | Enable cache-ttl mode |

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Summary Checklist

• [ ] Audit: wc -c on workspace files + session_status
• [ ] Split: AGENTS.md ≤ 5KB, MEMORY.md ≤ 3KB
• [ ] Delete: BOOTSTRAP.md (if exists)
• [ ] Cache: cacheRetention: "long" on Anthropic models
• [ ] Prune: contextPruning with aggressive settings
• [ ] Route: Cheap model for heartbeat/simple tasks
• [ ] Validate: session_status shows cache hits + low context %
• [ ] Monitor: Weekly review of KPIs