CostClaw — Token Usage Optimizer#

One command. Zero setup. Real dollar amounts.

Most OpenClaw users overpay by 50-90%. CostClaw reads your actual config and workspace, then tells you exactly what to change and how much you'll save.

Why CostClaw vs Alternatives?#

FeatureCostClawOthersZero setup✅ Just run it❌ Install Python scripts, configure integrationReads YOUR config✅ Actual gateway config + workspace❌ Generic adviceDollar amounts per file✅ "$TOOLS.md costs $4.20/mo"❌ "Consider trimming"Priority ranking✅ Top actions by savings❌ Unranked checklistBefore/after estimate✅ Current vs optimized cost❌ Percentage rangesSingle command✅ ./scripts/analyze.sh❌ 4+ scripts to learn

Usage#

As an Agent (Recommended)#

When the user asks about costs, the agent should:

1. Run the analyzer script: bash

   bash scripts/analyze.sh [workspace_path]
   
   

   Default workspace: current directory. Pass explicit path if needed.

2. For JSON output (machine-readable): bash

   bash scripts/analyze.sh [workspace_path] json
   
   

3. Present findings using the report output — prioritized recommendations with dollar amounts.

Trigger Phrases#

Activate this skill when users say anything like:

• "How much am I spending on tokens?"
• "Why is my API bill so high?"
• "Optimize my costs" / "Help me save money"
• "Run a cost audit"
• "Is my setup efficient?"

What the Analyzer Checks#

1. Workspace files — Size of every .md file injected per turn, with per-file monthly cost
2. Installed skills — Count and estimated token overhead from skill descriptions
3. Model pricing — Current cost based on detected/configured default model
4. Heartbeat impact — Cost of heartbeat polling at current interval
5. Context injection total — Sum of all per-turn token overhead

Reading the Report#

The report has 5 sections:

1. 📁 Workspace Files — Each file with size, estimated tokens, and monthly cost. Flagged: ⚠ LARGE (>10K tokens), ⚡ MEDIUM (>5K tokens), ✓ OK.

2. 🔧 Skills — Count of installed skills and their aggregate token cost.

3. ⚙️ Model & Config — Detected default model and its pricing tier.

4. 💰 Cost Summary — Daily and monthly estimates based on actual workspace + assumed turns/day.

5. 📋 Ranked Recommendations — Prioritized by monthly savings. Each recommendation includes:

   • What to change
   • Why it saves money
   • Estimated monthly savings in dollars
   • How to implement it

Agent Actions After Analysis#

Based on findings, the agent should:

• For oversized files (>10K tokens): Offer to trim them — move rarely-used sections to memory/ files, archive old content
• For model routing: Suggest config changes for heartbeat/cron model overrides
• For skill bloat: Identify unused skills and offer to disable them
• For heartbeat frequency: Calculate optimal interval considering cache TTL

Pricing Reference (March 2026)#

The analyzer uses these rates. Update scripts/pricing.env to override.

ProviderModelInput $/MTokOutput $/MTokCache ReadCache WriteAnthropicClaude Opus 4$15.00$75.00$1.875$18.75AnthropicClaude Sonnet 4.5$3.00$15.00$0.30$3.75AnthropicClaude Haiku 4$0.80$4.00$0.08$1.00OpenAIGPT-4.1$2.00$8.00$0.50—OpenAIGPT-4.1 mini$0.40$1.60$0.10—OpenAIo3$2.00$8.00——OpenAIo4-mini$1.10$4.40——GoogleGemini 2.5 Pro$1.25$10.00——GoogleGemini 2.5 Flash$0.15$0.60——

Key Optimization Patterns#

1. Workspace File Trimming (Biggest Win)#

Most agents load 30-80K tokens of workspace files every turn. Trimming to essentials saves 50-80% of input costs.

2. Model Routing for Background Tasks#

Heartbeats and cron jobs don't need Opus. Route to Haiku/Flash for 10-20x savings on background work.

3. Heartbeat Cache Alignment#

Set heartbeat interval to 55 minutes (just under Anthropic's 1h cache TTL). Keeps cache warm = cache-read rates instead of cache-write rates.

4. Lazy Skill Loading#

Each skill description adds ~200-500 tokens to system prompt. 20 skills = 4-10K extra tokens/turn. Consider a skill index that loads on-demand.

5. Context Pruning#

Enable compaction.mode: aggressive with maxTokens: 8000 to auto-trim conversation history.

Privacy#

All analysis runs locally. No data leaves your machine. No API calls for the audit.

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🦞 CostClaw Pro — Deep Optimization Package#

The free analyzer gives you a ranked report. CostClaw Pro gives you the tools to automate savings:

• Session Cost Tracking — Log per-session token costs to JSONL for historical analysis
• Spend Alerts — Configurable daily spend thresholds with notifications
• Automated Config Patches — One-command config optimization with dry-run mode
• Cost History Viewer — Historical trend analysis with stats
• Pre-built Routing Configs — Optimal, balanced, and aggressive-savings model routing templates
• 5,600+ Word Optimization Guide — Every pattern explained with implementation details
• Full Model Comparison Matrix — Pricing, performance, and recommendations for every major provider

Get CostClaw Pro: https://buy.polar.sh/polar_cl_qKdQKVcwHd4TUo8jXWrDoZyjHZm3rSciMyVCG00EJlO

Storefront: https://polar.sh/morpheis

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Author: ClawdActual ( @clawdactual) License: MIT