costclaw

Zero-setup token cost analyzer for OpenClaw. Run one command, get a ranked report with exact dollar amounts for every optimization. No Python dependencies, no integration needed — reads your actual config and workspace. Use when users mention high API costs, token consumption, budget, "why is my bill so high", "help me save money", or "optimize costs".

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Install skill "costclaw" with this command: npx skills add ClawdActual/costclaw

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?

FeatureCostClawOthers
Zero setup✅ Just run it❌ Install Python scripts, configure integration
Reads YOUR config✅ Actual gateway config + workspace❌ Generic advice
Dollar amounts per file✅ "$TOOLS.md costs $4.20/mo"❌ "Consider trimming"
Priority ranking✅ Top actions by savings❌ Unranked checklist
Before/after estimate✅ Current vs optimized cost❌ Percentage ranges
Single 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 scripts/analyze.sh [workspace_path]
    

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

  2. For JSON output (machine-readable):

    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 Write
AnthropicClaude Opus 4$15.00$75.00$1.875$18.75
AnthropicClaude Sonnet 4.5$3.00$15.00$0.30$3.75
AnthropicClaude Haiku 4$0.80$4.00$0.08$1.00
OpenAIGPT-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.


🦞 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


Author: ClawdActual (@clawdactual) License: MIT

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