Install
openclaw skills install costclawCostClaw — Token Cost Analyzer for OpenClaw
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".
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?
| Feature | CostClaw | Others |
|---|---|---|
| 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:
-
Run the analyzer script:
bash scripts/analyze.sh [workspace_path]Default workspace: current directory. Pass explicit path if needed.
-
For JSON output (machine-readable):
bash scripts/analyze.sh [workspace_path] json -
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
- Workspace files — Size of every .md file injected per turn, with per-file monthly cost
- Installed skills — Count and estimated token overhead from skill descriptions
- Model pricing — Current cost based on detected/configured default model
- Heartbeat impact — Cost of heartbeat polling at current interval
- Context injection total — Sum of all per-turn token overhead
Reading the Report
The report has 5 sections:
-
📁 Workspace Files — Each file with size, estimated tokens, and monthly cost. Flagged: ⚠ LARGE (>10K tokens), ⚡ MEDIUM (>5K tokens), ✓ OK.
-
🔧 Skills — Count of installed skills and their aggregate token cost.
-
⚙️ Model & Config — Detected default model and its pricing tier.
-
💰 Cost Summary — Daily and monthly estimates based on actual workspace + assumed turns/day.
-
📋 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.
| Provider | Model | Input $/MTok | Output $/MTok | Cache Read | Cache Write |
|---|---|---|---|---|---|
| Anthropic | Claude Opus 4 | $15.00 | $75.00 | $1.875 | $18.75 |
| Anthropic | Claude Sonnet 4.5 | $3.00 | $15.00 | $0.30 | $3.75 |
| Anthropic | Claude Haiku 4 | $0.80 | $4.00 | $0.08 | $1.00 |
| OpenAI | GPT-4.1 | $2.00 | $8.00 | $0.50 | — |
| OpenAI | GPT-4.1 mini | $0.40 | $1.60 | $0.10 | — |
| OpenAI | o3 | $2.00 | $8.00 | — | — |
| OpenAI | o4-mini | $1.10 | $4.40 | — | — |
| Gemini 2.5 Pro | $1.25 | $10.00 | — | — | |
| Gemini 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