Api Cost Optimizer
📖 技能介紹
name: api-cost-optimizer description: "Analyze OpenClaw agent configuration and API usage patterns to identify cost-saving opportunities. Diagnose inefficient heartbeat configs, estimate daily/weekly API spend, and generate actionable recommendations to reduce LLM API costs. Essential for any agent operator running 24/7 on a budget. Use when: agent costs are higher than expected, heartbeat config needs review, or monthly API bill surprises you." metadata: { "openclaw": { "requires": { "bins": ["curl", "python3"] }, "install": [], }, }
API Cost Optimizer
Diagnose, estimate, and optimize LLM API costs for OpenClaw agents running 24/7.
What This Skill Does
- Estimates API spend from agent configuration (model, heartbeat interval, task complexity)
- Diagnoses heartbeat waste — the #1 cause of runaway API bills
- Counts and categorizes tools the agent has access to
- Produces a cost report with prioritized recommendations
- Estimates time-to-payback for any recommended changes
The Problem This Solves
Documented cases show agents burning $8–$250 per week in API costs due to misconfigured heartbeats and inefficient task patterns. A properly tuned heartbeat alone can reduce costs by 60–90%.
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
API_COST_MODEL |
No | openai |
Provider: openai, anthropic, minimax, lmstudio |
API_COST_INTERVAL |
No | weekly |
Report interval: daily, weekly, monthly |
HEARTBEAT_INTERVAL |
No | auto |
Override heartbeat interval in seconds (auto-detect if not set) |
MODEL_PRICE_INPUT |
No | auto | Price per 1M input tokens (auto-selected by provider) |
MODEL_PRICE_OUTPUT |
No | auto | Price per 1M output tokens (auto-selected by provider) |
Provider Default Pricing (per 1M tokens)
| Provider | Model | Input | Output |
|---|---|---|---|
| OpenAI | GPT-4o | $2.50 | $10.00 |
| OpenAI | GPT-4o-mini | $0.15 | $0.60 |
| OpenAI | GPT-4-turbo | $10.00 | $30.00 |
| Anthropic | Claude 3.5 Sonnet | $3.00 | $15.00 |
| Anthropic | Claude 3 Opus | $15.00 | $75.00 |
| MiniMax | MiniMax-M2 | $0.10 | $0.10 |
| MiniMax | MiniMax-M2.1 | $0.20 | $0.40 |
Scripts
analyze.sh — Full Cost Analysis
Runs a complete cost diagnostic on the current OpenClaw configuration.
./scripts/analyze.sh
Output: Detailed markdown report with: - Estimated API spend (daily / weekly / monthly) - Heartbeat cost analysis - Tool count risk factor - Top 3 cost reduction recommendations - Estimated savings after optimization
heartbeat_diagnosis.sh — Find Heartbeat Waste
Checks OpenClaw heartbeat configuration and calculates wasted API calls.
./scripts/heartbeat_diagnosis.sh
Output: Heartbeat efficiency score (0–100%), wasted calls per day, estimated annual waste.
estimate.sh — Quick Cost Estimate
One-shot estimate with optional custom parameters.
./scripts/estimate.sh <heartbeat_seconds> <tasks_per_day> <avg_input_tokens> <avg_output_tokens>
Output: Daily, weekly, and monthly cost estimates for the given parameters.
Cost Reduction Recommendations
Priority order:
- Increase heartbeat interval — If heartbeat is under 5 minutes, increase to 10–30 min for idle agents
- Switch to cheaper model — MiniMax M2 at $0.10/1M is 25x cheaper than GPT-4o for most tasks
- Batch tasks — Run 5–10 tasks per session instead of 1 task per heartbeat cycle
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- Cache responses — Use memory skills to avoid repeated context
- Disable verbose logging — Reduces token churn in long conversations
Usage Example
# Full analysis with MiniMax pricing
export API_COST_MODEL=minimax
./scripts/analyze.sh
# Quick estimate
./scripts/estimate.sh 300 20 8000 2000
# Heartbeat-only diagnosis
./scripts/heartbeat_diagnosis.sh
Notes
- Estimates are based on configuration analysis, not live API metering
- For actual spend tracking, enable provider cost logs and compare
- MiniMax models offer best price/performance for volume workloads
- Heartbeat waste is typically the single largest cost lever
🤖 AI 評測
這個 Skill 質量不錯，能有效幫助識別 OpenClaw agent 的 API 成本問題。優點是自動讀取配置、支援多家供應商、有清晰的評分和建議輸出。缺點是成本估算基於假設而非真實資料，可能不夠準確，另外只適合 OpenClaw 使用者使用。總體而言是一個實用且文件完善的工具，但對預算敏感的使用者來說估算精度還有提升空間。
