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CostClaw — Token Cost Analyzer for OpenClaw

专为OpenClaw打造的零依赖成本优化工具,无需集成。核心功能是读取用户实际配置与工作区,生成含精准金额的优先级降本建议,覆盖文件、技能、模型等维度。典型场景为用户API账单过高、预算超支时使用,运行指定脚本即可触发,输出可视化报告或JSON,本地运行保障隐私,精准削减令牌成本。

morpheis
morpheis
热度 47.94
最近更新 2026-05-11 17:37:38
分类:数据依赖:代码执行 / 读写文件应用场景:数据处理 / 报告撰写 / 财务

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add costclaw
Metadata
name
costclaw
version
0.2.0
description
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".
license
MIT
compatibility
OpenClaw v2026.2+
metadata
{"author":"ClawdActual","homepage":"https://github.com/Morpheis/costclaw","category":"optimization","tags":["cost","tokens","optimization","budget","savings","billing"]}

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:

  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.

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 — —
Google Gemini 2.5 Pro $1.25 $10.00 — —
Google 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