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Llm Cost Optimizer

该 Skill 读取本地 LLM API 用量日志，结合内置模型定价和任务类型识别降级、缓存与输出精简机会，生成成本优化建议；支持多家模型，但不会调用模型 API。

evezart
evezart
热度 24.84
最近更新 2026-05-12 19:11:48
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 / 推荐

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 llm-cost-optimizer
Metadata
name
llm-cost-optimizer
description
Analyze LLM API usage logs and suggest cost optimizations. Use when you need to reduce LLM spending, compare model costs, find downgrade opportunities, detect caching wins, or compress verbose outputs. Supports OpenAI, Anthropic, Google, DeepSeek, and Meta models.

LLM Cost Optimizer

Analyze LLM API usage patterns and suggest optimizations to reduce costs by 50%+.

Quick Start

Run the analysis script against a usage log JSON file:

python3 scripts/analyze.py --input usage_logs/

Input Format

Usage logs are JSON arrays of objects with:

  • timestamp (ISO 8601)
  • model (e.g. "gpt-4o", "claude-sonnet-4-20250514")
  • input_tokens (int)
  • output_tokens (int)
  • task_type (optional: "general", "coding", "classification", "extraction", "summary", "creative", "analysis")
  • session_id (optional)
  • cached (optional bool)

Optimization Strategies

  1. Downgrade: Find simple calls (low output, basic task types) on premium models and suggest cheaper alternatives
  2. Cache: Detect repeated prompt patterns and recommend prompt caching
  3. Compress: Find verbose outputs and suggest prompt tuning for conciseness

Supported Models & Pricing

All pricing is per 1M tokens (input/output). Rates are in the PRICING dict in scripts/analyze.py.

Model Tiers

  • Premium: gpt-4o, claude-sonnet-4, gemini-2.5-pro
  • Mid: gpt-4.1-mini, claude-haiku-3-5, gemini-2.5-flash, deepseek-v3
  • Budget: gpt-4.1-nano, deepseek-r1, llama-4-maverick

Downgrade suggestions map premium → mid → budget for simple tasks.