How does this skill help reduce API costs?

It implements a logic that routes simple tasks to cheaper models, utilizes prompt caching for repeated system instructions, and prevents expensive retries on permanent errors.

What is immutable cost tracking?

It is a design pattern using frozen dataclasses to track spending. This ensures that spend records are never modified in place, leading to more reliable auditing and easier debugging.

Does it support prompt caching for all requests?

The pipeline encourages prompt caching for system messages and long contexts over 1024 tokens, which significantly reduces costs and latency for repetitive inputs.

What models does this pipeline support?

While the examples focus on the Anthropic Claude family (Haiku, Sonnet, and Opus), the architectural patterns for routing and budget tracking are applicable to any LLM provider.

Cost-Aware LLM Pipeline

Name: Cost-Aware LLM Pipeline
Author: xu-xiang

byxu-xiang

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323

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データサイエンスとML

Optimizes LLM API expenditures by implementing intelligent model routing, budget guardrails, and efficient prompt caching strategies.

This skill provides a comprehensive framework for managing LLM API costs during application development. It introduces a reusable pipeline pattern that automatically selects the most cost-effective model based on task complexity—routing simpler tasks to Haiku and complex ones to Sonnet—while tracking cumulative spending via immutable data structures. By integrating granular retry logic for transient errors and automated prompt caching for long system messages, it ensures that developers can maintain high-quality AI features without exceeding budget constraints or wasting tokens on redundant processing.

主な機能

01Integrated prompt caching for long system instructions

02Smart retry logic limited to transient API failures

03Immutable budget tracking with automatic spending guardrails

04323 GitHub stars

05Complexity-based model routing (e.g., Haiku vs. Sonnet)

06Standardized pricing reference for multi-model orchestration

ユースケース

01Multi-model architectures balancing speed, cost, and intelligence

02Production applications requiring strict monthly API budget limits

03Batch processing large datasets where token costs accumulate rapidly

主な機能

01Integrated prompt caching for long system instructions

02Smart retry logic limited to transient API failures

03Immutable budget tracking with automatic spending guardrails

04323 GitHub stars

05Complexity-based model routing (e.g., Haiku vs. Sonnet)

06Standardized pricing reference for multi-model orchestration

ユースケース

01Multi-model architectures balancing speed, cost, and intelligence

02Production applications requiring strict monthly API budget limits

03Batch processing large datasets where token costs accumulate rapidly