LLM Cost Optimization

LLM Cost Optimization is an AI Engineering skill for Claude Code, published by nimadorostkar in Claude-Skills-collection.

18 stars2 forkson nimadorostkar/Claude-Skills-collectionAdded 2026/07/16+13% in starsRepository updated 2026/07/14

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Install in seconds

Install LLM Cost Optimization

Copy LLM Cost Optimization into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/nimadorostkar/Claude-Skills-collection/tree/main/skills/ai/llm-cost-optimization ~/.claude/skills/llm-cost-optimization

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/nimadorostkar/Claude-Skills-collection.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/ai/llm-cost-optimization/SKILL.md in nimadorostkar/Claude-Skills-collection
Installs to: ~/.claude/skills/llm-cost-optimization
Collection: One of 50 skills cataloged from this repository
Category: AI Engineering — 3670 skills

What LLM Cost Optimization does

Optimize LLM feature costs by identifying where tokens are spent and applying caching, context reduction, model routing, batching, and output limits without degrading output quality.

LLM Cost Optimization is cataloged under AI Engineering on DirSkills. LLM Cost Optimization comes from a repository tagged ai, claude, claude-skills and skills.

Documentation

README

Excerpt

Reduce the cost of an LLM feature without losing the quality that justified it. Most LLM bills are dominated by one or two things that nobody has measured, and the fix is usually structural rather than a matter of shaving tokens.

When to Use

An LLM feature that is too expensive at current or projected volume.
Before scaling a feature from pilot to production traffic.
A bill that grew and nobody can explain why.

Capabilities

Token accounting: where the spend actually is.
Prompt caching.
Context reduction and retrieval narrowing.
Model routing and downgrading.
Batch processing for non-interactive work.
Output-length control.

Inputs

This is the opening of the README. Read the full README on GitHub.

Frequently asked about LLM Cost Optimization

What else does nimadorostkar publish alongside LLM Cost Optimization?
LLM Cost Optimization is one of 50 skills that DirSkills catalogs from nimadorostkar/Claude-Skills-collection, the repository it ships in. Its siblings there include API Design, Agent Design and Agent Instructions. Each one is a separate skill with its own page in this directory, installs the same way LLM Cost Optimization does, and is maintained by nimadorostkar in that same repository. The rest of the collection is listed on the nimadorostkar/Claude-Skills-collection page.
How does LLM Cost Optimization compare to other AI Engineering skills?
LLM Cost Optimization ranks #3593 by stars among the 3670 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of LLM Cost Optimization against them. Open each page to compare what they document and how they install.