cost-aware-llm-pipeline

npx skills add mturac/everything-openai-codex --skill cost-aware-llm-pipeline --agent codex

Same command for any agent — swap --agent for claude-code, cursor, copilot.

# Cost-Aware LLM Pipeline Patterns for controlling LLM API costs while maintaining quality. Combines model routing, budget tracking, retry logic, and prompt caching into a composable pipeline. ## When to Activate - Building applications that call LLM APIs (Codex, GPT, etc.) - Processing batches of items with varying complexity - Need to stay within a budget for API spend - Optimizing cost without sacrificing quality on complex tasks ## Core Concepts ### 1. Model Routing by Task Complexity Automatically select cheaper models for simple tasks, reserving expensive models for complex ones. ```python MODEL_STANDARD = "codex-standard-4-6" MODEL_FAST = "codex-fast-4-5-20251001" _STANDARD_TEXT_THRESHOLD = 10_000 # chars _STANDARD_ITEM_THRESHOLD = 30 # items def select_model( text_length: int, item_count: int, force_model: str | None = None, ) -> str: """Select model based on task complexity.""" if force_model is not None: return force_model if text_length >= _STANDARD_TEXT_THRESHOLD or item_count >= _STANDARD_ITEM_THRESHOLD: return MODEL_STANDARD # Complex task return MODEL_FAST # Simple task (3-4x cheaper) ``` ### 2. Immutable Cost Tracking Track cumulative spend with frozen dataclasses.