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Optimizing LLM Accuracy | OpenAI API

Provides strategies and methodologies for improving the performance and precision of LLM outputs, including techniques like few-shot prompting, chain-of-thought reasoning, and fine-tuning.

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Viewing SKILL.md

Optimizing LLM Accuracy | OpenAI API

Provides strategies and methodologies for improving the performance and precision of LLM outputs, including techniques like few-shot prompting, chain-of-thought reasoning, and fine-tuning.

When To Use

Use when you need to improve the reliability of model responses, reduce hallucinations, or implement advanced prompting techniques like few-shot or chain-of-thought.

Reference Files

FileContainsUse For
SKILL.mdEntry point: scope, routing table, and workflow.Start here.
docs/optimizing-llm-accuracy-openai-api-workflow-guide.mdA guide detailing strategies and best practices for maximizing correctness and consistent behavior when working with OpenAI LLMs.Questions about a guide detailing strategies and best practices for maximizing correctness and consistent behavior when working with...
examples/optimizing-llm-accuracy-openai-api-openai-api-few-shot-prompting-iceland.textA text-based example demonstrating few-shot prompting techniques to improve LLM accuracy for Icelandic grammar correction.Exact payloads, commands, or snippets shown in A text-based example demonstrating few-shot prompting techniques to improve LLM accuracy for Icelandic grammar correc...
examples/optimizing-llm-accuracy-openai-api-openai-api-llm-accuracy-training.textA text-based training example demonstrating a system prompt and few-shot correction task for Icelandic sentences.Exact payloads, commands, or snippets shown in A text-based training example demonstrating a system prompt and few-shot correction task for Icelandic sentences.

What This Skill Covers

  • We’ve worked with many developers across both start-ups and enterprises, and the reason optimization is hard consistently boils down to these reasons:
  • Main sections: How to maximize correctness and consistent behavior when working with LLMs, LLM optimization context, Prompt engineering, Optimization, Evaluation.

Workflow

  1. Open the most relevant file under docs/ for the exact documented workflow and wording.
  2. Open schemas/ files for exact structured contracts.
  3. Open examples/ files for concrete requests, commands, snippets, and manifests.
  4. Do not add behavior or configuration that is not present in the attached source files.

Canonical source: https://developers.openai.com/api/docs/guides/optimizing-llm-accuracy