Design prompts that enforce structured JSON outputs from LLMs.
npx skills add https://github.com/skomax/skills --skill prompt-engineering-skomax
Please help me install this Agent Skill. Skill: prompt-engineering Source: https://github.com/skomax/skills/tree/main/.claude/skills/prompt-engineering Command: npx skills add https://github.com/skomax/skills --skill prompt-engineering-skomax
This Skill helps developers design precise prompts that coax LLMs into producing deterministic, structured outputs, reducing ambiguity across tasks like document processing, content generation, and data extraction.
Provide a structured prompt template to extract data from a document using few-shot examples.
High-intent search queries and answers about installing and using this skill.
Get structured JSON output from an LLM by using prompt templates that enforce explicit output formats, clear constraints, and guided examples to improve reliability and reproducibility.
The best way to reduce hallucinations during data extraction is applying few-shot patterns and templates, which provide guided examples to improve accuracy and reduce ambiguity in LLM responses.
Design prompts for document processing workflows by creating reusable prompt blocks that apply clear constraints and few-shot examples, ensuring deterministic outputs across integration and content generation tasks.
Yes, chain-of-thought prompting can be combined with structured output templates to guide LLMs through reasoning steps, producing deterministic formats for data extraction and integration workflows.
LLM prompts produce inconsistent results across models when lacking explicit constraints and few-shot examples, which are necessary to enforce deterministic, structured outputs and reduce ambiguity across domains.
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