prompt-engineeringlisted

# Prompt Engineering Treat prompts as small behavioral specs. Improve them by naming the job, testing the behavior, changing one important thing at a time, and preserving the prompt's operating context. ## Core Workflow 1. **Scope the prompt job.** Identify the target model or provider, audience, runtime surface, inputs, tools, output contract, constraints, and where the prompt will live. If the prompt belongs to a repo, inspect existing prompts, schemas, examples, tool definitions, evals, logs, and docs before asking avoidable questions. 2. **Define success before rewriting.** State the desired behavior, hard requirements, acceptable variation, known failure modes, and evidence that would prove the prompt improved. If success is vague, turn it into 3-7 concrete cases before editing. 3. **Choose the lightest pattern that fits.** Use direct instructions for simple tasks, structured sections for context control, few-shot examples for format or judgment calibration, schemas for machine-readable output, tool-use instructions for action boundaries, and repetition only when the model repeatedly drops critical constraints. 4. **Draft with clean boundaries.** Put task, context, constraints, examples, tools, and output format in separate labeled sections. Delimit user-controlled or retrieved content clearly. Keep stable instructions before variable content when prompt caching, reuse, or maintainability matters. 5. **Evaluate against real