prompt-engineering

To write system prompts with explicit behavioral contracts, standardize instructions using a 5-layer architecture: identity, context, task, process, and output. This grounds agent reasoning and enforces repeatable, auditable behavior across builder, research, and review workflows.

The best way to structure multi-agent task definitions is using ready-to-use templates like builder-agent.md, research-agent.md, and review-agent.md. These templates enforce action-first tool usage, exact parameter names, and parallel tool calls for reliable execution.

Avoid anti-patterns and meta-commentary by applying guardrails such as DRY principles and explicit constraints within your prompts. Target the agent audience directly and enforce atomic edits to reduce ambiguity in the behavioral contract.

Yes, you need frontmatter requirements specifying the name and description when building prompts for tool-centric agents. Satisfying these frontmatter fields ensures the prompt integrates correctly with templates and enables repeatable, auditable prompt construction.

A templates-driven structure provides reference materials and operating rules to standardize outputs, whereas ad-hoc generation lacks repeatable constraints. Using domain-specific templates ensures reliable behavior across different agent roles without ambiguity.