prompt-writing

Effective prompts for AI delegation embed the CLEAR framework: Context (background and constraints), Limitations (what the agent cannot do), Expectations (success criteria), Actions (specific steps), and Resources (available tools). Structure prompts with explicit constraints, deterministic output formats, and context sufficient for the agent to complete multi-step workflows independently.

The CLEAR framework—Context, Limitations, Expectations, Actions, Resources—is a structured approach to prompt design that ensures AI agents receive complete operational guidance. It eliminates ambiguity in task execution, enforces consistent output formats, and enables reliable multi-step workflow automation across engineering, testing, and operational scenarios.

Design subagent prompts by specifying task dependencies, success criteria for each step, context-transfer patterns between agents, and required output formats. Use templates that enforce explicit handoffs, define what information each subagent receives and produces, and include validation checkpoints to ensure deterministic results across the entire workflow.

Yes. Standardized prompt templates enforce consistent context-transfer patterns, output formats, and constraint specification across projects. Templates with delivery guidance reduce iteration time, minimize ambiguity in agent behavior, and make complex workflows reproducible and maintainable.

Include explicit resource constraints, prohibited actions, expected output format with examples, success criteria, and contextual boundaries. Specify what the agent cannot do as clearly as what it should do, provide concrete examples of desired outputs, and define failure modes so the agent can self-validate or escalate appropriately.

Structure delegation prompts with Context (what the Task inherits), Actions (discrete steps the Task executes), Expectations (measurable success criteria), Limitations (scope boundaries), and required Resources (tools, data sources, permissions). This ensures Task tools execute deterministically and produce outputs suitable for downstream processing or notification.