prompting

Design prompt contracts with inputs, outputs, constraints, and success criteria.

Updated Feb 22, 2026
One-click install
npx skills add https://github.com/pyronaur/ngents --skill prompting-pyronaur
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: prompting
Source: https://github.com/pyronaur/ngents/tree/main/skills/prompting
Command: npx skills add https://github.com/pyronaur/ngents --skill prompting-pyronaur

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Prompting Skill provides a structured playbook for crafting effective prompts for coding agents, focusing on context contracts, scope discipline, tool contracts, and verification loops to reduce drift, improve grounding, and ensure safe, reliable execution.

Core Features & Use Cases

  • Prompt contracts and prompt discipline: define inputs, outputs, constraints, and success criteria to guide agent behavior.
  • Reference-driven grounding: load core references to improve clarity, consistency, and safety in agent actions.
  • Workflow governance: guidance for verbosity control, scope management, and tool-use reasoning across long-horizon tasks.

Quick Start

Draft a robust coding-agent prompt contract that defines inputs, outputs, constraints, and success criteria.

Frequently Asked Questions about prompting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write prompt contracts for coding agents to prevent prompt drift?

You create prompt contracts for coding agents by explicitly defining inputs, outputs, constraints, and success criteria, which enforces schema-driven scope discipline and prevents prompt drift during long-horizon tasks.

What is prompt engineering for software engineering agents?

Prompt engineering for software engineering agents is the practice of designing robust prompt contracts with explicit inputs, outputs, and constraints. It ensures reliable tool-use, structured outputs, and verification loops for safe agent-based workflows.

How do I structure AGENTS.md instructions for reliable tool-use?

Structure AGENTS.md instructions by defining explicit tool contracts, loading core references for grounding, and establishing verification loops. This schema-driven approach ensures reliable tool-use and scope management across complex agent workflows.

Does this approach support tool-use verification loops in agent workflows?

Yes, this prompt engineering approach supports tool-use verification loops by enforcing schema-driven contracts with explicit constraints and success criteria. It enables structured outputs and tool calls to ensure safe, reliable execution across agent-based workflows.

How to debug prompt drift in coding agent workflows?

Debug prompt drift in coding agent workflows by applying schema-driven prompt contracts that enforce explicit inputs, outputs, and constraints. Reference-driven grounding and scope discipline realign agent behavior with the original success criteria.