Define and enforce prompt engineering standards for AGENTS.md and caching workflows.
npx skills add https://github.com/tianjianjiang/smith --skill smith-prompts
Please help me install this Agent Skill. Skill: smith-prompts Source: https://github.com/tianjianjiang/smith/tree/main/smith-prompts Command: npx skills add https://github.com/tianjianjiang/smith --skill smith-prompts
Inconsistent prompt design and uncontrolled prompt usage lead to unreliable AI interactions and inflated costs. This skill provides a standardized framework for prompt engineering, caching strategies, and structured AGENTS.md guidance to improve reliability and efficiency.
Apply the caching, progressive disclosure, and structured output rules to your next AGENTS.md and related prompts to standardize interactions.
High-intent search queries and answers about installing and using this skill.
To enforce prompt engineering standards, apply a standardized framework for prompt creation, AGENTS.md guidance, and caching workflows across projects. This reduces inconsistent design and controls usage to improve reliability.
Progressive disclosure patterns optimize token-efficiency by structuring prompts to reveal information sequentially. This approach limits unnecessary context exposure, reducing latency and compute costs during AI interactions.
Set up caching rules in AGENTS.md by defining standardized instructions that govern how AI interactions are stored and retrieved. This framework reduces latency, prevents uncontrolled usage, and cuts compute costs.
The best way to standardize structured output guidance is to implement a unified framework that aligns AGENTS.md workflows and prompt design. This ensures consistent cross-platform output and reliable AI interactions.
Inconsistent prompt design causes inflated costs and unreliable outputs because uncontrolled usage lacks caching rules and token-efficiency. Without standardized AGENTS.md guidance, AI interactions vary and waste compute resources.
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