Author agent skills using the S=(C,π,T,R) model and refactor system prompts into SKILL.md units.
npx skills add https://github.com/rd162/skills --skill authoring-skills-rd162
Please help me install this Agent Skill. Skill: authoring-skills Source: https://github.com/rd162/skills/tree/main/authoring-skills Command: npx skills add https://github.com/rd162/skills --skill authoring-skills-rd162
This Skill provides a methodology for creating well-structured agent skills and for refactoring monolithic system prompts into modular, reusable components that can be discovered, loaded on-demand, and executed with clear contracts.
Outline a process to author well-structured agent skills and refactor monolithic system prompts into reusable components.
High-intent search queries and answers about installing and using this skill.
Refactoring monolithic system prompts involves breaking down large system-rule files into discrete, reusable SKILL.md units. This skill guides the process using the S=(C,π,T,R) model to ensure components are discoverable, load-on-demand, and interoperable across different agents.
The S=(C,π,T,R) model is a standardized four-part framework for skill authoring. It defines consistent activation, executable policy, termination, and reuse for agent skills, ensuring clear contracts and graceful degradation across different models.
Cross-model portability is achieved by standardizing skill components through progressive disclosure and gating patterns. This skill provides a framework to make skills interoperable across different agents while maintaining graceful degradation during execution.
Standardizing prompt engineering components requires defining clear frontmatter, applicability rules, and termination policies. This skill provides a methodology to structure agent skills with clear contracts, ensuring they are discoverable and load-on-demand.
You need to modularize system prompts into SKILL.md units when monolithic rule files become difficult to manage or reuse. This refactoring enables progressive disclosure, allowing agents to discover and load specific skills on-demand.
Graceful degradation is a core feature of the S=(C,π,T,R) skill authoring framework. It ensures that agent skills can handle failures or unexpected inputs smoothly, maintaining execution stability across different models and environments.
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chengyihuaAutomates creation and packaging of modular Skill Units with SKILL.md.
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kaikojima05Execute agent-specific prompt instructions from @.[agent_name]/prompt/.prompt.md.
