skill-to-workflow

Name: skill-to-workflow
Availability: InStock
Author: Memect

Distill validated verification skills into worker-LLM workflow blueprints.

13|4|Updated Apr 27, 2026

Search Tags:#workflow #verification #llm #skill #distillation #cost-efficiency #rule-based

Ready to run

npx skills add https://github.com/memect/kc --skill skill-to-workflow

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill-to-workflow
Source: https://github.com/memect/kc/tree/main/template/skills/zh/skill-to-workflow
Command: npx skills add https://github.com/memect/kc --skill skill-to-workflow

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams convert verified verification rules (Skills) into cheaper, faster workflows by distilling them into worker LLM prompts and executable components once accuracy targets are met.

Core Features & Use Cases

Distill validated skills into cost-efficient worker-LLM workflows.
Describe and preserve the decision logic for when to code vs when to rely on LLM prompts.
Use case: When a rule passes testing and meets SKILL_ACCURACY, generate a lean workflow blueprint that can be implemented in code and/or LLM steps for production.

Quick Start

Run this skill after a rule has passed testing and reached the SKILL_ACCURACY threshold to generate a corresponding workflow blueprint.

Frequently Asked Questions about skill-to-workflow

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

FAQPage Schema

How do I distill validated verification rules into cost-efficient LLM workflows?▼

To distill validated verification rules into cost-efficient LLM workflows, you use a distillation process that converts rules meeting the SKILL_ACCURACY threshold into worker-LLM pipelines. This generates deterministic workflow artifacts and evaluation data for testing sample documents.

When should I convert verification skills into worker-LLM pipelines?▼

You should convert verification skills into worker-LLM pipelines once a rule has passed testing and reached the required SKILL_ACCURACY threshold. This ensures the underlying logic is validated before optimizing for cost and speed in production.

How do I decide which verification logic to implement in code versus LLM prompts?▼

Deciding between code and LLM prompts involves distilling the verified skill to evaluate rule complexity and context size. The process guides model tiering and prompt design for small contexts, clearly preserving decision logic for executable components versus LLM steps.

Can I test distilled worker-LLM workflows against sample documents?▼

Yes, you can test distilled worker-LLM workflows against sample documents. The distillation process produces deterministic workflow artifacts and evaluation data, enabling testing and iteration loops to validate the cost-efficient pipeline before full deployment.

What are the limitations of distilling skills into worker-LLM pipelines?▼

A key limitation is that skill distillation into worker-LLM pipelines only applies to rules that have already passed testing and met the SKILL_ACCURACY threshold. It cannot be used to validate initial rules or fix unverified verification logic.