skillify

Transforms chat sessions into tested skill definitions with automatic grading and error correction.

3|2|Updated Mar 17, 2026

Search Tags:#automation #workflow #testing #refactoring #infrastructure #agent-development

Ready to run

npx skills add https://github.com/broomva/skills --skill skillify-broomva

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skillify
Source: https://github.com/broomva/skills/tree/main/skills/tooling/skillify
Command: npx skills add https://github.com/broomva/skills --skill skillify-broomva

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pytest, pyyaml, and includes scripts (resource) and tests (resource) components.

What problem does it solve?

This Skill solves the problem of "code rot" where ad-hoc solutions created during a chat session are lost or become unreliable because they lack proper testing, documentation, and registration.

Core Features & Use Cases

Automated Distillation: Transforms successful chat workflows into permanent, infrastructure-grade skills.
Quality Gatekeeping: Enforces a 10-step checklist including unit tests, resolver evaluation, and registry registration to ensure reliability.
Use Case: After successfully debugging a complex deployment issue in a chat, use this Skill to package the procedure into a reusable, tested tool that future agents can invoke automatically.

Quick Start

Use the skillify skill to distill the current session into a permanent, tested skill.

Frequently Asked Questions about skillify

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

FAQPage Schema

How do I turn ad-hoc chat workflows into permanent tested agent skills?▼

To distill ad-hoc chat workflows into permanent tested agent skills, you scaffold code and enforce a 10-step quality gate validating syntax, unit tests, and registry compliance. This prevents code rot by packaging successful procedures into reusable infrastructure.

What is the best way to prevent code rot in automated agent workflows?▼

Preventing code rot in automated agent workflows requires distilling successful ad-hoc solutions into permanent skills with proper testing, documentation, and registration. A deterministic script-based gate validates code syntax and unit tests to ensure long-term reliability.

How does the quality gate mechanism work when refactoring chat workflows into infrastructure?▼

The quality gate mechanism works when refactoring chat workflows into infrastructure by enforcing a 10-step checklist. It uses a deterministic script-based gate to validate code syntax, execute unit tests with pytest, evaluate the resolver, and ensure registry registration compliance.

Do I need pytest and pyyaml to automate workflow distillation for agent development?▼

Yes, you need pytest and pyyaml to automate workflow distillation for agent development. Pytest executes the unit tests required by the 10-step quality gate, while pyyaml handles configuration, ensuring the distilled scripts meet registry compliance before integration.

Can I integrate refactored agent skills with an existing knowledge graph and resolver?▼

Yes, you can integrate refactored agent skills with an existing knowledge graph and resolver. The distillation process explicitly includes resolver evaluation and registry registration as part of its 10-step quality gate, ensuring seamless infrastructure integration.

When should I not use automated workflow distillation for refactoring?▼

You should not use automated workflow distillation for refactoring when the ad-hoc chat procedure is non-deterministic or lacks a clear script-based implementation. The quality gate requires validating code syntax and unit tests, making it unsuitable for purely conversational logic without code.