skills-management

Name: skills-management
Availability: InStock
Author: CodeAlive

Manage AI coding agent skill lifecycles across discovery, installation, review, and optimization.

119|10|Updated Jan 16, 2026

Search Tags:#automation #multi-agent #skills management #skill discovery #quality review #skillopt optimization

Ready to run

npx skills add https://github.com/CodeAlive-AI/ai-driven-development --skill skills-management

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skills-management
Source: https://github.com/CodeAlive-AI/ai-driven-development/tree/main/skills/skills-management
Command: npx skills add https://github.com/CodeAlive-AI/ai-driven-development --skill skills-management

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you reliably find the right AI coding agent skill, install or remove it across agents and scopes, and keep its quality high using review and SkillOpt-style optimization loops.

Core Features & Use Cases

Skill discovery & ecosystem management: Search local and remote skills and manage installs/updates/removals.
Skill lifecycle operations: List, show details, review quality, delete, move, copy, and transfer skills across agents.
Quality improvement (SkillOpt loop): Run bounded-edit optimization with held-out validation, rejected-edit buffering, and an epoch-boundary slow update.

Quick Start

Use the skills-management skill to list your installed skills and then review a specific skill named skills-management using the command python3 scripts/review_skill.py skills-management.

Frequently Asked Questions about skills-management

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

FAQPage Schema

How do I find and install the right AI coding agent skill for a specific task?▼

To find and install an AI coding agent skill, use a skill discovery process that searches local and remote repositories. It matches your requested capability against available skills, then installs the selected skill across multiple agents and scopes.

How does SkillOpt optimization improve the quality of agent skills?▼

SkillOpt optimization improves agent skills by running bounded-edit loops with held-out validation. It iteratively refines SKILL.md content, buffers rejected edits, and applies epoch-boundary slow updates to measurably enhance skill reliability.

Can I manage skill lifecycles across multiple agents and different scopes?▼

Yes, you can manage skill lifecycles across multiple agents and scopes. This includes listing, showing details, deleting, moving, copying, and transferring skills between agents to maintain consistent multi-agent environments.

What do I need to run a SkillOpt-style optimization loop for my agent skills?▼

To run a SkillOpt-style optimization loop, you need a measurable verifier and a task set formatted in tasks.jsonl. Access to the repository's deterministic scripts for listing, reviewing, and discovery is also required.

What is the best way to review the quality of an installed agent skill?▼

The best way to review an installed agent skill is by executing a validation-driven review script. This process analyzes the SKILL.md content and structural files to ensure the skill meets deterministic quality standards.

How do I update or remove outdated skills from my coding agents?▼

You can update or remove outdated skills from coding agents by executing targeted lifecycle operations. This process uninstalls or replaces the deprecated skill versions across local and remote scopes to keep your agents current.