skill-installer-plus

Coordinate local-first skill installs with lockdown admission and ledger evidence.

2|1|Updated Feb 9, 2026
One-click install
npx skills add https://github.com/grtninja/skill-arbiter --skill skill-installer-plus
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-installer-plus
Source: https://github.com/grtninja/skill-arbiter/tree/main
Command: npx skills add https://github.com/grtninja/skill-arbiter --skill skill-installer-plus

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Efficiently plan and admit new skills in a safe, lockdown-enabled way, capturing evidence to improve future installs.

Core Features & Use Cases

  • Local-first planning: prioritize candidate skills based on prior results and arbiter evidence.
  • Lockdown admission: admit chosen skills under personal-lockdown mode with controlled artifacts.
  • Learning loop: persist outcomes to a ledger and iteratively improve recommendations.

Quick Start

Run the plan/admit flow to generate a recommended set of skills for installation.

Frequently Asked Questions about skill-installer-plus

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

FAQPage Schema
What is a lockdown admission process for local skill installation?

Lockdown admission gates skill changes using controlled artifacts, collecting arbiter evidence to prevent regressions during local skill installation. It enforces local-source flows and provides deterministic plan outputs for safe governance.

How do I plan a local-first skill installation with governance evidence?

Run the plan flow to prioritize candidate skills based on prior results and arbiter evidence. The process generates a recommended set of skills for installation, outputting deterministic plan and admit JSON artifacts with ledger updates.

Can I prevent regressions when adding or updating skills locally?

Yes, you prevent regressions by applying immutable and pinned controls during the admission process. These controls gate changes and capture arbiter evidence, ensuring that adding or updating skills does not break existing functionality.

Does skill installation planning support learning feedback loops?

Yes, installation planning supports learning feedback loops by persisting outcomes to a ledger. This iteratively improves future candidate recommendations by applying prior results and arbiter evidence to the local-first planning process.

What are the limitations of local-first lockdown admission for skills?

Lockdown admission is limited by its strict local-source enforcement and immutable controls, which prevent dynamic or remote updates. It requires generating deterministic plan and admit JSON artifacts, restricting rapid uncontrolled changes.