continuous-inverter

Name: continuous-inverter
Availability: InStock
Author: plurigrid

Detect spectral-gap degradation across six theorem provers on every commit.

60|13|Updated Dec 22, 2025

Search Tags:#automation #CI/CD #remediation #provers #spectral-health

Ready to run

npx skills add https://github.com/plurigrid/asi --skill continuous-inverter

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: continuous-inverter
Source: https://github.com/plurigrid/asi/tree/main/ies/music-topos/.codex/skills/continuous-inverter
Command: npx skills add https://github.com/plurigrid/asi --skill continuous-inverter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Real-time monitoring and automated remediation for proof-system health across multiple theorem provers, generating CI/CD workflows and proactive suggestions when gaps degrade.

Core Features & Use Cases

Prover-wide analysis: Monitor spectral gaps across 6 provers in parallel.
Remediation strategies: Möbius-filter guided rewriting and recommendations.
CI/CD & Dashboards: Generate GitHub Actions templates and visual dashboards for trend tracking.

Quick Start

Save the generated CI/CD workflow to .github/workflows/spectral-health-check.yml and push to trigger the health-check pipeline.

Frequently Asked Questions about continuous-inverter

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

FAQPage Schema

How do I monitor theorem prover health across multiple provers in my CI/CD pipeline?▼

Monitor spectral-gap degradation across six theorem provers on every commit by analyzing parallel proofs in real time. The Skill detects health changes automatically and generates GitHub Actions workflows to integrate monitoring into your CI/CD pipeline, triggering checks on each push.

Can I automate remediation suggestions when proof-system performance degrades?▼

Yes. The Skill analyzes parallel proofs and generates per-prover remediation suggestions guided by Möbius-filter rewriting strategies when spectral gaps degrade, providing actionable guidance to restore prover health without manual intervention.

What does spectral-gap degradation mean and why should I monitor it?▼

Spectral-gap degradation indicates declining performance across theorem provers. Monitoring it detects proof-system health issues early, allowing automated remediation before failures cascade. The Skill tracks gaps across six provers in parallel to catch anomalies in real time.

How do I set up automated health-check workflows for my proof systems?▼

Generate a GitHub Actions CI/CD template using the Skill's workflow generator, then save it to .github/workflows/spectral-health-check.yml and push to your repository. The pipeline runs on every commit, monitoring prover health and producing dashboards for trend tracking.

Does this work with any theorem prover or only specific ones?▼

The Skill monitors six specific theorem provers in parallel, analyzing each prover's spectral gaps and generating prover-specific remediation suggestions. Check the documentation to confirm your provers are included in the supported set.

What's the difference between real-time monitoring and automated remediation in this approach?▼

Real-time monitoring detects spectral-gap changes on every commit using parallel prover analysis. Automated remediation generates actionable suggestions and CI/CD workflows when health degrades, enabling faster response without manual diagnosis.