memory-debug

Diagnose and fix Signet memory issues across daemon health, embeddings, and data integrity.

237|40|Updated Feb 11, 2026
One-click install
npx skills add https://github.com/Signet-AI/signetai --skill memory-debug-signet-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: memory-debug
Source: https://github.com/Signet-AI/signetai/tree/main/skills/memory-debug
Command: npx skills add https://github.com/Signet-AI/signetai --skill memory-debug-signet-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Diagnose and fix Signet memory issues (daemon health, embeddings, search quality, and data integrity).

Core Features & Use Cases

  • Verify daemon health and config
  • Validate write/read paths for memories
  • Check embedding health and provider configuration
  • Run advanced diagnostics and reproducible checks
  • Generate actionable remediation steps

Quick Start

Run memory-debug to diagnose and fix memory issues across daemon health, embeddings, search quality, and data integrity.

Frequently Asked Questions about memory-debug

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

FAQPage Schema
How do I diagnose memory recall failures and check daemon health in local Signet deployments?

To diagnose memory recall failures, run health checks on your local Signet daemon to verify configuration, validate write and read paths, and identify the root cause of recall quality degradation.

What causes memory embeddings health issues and how can I validate my provider configuration?

Memory embeddings health issues often stem from misconfigured embedding providers. You can validate provider configuration and run diagnostic checks to detect anomalies affecting memory persistence and data integrity.

Can I run data integrity audits on my Signet memory database without external dependencies?

Yes, you can run data integrity audits on local-first Signet deployments without external dependencies. The diagnostic workflow includes reproducible checks to audit memory data and generate actionable remediation steps.

What is the best way to fix Signet memory issues affecting search quality and data persistence?

The best way to fix Signet memory issues is to execute a structured diagnostic workflow covering status checks, remember and recall path validation, and embedding health diagnostics to generate actionable remediation steps.

Why does my Signet memory recall return incomplete or missing results, and how do I debug it?

Incomplete memory recall results typically indicate embedding health problems or write path failures. Debug the issue by verifying daemon health, validating the remember and read paths, and checking the embedding provider configuration.

Does memory-debug work with remote Signet deployments or is it limited to local-first setups?

Memory-debug is specifically applied to local-first Signet deployments for daemon health checks, memory embeddings health, recall failures, and data integrity audits, making it unsuitable for remote deployment configurations.