meta-mode-memory

Name: meta-mode-memory
Availability: InStock
Author: amaledtuning

Store and query compact task-state memory files in Codex repositories.

Updated Apr 21, 2026

Search Tags:#markdown #memory #ingestion #knowledge #checkpoint #deterministic

Ready to run

npx skills add https://github.com/amaledtuning/CODEX_Skills --skill meta-mode-memory

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: meta-mode-memory
Source: https://github.com/amaledtuning/CODEX_Skills/tree/main/skills/meta-mode-memory
Command: npx skills add https://github.com/amaledtuning/CODEX_Skills --skill meta-mode-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

File-first memory sandbox for Codex. Stores compact durable task-state snapshots, ingests docs, and compiles deterministic knowledge pages, with query and lint/audit support.

Core Features & Use Cases

File-first memory sandbox for compact, durable task-state memory in the repo without external services, hooks, or model-dependent indexing.
Ingest markdown or text docs into memory inbox/ingest.
Compile deterministic knowledge pages and run audits for structure and markdown-link health.

Quick Start

Use save_note.py to capture a concise memory note into today's daily log and optionally create a checkpoint with session_checkpoint.py.

Frequently Asked Questions about meta-mode-memory

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

FAQPage Schema

How do I store durable task-state memory for Codex workflows without external services?▼

You can store durable task-state memory by using a file-first memory sandbox that writes compact snapshots directly into a local repository under a `.codex-memory` directory without requiring external services or model-dependent indexing.

What is the best way to ingest markdown documentation into a local repository memory system?▼

The best way to ingest markdown documentation is to use a memory ingestion tool that imports docs into a local memory inbox, enabling subsequent querying and compilation of deterministic knowledge pages.

How do I create a checkpoint to save implementation notes during a coding session?▼

You create a checkpoint by running a dedicated script like `session_checkpoint.py` to capture concise memory notes into a daily log, preserving implementation state within your repository.

Can I run an audit on markdown link health and structure for my local knowledge pages?▼

Yes, you can run an audit to check markdown link health and structural integrity, ensuring that compiled deterministic knowledge pages remain valid and accessible within your local memory layout.

Do I need external dependencies or hooks to maintain a file-first memory sandbox?▼

No, you do not need external dependencies or hooks to maintain a file-first memory sandbox, as it enforces a local file layout with optional overrides and operates entirely self-contained.

How does deterministic knowledge compilation work for local task-state snapshots?▼

Deterministic knowledge compilation works by processing ingested markdown and text documents into structured knowledge pages, ensuring consistent output structure and markdown-link health for auditing.