mem-monthly

Analyze monthly L2 behavior updates and extract recurring patterns into L3 memory frameworks.

333|83|Updated Jan 9, 2026
One-click install
npx skills add https://github.com/SpaceZephyr/myskill --skill mem-monthly-spacezephyr
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mem-monthly
Source: https://github.com/SpaceZephyr/myskill/tree/main/mem-monthly
Command: npx skills add https://github.com/SpaceZephyr/myskill --skill mem-monthly-spacezephyr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps review a month's memory updates, connect repeated behaviors into higher-level thinking patterns, and identify whether core values need a manual reset.

Core Features & Use Cases

  • Monthly behavior review: Reads the month's L2 behavior updates and summarizes what changed.
  • Pattern extraction: Finds shared decision rules, preferences, or habits across multiple actions and promotes them into L3 cognitive frameworks.
  • Core-value check: Flags possible misalignment or stale L4 values and guides the user through a manual reflection process before any update.
  • Use case: Use it when you say "月复盘", at the end of the month, or whenever you want to turn many concrete behaviors into a clearer personal operating model.

Quick Start

Tell me “月复盘” and I will review this month’s L2 updates, infer recurring L3 patterns, and tell you whether L4 needs manual calibration.

Frequently Asked Questions about mem-monthly

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

FAQPage Schema
How do I turn monthly behavior logs into higher-level cognitive patterns?

A monthly review analyzes your L2 behavior updates to group related actions and extract recurring decision rules into L3 cognitive frameworks. It compares multiple behaviors to infer shared principles and flags whether L4 core values need manual recalibration.

What is the best way to run a monthly reflection on my memory system?

Running a monthly reflection involves reading all L2 behavior records from the month and grouping related actions into stable patterns. This infers shared decision principles, promotes them into L3 cognitive frameworks, and flags whether L4 core values need manual recalibration.

When do I need to recalibrate my core values during a monthly review?

Core value recalibration is needed when the monthly review flags possible misalignment or stale L4 values after analyzing L2 behavior updates. The system guides you through a manual reflection process before any update to ensure principles match actions.

Can I extract recurring habits and decision rules from multiple daily actions?

Yes, recurring habits and decision rules are extracted by comparing multiple behaviors to infer a shared decision principle. The system reads all L2 records, groups related actions into stable patterns, and promotes them into L3 cognitive frameworks for a clearer operating model.

Does monthly behavior analysis work without prior L2 memory updates?

No, monthly behavior analysis requires reading all L2 behavior updates to function correctly. Without prior L2 records documenting actions throughout the month, the system cannot group related actions or extract recurring cognitive patterns into L3 frameworks.