mem-monthly_skill

Overview

This skill performs a monthly review of an AI personal memory system. It analyzes last month’s L2 behavior updates, extracts recurring thinking patterns into L3 cognitive frameworks, and checks whether L4 core values need recalibration. The skill produces a concise monthly report and prompts manual actions when core-level changes are required.

How this skill works

On trigger (user says "monthly review" or at month-end), the skill reads all L2 behavior updates from the current month. It clusters behaviors to identify common decision principles and attempts to formalize those principles as L3 cognitive framework files. Finally, it evaluates L4 core-layer alignment and marks items that require manual review before updating metadata and generating the monthly report.

When to use it

• User requests a 'monthly review' verbally or via command
• Automated end-of-month scheduled reviews
• When you want to distill behavior patterns into stable cognitive frameworks
• Before major planning sessions to ensure memory/cognition alignment
• When suspecting value drift or inconsistent decision behavior

Best practices

• Keep L2 behavior entries concise and timestamped to improve pattern detection
• Review suggested L3 frameworks and edit descriptions or application notes before confirming
• Treat all L4 recommendations as prompts for manual reflection — L4 is only updated by you
• Run reviews regularly (monthly) to capture emerging patterns early
• Verify the monthly report and accept or request modifications to recorded L3 files

Example use cases

• User says 'month review' and receives a report summarizing new behaviors and extracted frameworks
• End-of-month automated run that creates 1–3 new L3 frameworks from recurring habits
• Detecting that recent actions conflict with stated core values and prompting a manual L4 review
• Preparing a planning session with a distilled set of decision frameworks from recent behavior