Weekly Reflect

Review and prune activity logs and memory entries in markdown and JSON.

17|1|Updated Mar 25, 2026
One-click install
npx skills add https://github.com/aaronjmars/miroshark-aeon --skill weekly-reflect
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Weekly Reflect
Source: https://github.com/aaronjmars/miroshark-aeon/tree/main/skills/reflect
Command: npx skills add https://github.com/aaronjmars/miroshark-aeon --skill weekly-reflect

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the process of reviewing recent activity, consolidating memory, and removing stale entries, helping maintain an efficient knowledge base.

Core Features & Use Cases

  • Memory Review: Analyzes current memory state, logs activity, and identifies patterns or gaps.
  • Content Management: Moves detailed notes into topic files and updates existing documents.
  • Stale Entry Pruning: Removes irrelevant or outdated information to keep memory lean and useful.
  • Use Case: An organization uses this Skill to automatically perform weekly memory audits, ensuring their internal knowledge system remains accurate and uncluttered.

Quick Start

Run this Skill to analyze the latest memory logs and update the knowledge base accordingly.

Frequently Asked Questions about Weekly Reflect

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

FAQPage Schema
How do I automate memory consolidation and prune stale entries from a knowledge base?

Automating memory consolidation involves parsing markdown and JSON activity logs to identify patterns, moving detailed notes into topic files, and removing outdated entries. This process maintains a concise and efficient long-term knowledge system through file operations.

What is the best way to review weekly activity logs for a personal knowledge base?

Reviewing weekly activity logs is best handled by analyzing the current memory state to identify gaps and patterns. You can then update existing markdown documents and consolidate relevant logs into structured topic files to keep your knowledge base accurate.

Can I use automated memory pruning for team project contexts?

Automated memory pruning suits team project contexts by auditing shared knowledge systems. It performs file operations to remove irrelevant or outdated information, ensuring the team's internal memory remains lean and useful for ongoing reference.

How does removing outdated information from JSON and markdown logs work?

Removing outdated information works by parsing JSON and markdown memory entries to evaluate their current relevance. The system identifies stale data and executes file operations to delete or update those specific entries, keeping the knowledge system uncluttered.

When should I run a memory audit to maintain my knowledge system?

You should run a memory audit when your knowledge base accumulates excessive or outdated activity logs. Regular audits analyze the current memory state, consolidate detailed notes into topic files, and prune irrelevant entries to keep the system efficient.