maestro-revisar-memorias

Review Maestro memory stores and propose evidence-backed keep, edit, or discard actions.

Updated Apr 9, 2026
One-click install
npx skills add https://github.com/eusouwillnunes/sistema-maestro --skill maestro-revisar-memorias
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: maestro-revisar-memorias
Source: https://github.com/eusouwillnunes/sistema-maestro/tree/main/skills/maestro-revisar-memorias
Command: npx skills add https://github.com/eusouwillnunes/sistema-maestro --skill maestro-revisar-memorias

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Consolidates, cleans, and evolves the Maestro memory store so accumulated user and project memories stop becoming stale, inconsistent, or missing, and agents remain aligned with actual usage evidence.

Core Features & Use Cases

  • Diagnostic Audit: Read user and project memory indexes and session histories to produce a concise state overview (preferences, agent adjustments, decisions, sessions).
  • Evidence-based Review: Present each memory category item-by-item with options to keep, edit, or discard while citing originating sessions or feedback.
  • Evolution Proposals: Recommend concrete agent changes (checklist additions, new rules, modified flows) with justification, impact, and target override file locations; apply only after explicit user approval.
  • Use Case: After several marketing sprints, detect recurring client preferences hidden in session logs, propose new persistent memories and agent checklist updates, and update the project's memory indexes after approval.

Quick Start

Please review the project's Maestro memories, present keep/edit/discard choices per category with evidence, propose agent evolutions with justifications, and prepare approved changes for writing to the user's overrides.

Frequently Asked Questions about maestro-revisar-memorias

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

FAQPage Schema
How do I audit AI agent memory stores for stale or inconsistent session data?

To audit agent memory stores, you review user and project memory indexes alongside session histories to produce a diagnostic state overview. This process identifies stale, inconsistent, or missing accumulated memories by citing originating sessions as evidence.

What is the best way to clean up and condense project context memories?

The best way to clean up project context memories is to evaluate each item item-by-item with options to keep, edit, or discard. This evidence-based review condenses memories by tracing back to originating sessions and feedback logs before applying changes.

How do I propose agent evolution changes based on user preferences and decision logs?

You propose agent evolution changes by analyzing decision logs and session histories to recommend concrete checklist additions, new rules, or modified flows. Proposals include justifications, impact analysis, and target override file locations for explicit user approval.

Does memory review require explicit approval before modifying override files?

Yes, memory review requires explicit user approval before modifying any override files. The system prepares approved changes and then regenerates memory indexes in the user's home directory and project vault only after receiving direct confirmation.

Can I use this memory audit process to detect hidden recurring client preferences in session histories?

Yes, you can use this memory audit process to detect hidden recurring client preferences by analyzing session histories and feedback. It identifies patterns to propose new persistent memories and agent checklist updates aligned with actual usage evidence.