remember

Name: remember
Availability: InStock
Author: Morgan

Capture corrections and friction signals into structured methodology notes.

Updated Aug 23, 2026

Search Tags:#context #methodology #notes #sessions #friction #remember

Ready to run

npx skills add https://github.com/hellofrommorgan/intent-computer --skill remember-hellofrommorgan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: remember
Source: https://github.com/hellofrommorgan/intent-computer/tree/main/packages/plugin/src/skill-sources/remember
Command: npx skills add https://github.com/hellofrommorgan/intent-computer --skill remember-hellofrommorgan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps teams convert user friction and corrective feedback into durable, actionable guidance that the system can learn from across sessions.

Core Features & Use Cases

Explicit mode to capture described friction via /remember "description".
Contextual mode to mine recent conversation for corrections when the target is empty.
Session mining mode to scan stored sessions for patterns and generate methodology notes.

Quick Start

Invoke /remember with a clear friction description to capture a methodology note.

Frequently Asked Questions about remember

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

FAQPage Schema

How do I turn user corrections into durable methodology notes?▼

To turn user corrections into durable methodology notes, you capture friction signals explicitly or contextually, converting them into structured guidance stored under ops/methodology/ for cross-session learning.

What is the best way to capture friction signals from recent conversations?▼

The best way to capture friction signals is using contextual mode with an empty target, which mines recent conversation interactions to identify corrections and generate structured methodology notes.

Can I scan stored sessions for recurring friction patterns automatically?▼

Yes, you can scan stored sessions automatically using session mining mode, which detects recurring friction patterns and generates methodology notes with provenance and source mode for auditability.

How do I store methodology notes with provenance for auditability?▼

You store methodology notes with provenance for auditability by writing structured outputs to ops/methodology/ with links to related notes and records of the source capture mode used.

Does this methodology note capture tool require explicit descriptions for every entry?▼

No, it does not require explicit descriptions for every entry, as it supports contextual mode to mine recent conversations and session mining mode to scan past interactions automatically.

When should I not use automated session mining for feedback analysis?▼

You should not use automated session mining when stored sessions are unavailable or when recent real-time conversational context contains the most relevant friction signals to capture explicitly.