diary

Capture session context, decisions, and learnings into a dated Markdown file.

12|2|Updated Feb 23, 2025
One-click install
npx skills add https://github.com/YousefHadder/dotfiles --skill diary-yousefhadder
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: diary
Source: https://github.com/YousefHadder/dotfiles/tree/main/codex/.codex/skills/diary
Command: npx skills add https://github.com/YousefHadder/dotfiles --skill diary-yousefhadder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the ephemeral nature of AI sessions by creating persistent diary entries, ensuring that context, decisions, and learnings are not lost between interactions.

Core Features & Use Cases

  • Session Logging: Captures key details of a work session, including context, decisions made, patterns learned, problems solved, and unfinished business.
  • Cross-Session Continuity: Enables future AI instances to reference past sessions for improved context and consistency.
  • Use Case: After a complex debugging session, use this skill to log the problem, the solution, and any new insights gained, so that if the issue re-emerges or similar problems arise, the AI can quickly recall the resolution.

Quick Start

Use the diary skill to capture the current session's context, decisions, and learnings.

Frequently Asked Questions about diary

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

FAQPage Schema
How do I preserve AI session context and decisions for cross-session continuity?

Session context is preserved by capturing decisions, learned patterns, and problems solved into a dated Markdown file. This diary entry enables future AI instances to reference past sessions for improved contextual awareness and knowledge retention.

What is the best way to log session memory and prevent lost context between interactions?

Logging session memory involves recording unfinished business and resolutions into a persistent Markdown file. This prevents lost context between interactions by creating a dated knowledge base that future AI sessions can reference for consistency.

Does the diary skill require file system access to write decision logs?

Yes, the diary skill requires file system access to write entries to ~/.codex/memory/diary/. It creates persistent dated Markdown files in this directory to store session context, decisions, and learned patterns for cross-session continuity.

How do I create a decision log for a complex debugging session?

Create a decision log by capturing the problem, solution, and new insights gained during the debugging session. The diary skill automatically formats these details into a dated Markdown file for future reference if similar problems re-emerge.

Can I use session logging for knowledge retention across multiple AI interactions?

Yes, session logging facilitates knowledge retention by capturing context, decisions, and learned patterns into persistent Markdown files. Future AI instances can reference these dated entries to maintain consistency and recall past resolutions across interactions.

What are the limitations of using Markdown files for context preservation?

Markdown files for context preservation are limited to text-based entries stored in ~/.codex/memory/diary/. They require manual triggering to log sessions and do not automatically capture real-time context without explicit invocation of the diary skill.