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SahilAshar
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session-log

Create structured session logs with Markdown templates and YAML frontmatter.

Updated Aug 17, 2021
Search Tags:#documentation#development workflow#context capture#decision logging#ai assistant#session log
One-click install
npx skills add https://github.com/SahilAshar/dotfiles --skill session-log-sahilashar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: session-log
Source: https://github.com/SahilAshar/dotfiles/tree/main/.github/skills/session-log
Command: npx skills add https://github.com/SahilAshar/dotfiles --skill session-log-sahilashar

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps you create structured, searchable logs of your AI-assisted development sessions, capturing crucial context, decisions, and learnings that would otherwise be lost.

Core Features & Use Cases

  • Structured Logging: Provides a standardized template for session logs, including metadata, goals, context, conversation flow, decisions, and artifacts.
  • Decision Capture: Explicitly documents the "why" behind technical choices, including alternatives considered and trade-offs.
  • Use Case: When starting a complex feature implementation with an AI agent, use this skill to log the initial goals, the architectural decisions made, and any challenges encountered, ensuring future clarity for yourself and your team.

Quick Start

Use the session-log skill to create a new session log file for your current development work.

Frequently Asked Questions about session-log

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

FAQPage Schema
How do I document AI-assisted development sessions to keep track of decisions?▼

Document AI-assisted development sessions by creating structured Markdown logs with YAML frontmatter. This approach captures crucial context, decisions, and troubleshooting history, ensuring future reference clarity for you and your team.

What is the best way to capture the context and decisions from AI coding sessions?▼

The best way to capture context from AI coding sessions is using a standardized template that records metadata, goals, conversation flow, and architectural decisions. This explicitly documents the technical choices, alternatives considered, and trade-offs.

How do I create a searchable log of my AI chat history for complex feature implementations?▼

Create a searchable log of your AI chat history by saving session details in a structured Markdown format. Using ISO 8601 timestamps, participant tracking, and tag-based categorization enhances the searchability of your complex feature implementation records.

Can I use a standard Markdown template for logging AI development workflow context?▼

Yes, you can use a defined Markdown template with YAML frontmatter for logging AI development workflow context. This structured format supports participant tracking and tag-based categorization to organize your development context effectively.

Why does my team lose context on technical choices made during AI development sessions?▼

Teams lose context on technical choices because AI chat history is often ephemeral. Using a structured session log explicitly documents the 'why' behind decisions, including alternatives and trade-offs, preventing crucial context loss.

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