How does the multi-agent analysis work?

It runs four agents in parallel—doc-updater, automation-scout, learning-extractor, and followup-suggester—followed by a duplicate-checker to ensure all suggestions are unique and valuable.

Does it automatically commit my code without asking?

No, it analyzes your work first and then provides a 'Create commit' option within an interactive selection menu, allowing you to review the suggested message before execution.

What happens when I run the session-wrap skill?

The skill analyzes your Git changes, triggers four specialized sub-agents to evaluate your work, and presents an interactive menu to commit changes, update documentation, or create new automations.

Which documentation files does it prioritize for updates?

It specifically checks and suggests updates for CLAUDE.md and context.md to ensure your project's local AI instructions and context remain up to date.

Session Wrap

Name: Session Wrap
Author: team-attention

byteam-attention

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313

생산성 및 워크플로

Automates the end-of-session workflow by analyzing code changes, updating documentation, and suggesting follow-up tasks using multi-agent intelligence.

소개

The Session Wrap skill provides a comprehensive multi-agent orchestration workflow designed to systematically close out coding sessions. By running four specialized analysis agents in parallel, it identifies necessary documentation updates for files like CLAUDE.md, extracts key learnings, detects automation patterns, and suggests prioritized follow-up tasks. This ensures that context is preserved between sessions, technical debt is captured, and developers can resume work with maximum clarity and minimal cognitive overhead through an interactive, validation-backed summary.

주요 기능

Automated Git status and diff checking to generate accurate session summaries
Interactive action menu for creating commits and updating project context files
Context preservation for seamless transitions between development sessions
Multi-agent parallel analysis for documentation, automation, learnings, and tasks
Intelligent duplicate detection to prevent redundant documentation and automation proposals
313 GitHub stars

사용 사례

Extracting technical learnings and 'Today I Learned' points after troubleshooting complex bugs
Transitioning between different projects while ensuring all 'in-progress' thoughts are captured
Closing out a feature implementation by documenting new patterns and creating clean commits

소개

주요 기능

Automated Git status and diff checking to generate accurate session summaries
Interactive action menu for creating commits and updating project context files
Context preservation for seamless transitions between development sessions
Multi-agent parallel analysis for documentation, automation, learnings, and tasks
Intelligent duplicate detection to prevent redundant documentation and automation proposals
313 GitHub stars

사용 사례

Extracting technical learnings and 'Today I Learned' points after troubleshooting complex bugs
Transitioning between different projects while ensuring all 'in-progress' thoughts are captured
Closing out a feature implementation by documenting new patterns and creating clean commits