wrapup

Record end-of-session wrap-up data as structured JSONL for Claude Code.

1|Updated Feb 23, 2026

Search Tags:#learning #evaluation #memory #session #jsonl #wrapup

Ready to run

npx skills add https://github.com/gonnector/claude-session-wrapup-skill --skill wrapup-gonnector

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: wrapup
Source: https://github.com/gonnector/claude-session-wrapup-skill/tree/main
Command: npx skills add https://github.com/gonnector/claude-session-wrapup-skill --skill wrapup-gonnector

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill automates the recording of end-of-session notes, ensuring structured, easily searchable records while reducing manual effort.

Core Features & Use Cases

Two-layer structure: Session Summary (facts, Q&A, decisions with rationale, work done, actions) and Lesson-Learned (user and AI learning)
Optional session timing and AI/user evaluation metadata, with cross-project aggregation via JSONL logs

Quick Start

Invoke the /wrapup command at the end of a session to generate and save the structured wrap-up.

Frequently Asked Questions about wrapup

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

FAQPage Schema

How do I automatically capture end-of-session summaries and lessons learned?▼

You can automatically capture end-of-session summaries by invoking a command that records facts, decisions, and lessons learned into a structured JSONL format. This creates easily searchable records while reducing manual note-taking effort.

What is the best way to store session wrap-ups in a git-friendly format?▼

Storing session wrap-ups in a git-friendly JSONL format enables structured logging and cross-project aggregation. Each line represents a discrete record, making version control diffs clean and programmatic data extraction straightforward.

Can I track session timing and evaluation data across multiple projects?▼

Yes, you can track optional session timing and AI/user evaluation data across multiple projects. The structured JSONL logs support cross-project aggregation, allowing you to analyze session metrics and learning progress comprehensively.

Does session wrap-up logging support multilingual content and auto-memory integrations?▼

Session wrap-up logging supports multilingual content alongside optional auto-memory and todo integrations. This allows you to capture lessons and summaries in your preferred language while automatically syncing actionable items.

What structured data does a session wrap-up typically include for AI learning evaluation?▼

A session wrap-up for AI learning evaluation includes a two-layer structure: a session summary capturing facts, Q&A, decisions, and actions, plus a lesson-learned layer detailing both user and AI learning outcomes.

How do I export session notes and decisions with rationale for Claude Code?▼

You export session notes, decisions with rationale, and work done by triggering the end-of-session command. This automatically structures the data into JSONL format specifically designed for Claude Code consumption and cross-project logging.