wrap-up

Consolidate session learnings, hours, costs, and ideas into durable files.

Updated Apr 5, 2026
One-click install
npx skills add https://github.com/hilbertp/liberation-of-bajor --skill wrap-up-hilbertp
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: wrap-up
Source: https://github.com/hilbertp/liberation-of-bajor/tree/main/.claude/skills/wrap-up
Command: npx skills add https://github.com/hilbertp/liberation-of-bajor --skill wrap-up-hilbertp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents loss of valuable session information by capturing learnings, time estimates, token costs, and ideas before the AI context is compacted or the conversation ends.

Core Features & Use Cases

  • Consolidates directives, decisions, and session metrics into durable files for all roles.
  • Records new learnings and project debriefs, updates timesheets, and logs session token usage.
  • Captures emerging ideas and stamps an anchor to mark the session as properly wrapped up.
  • Ideal for any multi‑agent workflow where context depth grows or a handoff is imminent.

Quick Start

Run the wrap‑up skill before ending the conversation to record all session details.

Frequently Asked Questions about wrap-up

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

FAQPage Schema
How do I save session learnings and token costs before AI context is compacted?

To save session learnings and token costs before context compaction, run a wrap-up skill to consolidate directives, decisions, and metrics into durable timesheet JSONL logs and project anchor files.

What is the best way to record project debriefs and hours for a multi-agent workflow?

Recording project debriefs and hours for a multi-agent workflow requires consolidating session metrics and new learnings into durable files, updating timesheet logs, and stamping an anchor to mark a proper wrap-up.

When should I consolidate session data to prevent losing context in a multi-agent pipeline?

You should consolidate session data to prevent context loss at the end of any AI-driven conversation or when context depth approaches limits and a handoff is imminent across all roles in the pipeline.

Do I need project anchor files and timesheet JSONL logs to capture session metrics?

Yes, capturing session metrics requires access to project anchor files, timesheet JSONL logs, a usage-snapshot script, and wormhole functions to append entries and properly record session details.

How does capturing emerging ideas and session token usage work during a context handoff?

Capturing emerging ideas and session token usage during a handoff works by recording new learnings, logging token usage via a snapshot script, and stamping an anchor file to mark the session as wrapped up.

Can I log token usage and update timesheets across all roles in a multi-agent pipeline?

Yes, you can log token usage and update timesheets across all roles by applying a wrap-up skill that requires access to usage-snapshot scripts and appends entries to timesheet JSONL logs via wormhole functions.