Where does the handoff information get saved?

The skill writes all handoff data to the .context/handoff.md file within your project repository, making it easy for future sessions to read.

When should I trigger a handoff?

It is best practice to use the handoff skill at the end of every work session, before switching tasks, or when you need to compact the AI's context.

Does it track specific file modifications?

Yes, the skill generates a table of changed files, the type of modification, and a brief description of what was updated in each file.

How does the next session benefit from this?

The next session can run a start command to load the handoff file, providing the AI with immediate knowledge of previous work, blockers, and the exact next action to take.

Session Handoff

Name: Session Handoff
Author: RustyLindquist

byRustyLindquist

Productivity & Workflow

Generates comprehensive session summaries and context-preservation notes to ensure seamless work transitions.

About

The Handoff skill automates the creation of continuity documentation by summarizing completed tasks, tracking file modifications, and outlining pending items into a standardized .context/handoff.md file. By capturing the exact state of work, including verification steps and next actions, it ensures that subsequent sessions can resume immediately with full situational awareness. This reduces context-switching overhead, prevents lost progress during context compaction, and makes project states portable across different AI instances or developer shifts.

Key Features

Actionable verification steps and next-session roadmaps
Context compaction support for long-running projects
Flexible templates for both deep sessions and quick updates
Standardized .context/handoff.md output for session continuity
Automated work summarization and file change tracking
0 GitHub stars

Use Cases

Ending a coding session to ensure the AI retains exact progress for the next day
Preparing project state documentation for team collaboration or AI context resets
Switching between different project features or branches without losing momentum

About

Key Features

Actionable verification steps and next-session roadmaps
Context compaction support for long-running projects
Flexible templates for both deep sessions and quick updates
Standardized .context/handoff.md output for session continuity
Automated work summarization and file change tracking
0 GitHub stars

Use Cases

Ending a coding session to ensure the AI retains exact progress for the next day
Preparing project state documentation for team collaboration or AI context resets
Switching between different project features or branches without losing momentum