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by softaworkssoftaworks/agent-toolkit2.5k stars
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Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.

Use this Skill: https://skilld.dev/gh/softaworks/agent-toolkit/session-handoff

This session only. Nothing lands on disk.

README.md

≈1.8k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Session Handoff Skill

Overview

The Session Handoff skill creates comprehensive handoff documents that enable fresh AI agents to seamlessly continue work with zero ambiguity. It solves the long-running agent context exhaustion problem by preserving complete context, decisions, and state across sessions.

Purpose

When working on complex, multi-session projects with AI agents, context gets lost between sessions. This skill provides a structured approach to:

  • Preserve context - Capture all critical information before context window fills
  • Enable continuity - Allow new agents to pick up exactly where you left off
  • Document decisions - Record architectural choices and their rationale
  • Track progress - Maintain clear status of completed and pending work
  • Chain sessions - Link related handoffs for long-running projects

When to Use

User-Triggered

  • User says "save state", "create handoff", "I need to pause"
  • User requests "load handoff", "resume from", "continue where we left off"
  • User mentions "context is getting full" or "save this for later"

Agent-Triggered (Proactive)

  • Context window approaching capacity (>80% full)
  • Major task milestone completed
  • Work session ending with significant progress
  • After substantial work (5+ file edits, complex debugging, architecture decisions)
  • Before switching to a different task

Resumption Scenarios

  • Starting a new session on an existing project
  • Different agent needs to continue the work
  • Need to recall decisions made in previous sessions
  • Picking up after a long break

How It Works

The skill operates in two primary modes:

CREATE Mode

Generates a comprehensive handoff document capturing current state:

  1. Generate Scaffold - Smart script pre-fills metadata (timestamp, git status, modified files)
  2. Complete Document - Fill in critical sections (state, context, decisions, next steps)
  3. Validate - Automated checks for completeness, quality, and security
  4. Confirm - Present location and summary to user

RESUME Mode

Loads and validates existing handoff documents:

  1. Find Handoffs - List available handoffs in project
  2. Check Staleness - Assess if context is still current
  3. Load Document - Read handoff (and chain if linked)
  4. Verify Context - Validate assumptions and environment
  5. Begin Work - Start from "Immediate Next Steps"

Key Features

Smart Scaffolding

The create_handoff.py script automatically captures:

  • Timestamp and project path
  • Current git branch and recent commits
  • Modified and unstaged files
  • Handoff chain links (if continuing from previous)

Validation & Quality Assurance

The validate_handoff.py script checks:

  • No incomplete [TODO: ...] placeholders
  • All required sections populated
  • No potential secrets (API keys, passwords, tokens)
  • Referenced files exist
  • Quality score (0-100)

Staleness Detection

The check_staleness.py script assesses:

  • Time elapsed since handoff creation
  • Git commits made since handoff
  • Files changed since handoff
  • Branch divergence
  • Missing referenced files

Handoff Chaining

For long-running projects, chain handoffs together:

handoff-1.md (initial work)
    ↓
handoff-2.md --continues-from handoff-1.md
    ↓
handoff-3.md --continues-from handoff-2.md

Each handoff links to its predecessor, providing context breadcrumbs for new agents.

Usage Examples

Creating a Handoff

Basic handoff creation:

python scripts/create_handoff.py implementing-user-auth

Continuation handoff (linked to previous):

python scripts/create_handoff.py "auth-part-2" --continues-from 2024-01-15-auth.md

Validate before finalizing:

python scripts/validate_handoff.py .claude/handoffs/2024-01-15-143022-implementing-auth.md

Resuming from a Handoff

List available handoffs:

python scripts/list_handoffs.py

Check if handoff is current:

python scripts/check_staleness.py .claude/handoffs/2024-01-15-143022-implementing-auth.md

Load and continue work:

  1. Read the handoff document completely
  2. Verify context using resume checklist
  3. Start with first item in "Immediate Next Steps"

Handoff Document Structure

A complete handoff includes:

  1. Metadata - Timestamp, project path, git branch, commits
  2. Current State Summary - What's happening right now
  3. Important Context - Critical information for next agent
  4. Decisions Made - Architectural choices with rationale
  5. Immediate Next Steps - Clear, actionable first steps
  6. Pending Work - Remaining tasks and priorities
  7. Critical Files - Important locations and their purpose
  8. Key Patterns Discovered - Conventions and approaches
  9. Potential Gotchas - Known issues and workarounds
  10. Handoff Chain - Links to previous/next handoffs

See references/handoff-template.md for the complete template.

Storage Location

Handoffs are stored in: .claude/handoffs/

Naming convention: YYYY-MM-DD-HHMMSS-[slug].md

Example: 2024-01-15-143022-implementing-auth.md

Scripts Reference

Script Purpose Usage
create_handoff.py Generate new handoff with smart scaffolding python scripts/create_handoff.py [slug] [--continues-from <file>]
list_handoffs.py List available handoffs in a project python scripts/list_handoffs.py [path]
validate_handoff.py Check completeness, quality, and security python scripts/validate_handoff.py <file>
check_staleness.py Assess if handoff context is still current python scripts/check_staleness.py <file>

Quality Standards

Do not finalize a handoff if:

  • Validation score is below 70
  • Secrets are detected
  • [TODO: ...] placeholders remain
  • Required sections are empty

Best practices:

  • Write clear, specific next steps (not vague goals)
  • Document the "why" behind decisions, not just the "what"
  • Include code snippets for critical patterns
  • Reference specific file paths and line numbers
  • Update handoffs as work progresses

References

Benefits

  • Zero ambiguity - New agents know exactly what to do
  • Context preservation - No loss of critical information
  • Decision history - Understand why choices were made
  • Reduced onboarding - Faster agent startup on existing work
  • Quality assurance - Automated validation prevents incomplete handoffs
  • Security - Secret detection prevents credential leaks
  • Long-term memory - Handoff chains maintain project history

Source: SKILL.md on GitHub

1 warning17d5 checks · Risk SAFE
  • Gen Agent Trust Hub17d

    The Session Handoff skill manages markdown documents to preserve context between AI agent sessions. It uses Python scripts to collect project metadata via Git and validate document quality. Analysis identified that the skill executes local shell commands (Git) and ingests external project metadata, such as commit messages, which presents a surface for indirect prompt injection.

  • Socket17d

    No alerts

  • Snyk17d

    Risk: LOW · No issues

  • Runlayer7mo

    4/12 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at 1c0662a. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 months ago.

Dormantupdated 9 months ago
  • session-handoff
  • context-management
  • agent-continuity
  • memory-preservation
  • long-running-tasks
  • workflow-persistence
  • handoff-documentation
  • state-capture

README badge

README badge for softaworks/agent-toolkit/session-handoff

Generates handoff documents that preserve project state, context, and pending work so fresh AI agents can resume without ambiguity. Addresses long-running sessions where context windows fill up by capturing current state, decisions made, critical files, and immediate next steps in a chainable format.

Generated from the current SKILL.md.

When should I create a handoff?
Create a handoff when the user requests to save state, pause work, or says context is getting full. Also proactively suggest one after substantial work like 5+ file edits, complex debugging, or major architecture decisions.
Can I chain handoffs together for long-running projects?
Yes. Use the `--continues-from` flag when creating a new handoff to link it to a previous one, creating a context chain that new agents can follow.
What does the validation script check for?
The validator checks for remaining TODO placeholders, required sections, potential secrets (API keys, passwords, tokens), file existence, and generates a quality score. Do not finalize a handoff with detected secrets or a score below 70.
How do I know if a handoff is still usable when resuming?
Run the staleness checker, which assesses based on time elapsed, git commits, file changes, branch divergence, and missing files. It returns FRESH, SLIGHTLY_STALE, STALE, or VERY_STALE status.
Where are handoffs stored?
Handoffs are stored in `.claude/handoffs/` with timestamped filenames like `2024-01-15-143022-implementing-auth.md`.

Generated from the current SKILL.md. These answers refresh after source changes.