session-timeout-handler

Implement chunking and checkpoint mechanisms to resume Claude Code workflows after timeouts.

16|7|Updated Nov 20, 2025
One-click install
npx skills add https://github.com/jackspace/ClaudeSkillz --skill session-timeout-handler
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: session-timeout-handler
Source: https://github.com/jackspace/ClaudeSkillz/tree/main/skills/session-timeout-handler
Command: npx skills add https://github.com/jackspace/ClaudeSkillz --skill session-timeout-handler

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Build timeout-resistant Claude Code workflows with chunking strategies, checkpoint patterns, progress tracking, and resume mechanisms to handle 2-minute tool timeouts and ensure reliable completion of long-running operations.

Core Features & Use Cases

  • Chunking & batching: Break long tasks into manageable chunks that fit time limits.
  • Checkpoint resumes: Persist progress and resume after interruptions.
  • Checkpoint tracking: Progress visibility and resumability for robust automation.

Quick Start

Design a 2-minute chunked workflow, add a checkpoint after each chunk, and resume from the last checkpoint on re-run.

Frequently Asked Questions about session-timeout-handler

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

FAQPage Schema
How do I handle Claude Code tool timeouts in long-running workflows?

Claude Code workflows have a 2-minute timeout limit on tool execution. Handle timeouts by breaking tasks into chunks that complete within the limit, adding checkpoints after each chunk to save progress, and implementing resume logic to restart from the last checkpoint on interruption.

What's the best way to process 50+ items without hitting timeout errors?

Chunking strategies break large batch operations into smaller groups that fit within time limits. Process items in batches, persist progress after each batch completes, and resume from the last completed batch if a timeout occurs, ensuring reliable completion of bulk operations.

How do checkpoint and resume mechanisms work for workflow resilience?

Checkpoints persist workflow state after each completed chunk. On timeout or interruption, resume reads the last checkpoint and restarts from that point rather than from the beginning, eliminating duplicate work and ensuring long-running operations complete reliably.

Can I use chunking for commands that run longer than 60 seconds?

Yes. Commands exceeding 60 seconds risk timeout within the 2-minute window. Break them into smaller operations with progress tracking between steps, checkpoint results after each step, and resume if interrupted to handle long-running commands safely.

What types of tasks benefit most from timeout-resilient workflows?

Batch processing of multiple items, long-running commands over 60 seconds, bulk downloads, large API calls, and data-intensive tasks all risk timeout. Chunking and checkpoint patterns make these workloads reliable by breaking them into time-bounded segments with resumability.

How do I track progress and resumability across workflow interruptions?

Progress tracking logs completed chunks and current state. Resumability stores checkpoint data indicating where to restart. Together they provide visibility into workflow execution and enable safe re-runs from the last successful point without losing prior results.