set-task-timeout

Name: set-task-timeout
Availability: InStock
Author: OpenAkita

Adjust progress and hard timeout thresholds for the current AI task.

2.0k|267|Updated Jan 30, 2026

Search Tags:#task management #configuration #system settings #long-running tasks #timeout

Ready to run

npx skills add https://github.com/openakita/openakita --skill set-task-timeout

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: set-task-timeout
Source: https://github.com/openakita/openakita/tree/main/skills/system/set-task-timeout
Command: npx skills add https://github.com/openakita/openakita --skill set-task-timeout

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill allows you to dynamically adjust the timeout settings for the current task, preventing premature task termination due to long processing times or aggressive model switching.

Core Features & Use Cases

Prevent premature timeouts: Ideal for long-running tasks where the system might incorrectly flag them as stuck.
Optimize model switching: Avoid the system switching to a new model too quickly if the current one is making steady progress.
Use Case: Before starting a complex web scraping task that is expected to take several hours, use this skill to increase the progress_timeout_seconds to 3600 seconds to ensure it completes without interruption.

Quick Start

Use the set-task-timeout skill to set the progress timeout to 1800 seconds and provide a reason for the adjustment.

Frequently Asked Questions about set-task-timeout

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

FAQPage Schema

How do I prevent my long-running tasks from timing out prematurely?▼

To prevent premature task termination, you can adjust the timeout policy by increasing the progress timeout threshold in seconds, which stops the system from incorrectly flagging long-running operations as stuck.

Why does the system switch models too quickly during steady progress?▼

Aggressive model switching occurs when the progress timeout threshold is too low. Increasing the progress timeout seconds prevents the system from interrupting a model that is making steady progress on a complex operation.

Can I dynamically change timeout settings for a current AI task?▼

Yes, you can dynamically adjust timeout settings for the current task by providing an integer value for the new progress or hard timeout threshold in seconds and a string explaining the reason for the adjustment.

What is the best way to configure timeout settings for a web scraping task?▼

The best way to configure timeout settings for a web scraping task is to set the progress timeout seconds to a higher value, such as 3600, ensuring the operation completes without interruption from idle detection mechanisms.

What are the limitations of adjusting task timeout settings?▼

Limitations include the requirement to provide integer values for timeout durations and a string for the reason, meaning you cannot use fractional seconds or omit the justification when modifying progress and hard timeout thresholds.

Do I need a specific reason to modify progress timeout thresholds?▼

Yes, providing a reason string is required when you modify progress or hard timeout thresholds, ensuring there is a documented justification for adjusting the system's idle detection and timeout policy.