shark-status

Check Shark background job status, completed results, and recent logs.

12|Updated Mar 17, 2026
One-click install
npx skills add https://github.com/keugenek/shark --skill shark-status
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: shark-status
Source: https://github.com/keugenek/shark/tree/main/commands/shark-status
Command: npx skills add https://github.com/keugenek/shark --skill shark-status

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

When using the Shark non-blocking execution pattern for AI agents, manually checking multiple separate files to track running background remora jobs, view completed job results, and review recent execution logs is slow and disrupts workflow.

Core Features & Use Cases

  • Active Job Monitoring: Reads pending job data to report all running background jobs, including their labels, commands, elapsed runtime, and whether they are overdue past their maximum allowed runtime.
  • Completion Result Access: Displays the full contents of the .shark-done file if it exists, so you can immediately see results from finished jobs.
  • Log Review: Shows the last 10 lines of the SHARK_LOG.md file if present, giving you quick insight into recent execution events.
  • Use Case: If you have spawned multiple remora jobs for parallel web search, server health checks, and build tests, use this skill to get a single consolidated view of all job statuses, results, and recent logs without navigating to each file individually.

Quick Start

Ask the shark-status skill to check the current status of all running shark background jobs, view any completed job results, and display the most recent log entries.

Frequently Asked Questions about shark-status

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

FAQPage Schema
How do I check the status of background jobs running in parallel?

To check the status of background jobs running in parallel, you can use a consolidated monitoring view that reads pending job data to report running labels, commands, elapsed runtime, and overdue status without manual file navigation.

What is the Shark non-blocking execution pattern for AI agents?

The Shark non-blocking execution pattern is an AI agent workflow model that spawns remora sub-jobs to run in parallel, allowing the main agent to continue operating without waiting for background tasks to complete.

How do I view completed job results and recent execution logs without opening individual files?

You can view completed job results and recent execution logs without opening individual files by using a tool that displays the contents of the .shark-done file and the last 10 lines of the SHARK_LOG.md file in a single consolidated view.

Can I monitor overdue background tasks and elapsed runtime for spawned remora jobs?

Yes, you can monitor overdue background tasks and elapsed runtime for spawned remora jobs by reading pending job data, which reports whether jobs have exceeded their maximum allowed runtime alongside their current elapsed time.

Does this background job monitoring approach work without interrupting the main agent's workflow?

Yes, this background job monitoring approach works without interrupting the main agent's workflow because it consolidates visibility into job state, completion artifacts, and execution logs through a non-blocking execution model.