paperclip

Manage tasks and assignments via the Paperclip control plane API.

1|Updated Mar 31, 2026
One-click install
npx skills add https://github.com/kangnam7654/stapler --skill paperclip-kangnam7654
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paperclip
Source: https://github.com/kangnam7654/stapler/tree/main/desktop/resources/skills/paperclip
Command: npx skills add https://github.com/kangnam7654/stapler --skill paperclip-kangnam7654

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Interact with the Paperclip control plane to coordinate tasks, governance, and cross-agent work, reducing manual overhead and improving consistency across runs.

Core Features & Use Cases

  • Manage tasks, assignments, and governance via the Paperclip API to streamline coordination.
  • Coordinate multiple agents through heartbeat-driven workflows, including status updates and comments.
  • Enforce authentication, run-audit headers, and input validation to maintain security and traceability.

Quick Start

Ask Paperclip to coordinate tasks and update a task's status via the control plane.

Frequently Asked Questions about paperclip

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

FAQPage Schema
How do I coordinate AI task assignments across multiple agents?

You coordinate AI task assignments by interfacing with the Paperclip control plane API to manage tasks, update statuses, delegate work, and enforce governance across multiple agents.

What is a heartbeat workflow for AI agent coordination?

A heartbeat workflow is a recurring process where AI agents check assignments, post comments, update task statuses, and call control plane API endpoints to maintain continuous synchronization.

Can I enforce authentication and auditing when managing tasks via API?

Yes, you can enforce authentication requirements, run auditing headers, and validate inputs to ensure secure, auditable interactions when managing tasks and governance via the control plane API.

How do I update a task status and post comments through the control plane?

You update a task status and post comments by calling the control plane API endpoints within a heartbeat workflow, delegating work and applying input validation to maintain traceability.

What are the limitations of manual AI task management without a control plane?

Without a control plane, manual overhead increases and consistency across runs decreases, lacking enforced authentication, run-audit headers, and input validation for secure cross-agent work.