supervise

Plan and execute autonomous AI agent team leadership over multi-hour sessions.

Updated Feb 27, 2026

Search Tags:#workflow #long-running #autonomous #task-orchestration #team-coordination #ai-management

Ready to run

npx skills add https://github.com/danny0926/NLP-data-for-trading --skill supervise

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: supervise
Source: https://github.com/danny0926/NLP-data-for-trading/tree/main/.claude/skills/supervise
Command: npx skills add https://github.com/danny0926/NLP-data-for-trading --skill supervise

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Autonomously governs an AI-driven agent team, taking over decision-making, task assignment, monitoring, and anomaly handling to keep long-running projects on track without constant human input.

Core Features & Use Cases

Autonomous leadership: directs R&D priorities, allocates tasks, and tracks progress across the team during extended runs.
Cross-context coordination: supports 2+ hour headless operation and seamless relay across context windows.
Monitoring & recovery: detects anomalies, restarts or reassigns work, and produces comprehensive progress reports.
Runtime orchestration: maintains persistent state, manages a dynamic task queue, and interfaces with the Task system to sustain momentum.

Quick Start

Start a session by specifying a duration and strategic direction to hand off control to the autonomous CEO.

Frequently Asked Questions about supervise

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

FAQPage Schema

How do I automate task orchestration for an AI agent team over long-running sessions?▼

You automate task orchestration by specifying a duration and strategic direction, enabling the system to autonomously direct research, allocate tasks, and maintain persistent state across multi-hour headless sessions.

What is cross-context handoff in autonomous AI workflow management?▼

Cross-context handoff in autonomous AI workflows enables continuous task execution across context windows during multi-hour headless sessions, maintaining persistent state and recovering from anomalies without human intervention.

How do I start a headless session for autonomous team coordination?▼

Start a headless session by providing a duration and strategic direction as inputs, which hands off control to the autonomous system to manage the dynamic task queue and coordinate the agent team.

Can I monitor progress and handle anomalies in long-running AI agent workflows?▼

Yes, anomaly monitoring in long-running AI agent workflows is supported via persistent state tracking in supervisor_state.json, which detects issues, restarts or reassigns work, and generates comprehensive progress reports.

Does autonomous AI workflow orchestration work with standard file and web tools?▼

Autonomous AI workflow orchestration leverages standard tools including Read, Glob, Bash, Edit, Task, WebSearch, and WebFetch to execute tasks, manage dynamic queues, and interface with the Task system during extended runs.

When should I use an autonomous CEO mode for AI agent team coordination?▼

Use autonomous CEO mode for AI agent team coordination when long-running projects require extended headless operation, dynamic task allocation, and anomaly recovery without constant human input or manual intervention.