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AngelMaldonado
AngelMaldonadoCOMMUNITY
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Website𝕏@amaldonado_07GitHub

cx-supervise

Coordinate distributed tasks across AI agents with session-based tracking.

Updated Mar 25, 2026
Search Tags:#automation#multi-agent#orchestration#progress-tracking#task-distribution#coordinate
One-click install
npx skills add https://github.com/AngelMaldonado/skills --skill cx-supervise
Or copy as Structured Prompt for Agentβ–Ό
Please help me install this Agent Skill.
Skill: cx-supervise
Source: https://github.com/AngelMaldonado/skills/tree/main/.claude/skills/cx-supervise
Command: npx skills add https://github.com/AngelMaldonado/skills --skill cx-supervise

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinate multi-agent workflows by distributing tasks, tracking progress, and aggregating results across agents to accelerate complex projects.

Core Features & Use Cases

  • Task decomposition: break complex tasks into independent subtasks and assign to suitable agents.
  • Progress tracking: monitor subtask status with session-based logging and aggregation.
  • Blocker escalation: detect blockers and escalate to the developer for timely resolution.

Quick Start

Dispatch a complex task by outlining subtasks and starting a coordinated session with a unique session_id.

Frequently Asked Questions about cx-supervise

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

FAQPage Schema
How do I coordinate multi-agent workflows across distributed AI agents?β–Ό

Multi-agent workflows are coordinated by decomposing complex tasks into independent subtasks, assigning them to suitable agents, and aggregating results using a unique session_id for centralized logging and progress tracking.

How does session-based progress tracking work for parallelized AI tasks?β–Ό

Session-based progress tracking operates by propagating a required session_id across distributed subtasks, enabling centralized logging and real-time aggregation of subtask status to monitor the overall workflow execution.

What's the best way to decompose complex data analysis or code generation projects for multiple agents?β–Ό

The best way to decompose complex projects is to break them down into independent subtasks with clear acceptance criteria, allowing them to be parallelized and assigned to suitable AI agents for execution.

Can I use this to escalate blockers detected during distributed task execution?β–Ό

Yes, you can escalate blockers detected during distributed task execution. The orchestration mechanism detects subtask blockers and escalates them directly to the developer to ensure timely resolution.

Do I need to propagate a session_id for every subtask in an orchestrated workflow?β–Ό

Yes, session_id propagation is required for every subtask. It enforces session-based tracking, centralized logging, and accurate progress aggregation across all distributed AI agents.

When should I not use multi-agent orchestration for project task distribution?β–Ό

Multi-agent orchestration should be avoided when a complex task cannot be cleanly decomposed into independent subtasks with clear acceptance criteria, as the coordination overhead outweighs the benefits of parallelized execution.

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