team-planner

Coordinate specialist agents to decompose and parallelize engineering tasks.

42|9|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/drvoss/everything-copilot-cli --skill team-planner-drvoss
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: team-planner
Source: https://github.com/drvoss/everything-copilot-cli/tree/main/skills/copilot-exclusive/team-planner
Command: npx skills add https://github.com/drvoss/everything-copilot-cli --skill team-planner-drvoss

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Large, multi-domain tasks often overwhelm a single agent or model and require coordinated expertise, clear ownership, and deterministic tracking; team-planner provides a Copilot CLI-native pattern to decompose work, assemble specialist agents, and monitor progress until synthesis.

Core Features & Use Cases

  • Team design and tracking: Define a team roster and task assignments using the Copilot CLI session SQL database so ownership is explicit and auditable.
  • Deterministic dispatch: Dispatch background agents via the task tool or use /fleet for automatic fan-out to execute parallel specialists.
  • Monitoring and synthesis: Poll and follow up with running agents using read_agent and write_agent, record results in SQL, and use a general-purpose synthesizer to consolidate findings.
  • Use cases: Full-stack audits combining security, performance, and architecture reviews; parallelized feature work split across domain specialists; heavyweight code-review pipelines that require pair-agent review loops.

Quick Start

Dispatch a three-person team to audit the repository for security, performance, and architecture issues and track each assignment in the SQL session database.

Frequently Asked Questions about team-planner

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

FAQPage Schema
How do I parallelize multi-domain code reviews across different specialist agents?▼

Multi-domain code reviews can be parallelized by assembling specialist agents and dispatching them via the task tool or /fleet for automatic fan-out, tracking each assignment and result in SQL session tables for deterministic monitoring and synthesis.

What is the best way to orchestrate parallel AI agents for full-stack audits?▼

Full-stack audits can be orchestrated by decomposing the task into security, performance, and architecture domains, assigning each to a specialist agent, and using SQL session tables to track ownership and poll progress until results are synthesized.

How does tracking AI agent tasks with SQL work in Copilot CLI?▼

Tracking AI agent tasks with SQL in Copilot CLI uses session database tables to define team rosters and assignments, while read_agent and write_agent primitives monitor running agents and record results for deterministic auditability.

Can I use Copilot CLI to dispatch background agents for parallel feature work?▼

Copilot CLI can dispatch background agents for parallel feature work using the task tool or /fleet command, enabling automatic fan-out to domain specialists while monitoring their progress through SQL session tables.

When should I use multiple specialist agents instead of a single model for engineering tasks?▼

Multiple specialist agents are needed when large, multi-domain tasks overwhelm a single model and require coordinated expertise, clear ownership, and deterministic tracking across domains like security, performance, and architecture.

Does team-planner require external dependencies to manage AI agent orchestration?▼

Team-planner requires no external dependencies, relying entirely on Copilot CLI primitives like SQL session tables, the task tool, /fleet, read_agent, and write_agent for deterministic dispatch, monitoring, and synthesis.