deepen-plan

Coordinate parallel research agents to deepen multi-section plans with best practices.

Updated Mar 22, 2026

Search Tags:#automation #planning #synthesis #workflows #plan-deepening #research-coordination

Ready to run

npx skills add https://github.com/drhazemibclc/plate --skill deepen-plan-drhazemibclc

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: deepen-plan
Source: https://github.com/drhazemibclc/plate/tree/main/.codex/skills/deepen-plan
Command: npx skills add https://github.com/drhazemibclc/plate --skill deepen-plan-drhazemibclc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the enrichment of a plan by coordinating parallel research efforts across sections, adding depth, best practices, and concrete implementation details.

Core Features & Use Cases

Spawns per-section research agents to gather best practices, patterns, and real-world implementation guidance.
Aggregates learnings from project-wide solutions to avoid repeated mistakes and promote consistency.
Generates an enhanced plan with a detailed enhancement summary, concrete patterns, and references for implementation.

Quick Start

Provide the plan path; I will deepen the plan by running parallel research and synthesis to produce an enhanced version.

Frequently Asked Questions about deepen-plan

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

FAQPage Schema

How do I deepen a plan with automated parallel research?▼

To deepen a plan with automated parallel research, provide a multi-section plan path. The system spawns per-section research agents to gather best practices and synthesize learnings into an execution-ready enhanced plan.

What is plan deepening and how does it improve workflows?▼

Plan deepening is the process of orchestrating parallel research agents to add domain-specific depth, best practices, and concrete implementation details to multi-section plans. It improves workflows by producing an enhanced plan with an execution-ready summary and references.

Can I use parallel research agents to add implementation details to a multi-section plan?▼

Yes, you can use parallel research agents to add implementation details to a multi-section plan. The system coordinates per-section deep-dives and aggregates project-wide learnings to generate concrete patterns and references.

What's the best way to synthesize learnings from multiple research agents into a single plan?▼

The best way to synthesize learnings from multiple research agents is to coordinate them to explore domain-specific sections, then aggregate their outputs. This avoids repeated mistakes and produces an enhanced plan with an execution-ready enhancement summary.

Does plan deepening require any dependencies or external components to run?▼

Plan deepening requires no external dependencies or components to run. It autonomously spawns and coordinates parallel research agents to synthesize learnings and produce an enhanced, execution-ready plan with references.

When should I not use automated plan deepening for my workflows?▼

You should not use automated plan deepening for simple, single-section tasks that lack multi-section structure. The approach is designed for multi-section plans requiring domain-specific exploration and cross-skill integration to produce concrete implementation details.