do:deepen-plan

Orchestrate parallel research and review agents to enhance existing plans.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/adamfeldman/compound-workflows --skill do-deepen-plan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: do:deepen-plan
Source: https://github.com/adamfeldman/compound-workflows/tree/main/plugins/compound-workflows/skills/do-deepen-plan
Command: npx skills add https://github.com/adamfeldman/compound-workflows --skill do-deepen-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires init-values.sh, capture-stats.sh, validate-stats.sh, and includes scripts (resource) components.

What problem does it solve?

This Skill automates the enhancement of existing plans by orchestrating parallel research, skill, and review agents, while ensuring all outputs are persisted to disk to prevent context exhaustion.

Core Features & Use Cases

  • Context-Lean Operation: All agent outputs are written to disk, keeping the parent agent's context lean and allowing for longer sessions.
  • Persistent Outputs: All outputs are retained across runs for traceability and learning, with each run getting its own numbered directory.
  • Automated Discovery: Discovers available skills, learnings, and review/research agents dynamically.
  • Use Case: You have a complex software feature plan. Use this Skill to automatically research best practices, identify potential security vulnerabilities, and analyze the architecture, all while ensuring the detailed findings are saved for later review without filling up the AI's memory.

Quick Start

Use the do:deepen-plan skill to deepen the plan located at 'plans/feature-x-plan.md'.

Frequently Asked Questions about do:deepen-plan

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

FAQPage Schema
How do I enhance a software feature plan without exhausting AI context limits?

Plan enhancement is automated by orchestrating parallel research, skill, and review agents. All agent outputs are persisted to disk, keeping the parent agent's context lean and preventing context exhaustion during long sessions.

What is the best way to research best practices and security vulnerabilities for an existing architecture plan?

Use automated plan enhancement to dynamically discover available research and review agents. These agents execute in batches to analyze architecture and identify vulnerabilities, writing comprehensive findings directly to disk for later review.

Can I retain research agent outputs across multiple runs for traceability?

Yes, persistent outputs are retained across runs for traceability and learning. Each execution gets its own numbered directory on disk, ensuring all research findings and plan improvements are saved without filling up memory.

How do I manage agent orchestration for complex code review and context management tasks?

Agent orchestration manages execution in batches with robust error handling and stats capture. It dynamically discovers available skills and learnings, coordinating a multi-phase synthesis and triage process for comprehensive plan improvement.

Does deepening a plan require manual initialization of research and review agents?

No, automated discovery dynamically finds available skills, learnings, and review or research agents. You simply point the skill to your existing plan file, and it handles the parallel agent execution and multi-phase synthesis automatically.