planning

Name: planning
Availability: InStock
Author: lauraflorentin

Decompose goals into dependency-aware step plans for execution.

1|Updated Feb 11, 2026

Search Tags:#workflow #planning #agent #orchestration #multi-step #dependency-management #planning-pattern

Ready to run

npx skills add https://github.com/LauraFlorentin/skills-marketplace --skill planning-lauraflorentin

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: planning
Source: https://github.com/LauraFlorentin/skills-marketplace/tree/main/agentic-skills/skills/planning
Command: npx skills add https://github.com/LauraFlorentin/skills-marketplace --skill planning-lauraflorentin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Planning provides a structured approach where an agent decomposes goals into ordered, dependency-aware steps before acting, reducing reactive behavior and backtracking.

Core Features & Use Cases

Plan decomposition: Convert goals into a sequence of actionable steps with explicit dependencies.
Deterministic execution flow: Enforce order and guardrails to improve reliability.
Use Case: Apply to complex tasks like research, software design, or data analysis to ensure goal-directed progress.

Quick Start

Plan the goal and execute each step with worker agents, then summarize results.

Frequently Asked Questions about planning

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

FAQPage Schema

What is plan-first reasoning for multi-step agent orchestration?▼

Plan-first reasoning decomposes goals into structured, dependency-aware step plans before execution to improve agent reliability. It reduces reactive behavior and backtracking by enforcing a deterministic execution flow with order and guardrails.

How do I manage dependencies in multi-step agent workflows?▼

You manage dependencies by having a planner generate ordered steps with explicit dependencies before a worker agent executes them. The workflow includes safeguards for error handling and a synthesizer to summarize the final results.

When do I need dependency-aware step planning for agent tasks?▼

You need dependency-aware step planning for complex tasks like research, software design, or data analysis. Planning ahead reduces errors and backtracking in these multi-step scenarios where reactive behavior would otherwise compromise goal-directed progress.

How to execute multi-step tasks using a planner and worker agent?▼

To execute multi-step tasks, a planner generates ordered steps, a worker agent executes each step with context, and a synthesizer summarizes results. This architecture enforces deterministic execution flow and dependency safeguards throughout the process.

Can I use plan decomposition for software design and data analysis?▼

Yes, you can apply plan decomposition to software design and data analysis. Converting goals into a sequence of actionable steps with explicit dependencies ensures goal-directed progress and reduces backtracking in these complex workflows.

What are the limitations of plan-first reasoning in agent orchestration?▼

Plan-first reasoning requires a planner, worker agent, and synthesizer, adding architectural overhead. It is suited for complex multi-step tasks where planning reduces errors, but may be unnecessary for simple, reactive single-step actions.