llmn

Plan nutritionally optimized meals via the llmn CLI with YAML profiles.

2|Updated Dec 25, 2025
One-click install
npx skills add https://github.com/ddarmon/llmn --skill llmn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: llmn
Source: https://github.com/ddarmon/llmn/tree/main/.claude/skills/llmn
Command: npx skills add https://github.com/ddarmon/llmn --skill llmn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Plan nutritionally optimized meals by leveraging the llmn CLI to generate meal plans that meet calorie and macro targets, reducing manual planning time.

Core Features & Use Cases

  • Interactive, goal-driven meal planning that respects user constraints (calories, protein, macros) and generates per-meal breakdowns.
  • Workflow-guided optimization using template or multi-period modes, with what-if analysis and feasibility diagnosis.
  • Easy export and integration with LLM prompts for recipe generation and detailed meal plans.

Quick Start

Ask the user for their dietary goals and run a template-based optimization to generate a realistic daily meal plan.

Frequently Asked Questions about llmn

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

FAQPage Schema
How do I plan nutritionally optimized meals with calorie and macro targets?

To plan nutritionally optimized meals, you need a system that respects your constraints like calories and macros to generate a per-meal breakdown. This process uses a deterministic optimization workflow via the llmn CLI to produce a realistic daily meal plan.

Do I need Python to use the llmn CLI for meal planning?

Yes, you need Python 3.11+ installed to use the llmn CLI for meal planning. The deterministic optimization workflow runs through uv run llmn commands to generate your meal plans.

What is the best way to generate a daily meal plan that meets specific dietary constraints?

The best way to generate a daily meal plan is through a goal-driven optimization workflow. You gather dietary goals, check user profiles, create constraints, and run a template-based optimization to produce a realistic per-meal breakdown.

Can I use YAML profiles for meal planning optimization?

Yes, you can use optional YAML profiles for meal planning optimization. These profiles integrate with the llmn CLI to guide the optimization modes and generate per-meal breakdowns and feasibility feedback.

Why does my meal optimization workflow return feasibility feedback instead of a meal plan?

Your meal optimization workflow returns feasibility feedback when your dietary constraints are unachievable. The llmn CLI provides this diagnosis during the optimization process to indicate that the calorie and macro targets cannot be met.