skills.rest
koenvorster
koenvorsterCOMMUNITY
Explore all skills by this author →
GitHub

ollama-agents

Design and orchestrate Ollama YAML agents for local AI workflows.

Updated Aug 27, 2026
Search Tags:#agents#orchestration#yaml#ollama#system-prompt#ai-design#agent_runner
One-click install
npx skills add https://github.com/koenvorster/Personal_project_VorstersNV --skill ollama-agents
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ollama-agents
Source: https://github.com/koenvorster/Personal_project_VorstersNV/tree/main/.claude/skills/ollama-agents
Command: npx skills add https://github.com/koenvorster/Personal_project_VorstersNV --skill ollama-agents

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Streamline the design and management of Ollama YAML-based agents for local AI workflows, enabling repeatable configurations and reliable orchestration without relying on external APIs.

Core Features & Use Cases

  • Design, test, and refine system prompts for Ollama agents.
  • Select and configure models (llama3 / mistral / codellama) for each agent.
  • Orchestrate multiple agents via agent_runner.py to perform deterministic tasks.
  • Validate agent outputs against defined input/output schemas to ensure reliability.

Quick Start

Create a minimal YAML agent definition and test it with agent_runner.py.

Frequently Asked Questions about ollama-agents

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

FAQPage Schema
How do I orchestrate multiple Ollama agents for deterministic task execution?▼

You can orchestrate multiple Ollama agents by building agent_runner-based pipelines. This approach enforces structured YAML definitions and input/output schemas to ensure deterministic task execution and reliability.

What is the best way to define system prompts and select models for local AI workflows?▼

Defining system prompts and selecting models for local AI workflows is done through structured YAML configurations. This enables repeatable configurations and reliable orchestration without relying on external APIs.

Can I configure models like llama3 or mistral for different YAML agents?▼

Yes, you can select and configure models like llama3, mistral, or codellama for each agent. This model selection is handled within the YAML agent definitions to tailor the agent to specific tasks.

How do I validate agent outputs against defined schemas in Ollama YAML pipelines?▼

Validating agent outputs against defined input/output schemas ensures reliability and safety. The skill enforces these structured YAML definitions to check that agent responses meet expected formats.

Do I need external APIs to design and manage Ollama YAML agents?▼

No, you do not need external APIs to design and manage Ollama YAML agents. This approach enables repeatable configurations and reliable orchestration entirely for local AI workflows.

Why use YAML definitions for building local AI agent pipelines?▼

YAML definitions provide repeatable configurations and structured context prompts for local AI agents. This structure optimizes agent reliability and safety by enforcing strict input and output schemas.

Related Skills

Explore More Software Engineering Skills→
erichowenserichowens
181

metal-shader-expert

Optimize Metal Shader Language performance for Apple GPU rendering pipelines.

Community
Advanced
t-stringst-strings

Global Tech Stack

Enforce global tech stack standards in code generation and review tasks.

Official
Basic
IgorWarzochaIgorWarzocha
3

opencode-agent-generator

Generate OpenCode agent files with YAML frontmatter and permission controls.

Community
Basic
pacphipacphi
6

flow-nexus-swarm

Deploy and manage cloud-based AI agent swarms for event-driven workflow automation.

Community
Advanced