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memory-llm

Configure LLM providers for agent-memory summarization via interactive wizard.

14|3|Updated Jan 29, 2026
Search Tags:#configuration#LLM#wizard#cost-estimation#model-discovery#API-testing
One-click install
npx skills add https://github.com/SpillwaveSolutions/agent-memory --skill memory-llm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory-llm
Source: https://github.com/SpillwaveSolutions/agent-memory/tree/main/plugins/memory-setup-plugin/skills/memory-llm
Command: npx skills add https://github.com/SpillwaveSolutions/agent-memory --skill memory-llm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill guides users through configuring LLM providers for agent-memory summarization, turning a complex setup into a guided, repeatable workflow.

Core Features & Use Cases

  • Provider selection and model discovery: Choose a provider and discover compatible models with one guided flow.
  • API testing and cost awareness: Validate API access and present initial cost implications before enabling usage.
  • Quality tuning and advanced config: Expose advanced parameters and map choices to a persistent configuration file for repeatable deployments.
  • Use Case: A developer needs to switch from a cloud provider to a local Ollama model without reconfiguring multiple components.

Quick Start

Run the interactive wizard with the command: /memory-llm Then follow prompts to select provider, model, API key handling, and advanced settings. You can also run /memory-llm --test to verify the connection after setup.

Frequently Asked Questions about memory-llm

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

FAQPage Schema
How do I configure an LLM provider for agent memory summarization?▼

You can configure an LLM provider for agent memory summarization using an interactive wizard that guides provider selection, model discovery, API key handling, and advanced settings to generate a persistent configuration file.

Can I use a local Ollama model instead of cloud providers like OpenAI or Anthropic?▼

Yes, local Ollama deployments are supported alongside cloud providers like OpenAI and Anthropic. The wizard guides model discovery and API testing for your selected provider to ensure valid configuration.

How do I test my LLM API connection after setup?▼

You can test your LLM API connection after setup by running the wizard with the --test flag, which validates API access and confirms that your provider configuration is correctly established.

Does the LLM configuration wizard estimate API costs before usage?▼

Yes, the LLM configuration wizard presents initial cost implications before enabling usage, allowing you to validate API access and understand cost estimates during the provider selection process.

What is the best way to switch from a cloud LLM provider to a local model?▼

Switching from a cloud LLM provider to a local model is handled through the interactive wizard, which streamlines provider selection and reconfiguration without requiring manual updates to multiple components.

Are advanced LLM parameters exposed for quality tuning?▼

Yes, advanced parameters are exposed for quality tuning. The wizard maps these advanced settings alongside your provider choices to a persistent configuration file for repeatable deployments.

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