Agent skill

Letta Configuration

by letta-ai in letta-ai/skills

Configure LLM models and providers for Letta agents and servers.

MITAuto-check: notesDevOps & Cloud

Install Letta Configuration

skills CLI
$ npx skills add letta-ai/skills --skill letta-configuration -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install letta-ai/skills letta-configuration --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/letta-ai/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/letta/letta-configuration .claude/skills/letta-configuration && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
letta-configuration
GitHub stars
149
Token cost
~1.3k tokens
SKILL.md length
325 words
Files
15 (incl. scripts, references)
Skills in repo
22
Repo updated
First seen
Licence
MIT

At a glance

Configure LLM models and providers for Letta agents and servers.

  • Setting model handles
  • SKILL.md covers When to Use This Skill, Part 1: Model Configuration…, Part 2: Provider Configuration… and Anti-Hallucination Checklist, plus 1 more section
  • Runs Python and TypeScript scripts from its folder; calls python
  • Adjusting temperature/tokens

What it does

Letta Configuration is an agent skill from letta-ai/skills. Configure LLM models and providers for Letta agents and servers. Use when setting model handles, adjusting temperature/tokens, configuring provider-specific settings, setting up BYOK providers, or configuring self-hosted deployments with environment variables.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including scripts and reference files (for example `references/all_providers.md`, `references/common_providers.md` and `references/custom-endpoints.md`).

It sits in DevOps & Cloud, covering Deployment and Secrets management. It works with Letta, OpenAI, Ollama and OpenRouter. The repository describes itself as: A shared repository for skills. Intended to be used with Letta Code, Claude Code, Codex CLI, and other agents that support skills. The licence is MIT.

When your agent uses it

  • Setting model handles
  • Adjusting temperature/tokens
  • Configuring provider-specific settings
  • Setting up BYOK providers

Example prompts

  • “/letta-configuration”

Requirements

  • Python 3
  • Node.js
  • Docker

What it can do on your machine

Read from SKILL.md and the folder at commit 6785511. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 7 files in scripts/ (Python and TypeScript), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Letta Configuration loads about 1.3k tokens when it runs, and up to ~9.3k if it reads all its reference files. Until then it costs about 70 tokens; SKILL.md has 325 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:100
    # Generate .env for Docker
  • NoteMentions a .env fileSKILL.md:154
    - `scripts/generate_env.py` - Generate .env for Docker

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from letta-ai/skills at commit 6785511, republished under its MIT licence (© letta-ai). 325 words, ~1,257 tokens.

Download SKILL.mdSave it as .claude/skills/letta-configuration/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.
name
letta-configuration
description
Configure LLM models and providers for Letta agents and servers. Use when setting model handles, adjusting temperature/tokens, configuring provider-specific settings, setting up BYOK providers, or configuring self-hosted deployments with environment variables.
license
MIT

Letta Configuration

Complete guide for configuring models on agents and providers on servers.

When to Use This Skill

Agent-level (model configuration):

  • Creating agents with specific model configurations
  • Adjusting model settings (temperature, max tokens, context window)
  • Configuring provider-specific features (OpenAI reasoning, Anthropic thinking)
  • Changing models on existing agents

Server-level (provider configuration):

  • Setting up BYOK (bring your own key) providers
  • Configuring self-hosted deployments with environment variables
  • Validating provider credentials
  • Setting up custom OpenAI-compatible endpoints

Not covered here: Model selection advice (which model to choose) - see agent-development skill.


Part 1: Model Configuration (Agent-Level)

Model Handles

Models use a provider/model-name format:

ProviderHandle PrefixExample
OpenAIopenai/openai/gpt-4o, openai/gpt-4o-mini
Anthropicanthropic/anthropic/claude-sonnet-4-5-20250929
Google AIgoogle_ai/google_ai/gemini-2.0-flash
Azure OpenAIazure/azure/gpt-4o
AWS Bedrockbedrock/bedrock/anthropic.claude-3-5-sonnet
Groqgroq/groq/llama-3.3-70b-versatile
Togethertogether/together/meta-llama/Llama-3-70b
OpenRouteropenrouter/openrouter/anthropic/claude-3.5-sonnet
Ollama (local)ollama/ollama/llama3.2
Basic Model Configuration
python
from letta_client import Letta

client = Letta(api_key="your-api-key")

agent = client.agents.create(
    model="openai/gpt-4o",
    model_settings={
        "provider_type": "openai",  # Required - must match model provider
        "temperature": 0.7,
        "max_output_tokens": 4096,
    },
    context_window_limit=128000
)
Common Settings
SettingTypeDescription
provider_typestringRequired. Must match model provider (openai, anthropic, google_ai, etc.)
temperaturefloatControls randomness (0.0-2.0). Lower = more deterministic.
max_output_tokensintMaximum tokens in the response.
Changing an Agent's Model
python
client.agents.update(
    agent_id=agent.id,
    model="anthropic/claude-sonnet-4-5-20250929",
    model_settings={"provider_type": "anthropic", "temperature": 0.5},
    context_window_limit=64000
)

Note: Agents retain memory and tools when changing models.

Provider-Specific Settings

For OpenAI reasoning models and Anthropic extended thinking, see references/provider-settings.md.


Part 2: Provider Configuration (Server-Level)

Quick Start
bash
# Add provider via API
python scripts/setup_provider.py --type openai --api-key sk-...

# Generate .env for Docker
python scripts/generate_env.py --providers openai,anthropic,ollama

# Validate credentials
python scripts/validate_provider.py --provider-id provider-xxx
Add BYOK Provider
python
# Via REST API
curl -X POST http://localhost:8283/v1/providers \
  -H "Content-Type: application/json" \
  -d '{
    "name": "My OpenAI",
    "provider_type": "openai",
    "api_key": "sk-your-key-here"
  }'
Supported Provider Types

openai, anthropic, azure, google_ai, google_vertex, ollama, groq, deepseek, xai, together, mistral, cerebras, bedrock, vllm, sglang, hugging_face, lmstudio_openai

For detailed configuration of each provider, see:

  • references/common_providers.md - OpenAI, Anthropic, Azure, Google
  • references/self_hosted_providers.md - Ollama, vLLM, LM Studio
  • references/all_providers.md - Complete reference
  • references/environment_variables.md - Docker/self-hosted setup

Anti-Hallucination Checklist

Before configuring:

  • Model handle uses correct provider/model-name format
  • model_settings includes required provider_type field
  • context_window_limit is set at agent level, not in model_settings
  • Provider-specific settings use correct nested structure
  • For self-hosted: embedding model is specified
  • Temperature is within valid range (0.0-2.0)

Scripts

Model configuration:

  • scripts/basic_config.py - Basic model configuration
  • scripts/basic_config.ts - TypeScript equivalent
  • scripts/change_model.py - Changing models on existing agents
  • scripts/provider_specific.py - OpenAI reasoning, Anthropic thinking

Provider configuration:

  • scripts/setup_provider.py - Add providers via REST API
  • scripts/validate_provider.py - Check provider credentials
  • scripts/generate_env.py - Generate .env for Docker

© letta-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 14 other files (scripts, references) in letta/letta-configuration of letta-ai/skills.

  • SKILL.md
  • LICENSE
  • references/all_providers.md
  • references/common_providers.md
  • references/custom-endpoints.md
  • references/environment_variables.md
  • references/provider-settings.md
  • references/self_hosted_providers.md
  • scripts/basic_config.py
  • scripts/basic_config.ts
  • scripts/change_model.py
  • scripts/generate_env.py
  • scripts/provider_specific.py
  • scripts/setup_provider.py
  • scripts/validate_provider.py

Open the folder on GitHubat commit 6785511

Compare with similar skills

Letta Configuration next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Capacitymicrosoft/GitHub-Copilot-for-Azure2551 repos~1.7kAutomated safety check: PassMIT
Azure Bicep Skilltimothywarner-org/claude-code224—~2.9kAutomated safety check: PassMIT
Deploy Modelmicrosoft/GitHub-Copilot-for-Azure2551 repos~1.8kAutomated safety check: PassMIT
Deploynoskillish/bankmcp277—~744Automated safety check: PassMIT

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Categories

Questions about Letta Configuration

What does Letta Configuration do?

Configure LLM models and providers for Letta agents and servers. Letta Configuration is an agent skill from letta-ai/skills. Configure LLM models and providers for Letta agents and servers.

When should I use Letta Configuration?

Letta Configuration fits situations like: setting model handles; adjusting temperature/tokens; configuring provider-specific settings; setting up BYOK providers.

How do I install Letta Configuration in Claude Code?

Run `npx skills add letta-ai/skills --skill letta-configuration -a claude-code`. Or copy the skill folder (letta/letta-configuration in letta-ai/skills) into .claude/skills/letta-configuration in your project. Claude Code loads it when a task matches its description.

How do I install Letta Configuration in Codex?

Run `npx skills add letta-ai/skills --skill letta-configuration -a codex`. Or copy the skill folder (letta/letta-configuration in letta-ai/skills) into .agents/skills/letta-configuration in your project. Codex loads it when a task matches its description.

Can I use Letta Configuration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add letta-ai/skills --skill letta-configuration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/letta-configuration, .gemini/skills/letta-configuration, .github/skills/letta-configuration and .opencode/skills/letta-configuration in your project.

What does Letta Configuration need to run?

Going by SKILL.md and its folder, Letta Configuration needs Python and TypeScript for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3; Node.js; Docker.

Does Letta Configuration access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Letta Configuration safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Letta Configuration use?

Letta Configuration is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Letta Configuration use?

About 1.3k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8k tokens, read only when the agent opens those files.

What are the alternatives to Letta Configuration?

Skills that share tags, products or a category with Letta Configuration: Azure Architecture Autopilot (github/awesome-copilot, 40k stars), Capacity (microsoft/GitHub-Copilot-for-Azure, 255 stars), Azure Bicep Skill (timothywarner-org/claude-code, 224 stars) and Deploy Model (microsoft/GitHub-Copilot-for-Azure, 255 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Letta Configuration?

letta-ai (a GitHub organization) maintains it in letta-ai/skills, which has 149 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 1, 2026.

Source: letta-ai/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.