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Guide for adding new LLM models to Letta Code. An agent skill from letta-ai/letta-code.
Apache-2.0Auto-check passed
Install Adding Models
$ npx skills add letta-ai/letta-code --skill adding-models -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install letta-ai/letta-code adding-models --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/letta-ai/letta-code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.skills/adding-models .claude/skills/adding-models && rm -rf skills-srcUse ~/.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/
Install the "adding-models" agent skill from https://github.com/letta-ai/letta-code/tree/main/.skills/adding-models into .claude/skills/adding-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-models", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/letta-ai/letta-code/tree/main/.skills/adding-modelsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add letta-ai/letta-code --skill adding-models -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install letta-ai/letta-code adding-models --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/letta-ai/letta-code.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.skills/adding-models .agents/skills/adding-models && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "adding-models" agent skill from https://github.com/letta-ai/letta-code/tree/main/.skills/adding-models into .agents/skills/adding-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-models", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add letta-ai/letta-code --skill adding-models -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install letta-ai/letta-code adding-models --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/letta-ai/letta-code.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.skills/adding-models .cursor/skills/adding-models && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "adding-models" agent skill from https://github.com/letta-ai/letta-code/tree/main/.skills/adding-models into .cursor/skills/adding-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-models", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/letta-ai/letta-code.git --path .skills/adding-models--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add letta-ai/letta-code --skill adding-models -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install letta-ai/letta-code adding-models --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/letta-ai/letta-code.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.skills/adding-models .gemini/skills/adding-models && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "adding-models" agent skill from https://github.com/letta-ai/letta-code/tree/main/.skills/adding-models into .gemini/skills/adding-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-models", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install letta-ai/letta-code adding-modelsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add letta-ai/letta-code --skill adding-models -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/letta-ai/letta-code.git skills-src && mkdir -p .github/skills && cp -r skills-src/.skills/adding-models .github/skills/adding-models && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "adding-models" agent skill from https://github.com/letta-ai/letta-code/tree/main/.skills/adding-models into .github/skills/adding-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-models", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add letta-ai/letta-code --skill adding-models -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install letta-ai/letta-code adding-models --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/letta-ai/letta-code.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.skills/adding-models .opencode/skills/adding-models && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "adding-models" agent skill from https://github.com/letta-ai/letta-code/tree/main/.skills/adding-models into .opencode/skills/adding-models/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adding-models", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
adding-models- GitHub stars
- 3.5k
- Token cost
- ~1k tokens
- SKILL.md length
- 443 words
- Files
- 1
- Skills in repo
- 25
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Guide for adding new LLM models to Letta Code. An agent skill from letta-ai/letta-code.
- Works in 4 steps: Find Valid Model Handles → Update the Owning Catalog → Test the Model → …
- The user wants to add support for a new model
- SKILL.md covers Quick Reference, Workflow, Toolset Detection and Common Issues
- Calls curl, jq and bun; reaches api.letta.com
What it does
Adding Models is an agent skill from letta-ai/letta-code. Guide for adding new LLM models to Letta Code. Use when the user wants to add support for a new model, needs to know valid model handles, or wants to update model-specific compatibility behavior. Covers runtime catalog sources, CI test matrices, and handle validation.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It works with Letta. The repository describes itself as: Stateful agents that are like people, with memory, identity, and the ability to learn and adapt. The licence is Apache-2.0.
When your agent uses it
- The user wants to add support for a new model
- Needs to know valid model handles
- Wants to update model-specific compatibility behavior
Example prompts
- “/adding-models”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 42397c7. 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
Shell commands in SKILL.md call:
curljqbun
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
api.letta.com
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
Adding Models loads about 1k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 443 words of instructions outside code blocks.
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 passed
The automated check found no risky patterns in SKILL.md.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from letta-ai/letta-code at commit 42397c7, republished under its Apache-2.0 licence (© letta-ai). 443 words, ~1,048 tokens.
Download SKILL.mdSave it as
.claude/skills/adding-models/SKILL.md (or your agent's skills folder).- name
- adding-models
- description
- Guide for adding new LLM models to Letta Code. Use when the user wants to add support for a new model, needs to know valid model handles, or wants to update model-specific compatibility behavior. Covers runtime catalog sources, CI test matrices, and handle validation.
Adding Models
This skill guides you through adding a new LLM model to Letta Code.
Quick Reference
Key files:
src/agent/remote-model-catalog.ts- Runtime catalog loading and projectionsrc/agent/model-catalog.ts- Model lookup and compatibility aliases.github/workflows/ci.yml- CI test matrix (optional)src/tools/manager.ts- Toolset detection logic (rarely needed)
Workflow
Step 1: Find Valid Model Handles
First identify the agent source. These inputs are deliberately different:
| Agent source | Rows shown | Labels, presets, and capabilities |
|---|---|---|
| Cloud hosted | GET /v1/models/catalog only | GET /v1/models/catalog |
| Cloud organization BYOK | BYOK rows from GET /v1/models | Match to catalog metadata using provider metadata and model name; retain the BYOK handle for selection |
| Local | pi-ai inventory | pi-ai metadata |
| Custom App Server | Server runtime inventory | Server runtime metadata |
In Cloud mode, never use base/hosted rows from GET /v1/models to filter,
supplement, delay, or provide a fallback for the hosted catalog. This once made
GPT-4o appear in a selector even though the Cloud catalog deliberately omitted
it. GET /v1/models remains necessary for organization-specific BYOK rows.
Query the Cloud hosted catalog to see hosted preset IDs, handles, and capabilities:
curl -s https://api.letta.com/v1/models/catalog | jq '.models[] | [.id, .handle]'To inspect organization BYOK rows from a Cloud backend, query its model
inventory and filter by provider_category:
curl -s https://api.letta.com/v1/models/ \
| jq '.[] | select(.provider_category == "byok") | [.handle, .provider_type]'Do not use this response as a second hosted catalog.
Common provider prefixes:
anthropic/- Claude modelsopenai/- GPT modelsgoogle_ai/- Gemini modelsgoogle_vertex/- Vertex AIopenrouter/- Various providers
Show full SKILL.md (227 more words)Show less
Step 2: Update the Owning Catalog
Letta Code does not bundle a model catalog:
- Cloud hosted rows and presets come from the server's
GET /v1/models/catalogresponse. - Cloud
GET /v1/modelscontributes only organization BYOK rows to selectors. - Local model inventory comes from pi-ai and the active provider runtimes.
Add the model at the source that owns it. A hosted preset belongs in the server catalog. A local provider model belongs in pi-ai or that provider's discovery runtime.
Only change this repository when the model needs Letta Code-specific compatibility behavior, such as preserving an established CLI alias or recognizing a new provider for toolset selection. Keep that logic narrow and derive the handle and metadata from the runtime catalog rather than copying model definitions here.
Step 3: Test the Model
Test with headless mode:
bun run src/index.ts --new --model <model-id> -p "hi, what model are you?"Example:
bun run src/index.ts --new --model gemini-3-flash -p "hi, what model are you?"Step 4: Add to CI Test Matrix (Optional)
To include the model in automated testing, add it to .github/workflows/ci.yml:
# Find the headless job matrix around line 122
model: [gpt-5-minimal, gpt-4.1, sonnet-4.5, gemini-pro, your-new-model, glm-4.6, haiku]Toolset Detection
Models are automatically assigned toolsets based on provider:
openai/*→codextoolsetgoogle_ai/*orgoogle_vertex/*→geminitoolset- Others →
defaulttoolset
This is handled by isGeminiModel() and isOpenAIModel() in src/tools/manager.ts. You typically don't need to modify this unless adding a new provider.
Common Issues
"Handle not found" error: The model handle is incorrect. Run the validation script to see valid handles.
Model works but wrong toolset: Check src/tools/manager.ts to ensure the provider prefix is recognized.
© letta-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .skills/adding-models of letta-ai/letta-code.
Open the folder on GitHubat commit 42397c7
Compare with similar skills
Adding Models 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Adding Models this skillletta-ai/letta-code | 3.5k | — | ~1k | Automated safety check: Pass | Apache-2.0 | |
| Lettabotletta-ai/lettabot | 326 | — | ~3.4k | Automated safety check: Pass | Apache-2.0 | |
| Creating Letta Code Channelsletta-ai/skills | 147 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Letta Configurationletta-ai/skills | 147 | — | ~1.3k | Automated safety check: Notes | MIT | |
| Letta Filesystem To Memfsletta-ai/skills | 147 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Navigating Chatgpt Historyletta-ai/skills | 147 | — | ~1.3k | Automated safety check: Pass | MIT |
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Questions about Adding Models
What does Adding Models do?
Guide for adding new LLM models to Letta Code. An agent skill from letta-ai/letta-code. Adding Models is an agent skill from letta-ai/letta-code. Guide for adding new LLM models to Letta Code.
When should I use Adding Models?
Adding Models fits situations like: the user wants to add support for a new model; needs to know valid model handles; wants to update model-specific compatibility behavior.
How do I install Adding Models in Claude Code?
Run `npx skills add letta-ai/letta-code --skill adding-models -a claude-code`. Or copy the skill folder (.skills/adding-models in letta-ai/letta-code) into .claude/skills/adding-models in your project. Claude Code loads it when a task matches its description.
How do I install Adding Models in Codex?
Run `npx skills add letta-ai/letta-code --skill adding-models -a codex`. Or copy the skill folder (.skills/adding-models in letta-ai/letta-code) into .agents/skills/adding-models in your project. Codex loads it when a task matches its description.
Can I use Adding Models 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/letta-code --skill adding-models -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/adding-models, .gemini/skills/adding-models, .github/skills/adding-models and .opencode/skills/adding-models in your project.
What does Adding Models need to run?
Going by SKILL.md and its folder, Adding Models needs the command-line tools its instructions call (curl, jq and bun).
Does Adding Models access the network?
SKILL.md names 1 domain. In commands or code: api.letta.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Adding Models safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Adding Models use?
Adding Models is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Adding Models use?
About 1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Adding Models?
Skills that share tags, products or a category with Adding Models: Lettabot (letta-ai/lettabot, 326 stars), Creating Letta Code Channels (letta-ai/skills, 147 stars), Letta Configuration (letta-ai/skills, 147 stars) and Letta Filesystem To Memfs (letta-ai/skills, 147 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Adding Models?
letta-ai (a GitHub organization) maintains it in letta-ai/letta-code, which has 3,541 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 8, 2026.
Source: letta-ai/letta-code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.