letta-ai/letta-code

ملف letta-ai

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# Letta Code [![npm](https://img.shields.io/npm/v/@letta-ai/letta-code.svg?style=flat-square)](https://www.npmjs.com/package/@letta-ai/letta-code) [![Discord](https://img.shields.io/badge/discord-join-blue?style=flat-square&logo=discord)](https://discord.gg/letta) Letta Code is a stateful agent harness for creating agents that are more like people than tools. Letta Code agents have memory, identity, and a sense of experience over time. They learn and evolve over long horizons through rewriting their own memory, skills, prompts, and even the harness itself (through mods). Letta Code can be used interactively, or to power always-on agents that work proactively. Interact with agents through: * A local [**CLI**](https://docs.letta.com/letta-code/cli) * Your browser, including [mobile](https://docs.letta.com/letta-code/remote-mobile), at [chat.letta.com](https://chat.letta.com) * Messaging integrations, including [Telegram](https://docs.letta.com/letta-code/channels#telegram-cli), [Slack](https://docs.letta.com/letta-code/channels#slack-cli), [Discord](https://docs.letta.com/letta-code/channels#discord-cli), and [custom channels](https://github.com/letta-ai/letta-code/blob/main/src/channels/README.md) ![](https://github.com/letta-ai/letta-code/blob/main/assets/letta-code-demo.gif) ## Feature Overview > [!TIP] > Letta Code agents are designed to be self-configuring. If you want to configure something (e.g. skills, behavior, hooks, permissions), try asking your agent to do it for you. | Feature | Description | |---|---| | [Self-improvement & Learning](https://docs.letta.com/letta-code/memory) | Agents programmatically rewrite their context to improve and adapt over time, including system prompt learning (through [memory blocks](https://www.letta.com/blog/memory-blocks)) and [skill learning](https://www.letta.com/blog/skill-learning). Configure periodic dreaming with `/sleeptime`, investigate agent behavior with `/doctor [symptom]`, and view memory with `/palace` | | [Message search](https://docs.letta.com/letta-code/slash-commands) | Search across all messages and agents with `/search`. Agent can also search their own conversations or the conversations of other agents | | [MemFS](https://docs.letta.com/letta-code/memfs) | All context (including memory blocks) is tracked via git. Sync context to a custom GitHub repository by setting `/memory-repository set git@github.com:...` | | [Skills](https://docs.letta.com/letta-code/skills) | Loads global skills (`~/.letta`), project-scoped skills (`.agents/skills`), and agent-scoped skills (stored in MemFS). View skills with `/skills` and create with `/skill-creator` | | [Subagents & Multi-agent](https://docs.letta.com/letta-code/subagents) | Call built-in subagents (general-purpose, forked, recall) in the background. Agents can call any other agent (including themselves) as subagents | | [Messaging Integrations](https://docs.letta.com/letta-code/channels) | Chat with the same agent from Slack, Telegram, your browser (chat.letta.com) including mobile, and through [custom channels](https://github.com/letta-ai/skills/blob/main/letta/creating-letta-code-channels/SKILL.md) | | [Hooks](https://docs.letta.com/letta-code/hooks) | Run custom scripts at key points of agent execution to automate workflows | | [Permissions](https://docs.letta.com/letta-code/permissions) | Set permission modes and customize what actions are auto-approved or auto-denied | | [Crons & Schedules](https://docs.letta.com/letta-code/scheduling) | Configure heartbeats and crons, and let agents work across time with self-managed schedules | | [Remote computers](https://docs.letta.com/platform/computers/byom) (requires signing in with Letta) | Agents work across multiple computers. Connect any machine by running `letta server --computer-name "..."` | | [Secrets](https://docs.letta.com/letta-code/secrets) (requires signing in with Letta) | Make secrets available as environment variables (across machines) while obfuscating their values from context | Automatic client-side dreaming is disabled by default on native Windows, including when saved `/sleeptime` settings enable it. Manual `/dream` and `/reflect` commands remain available. To opt in, set `LETTA_ENABLE_WINDOWS_AUTO_REFLECTION=1` in the environment of the Letta Code process. This does not affect macOS, Linux (including WSL), or server-side dreaming. See the full list of slash commands in our [documentation](https://docs.letta.com/letta-code/slash-commands). ## Get started Install the package via [npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm): ```bash npm install -g @letta-ai/letta-code ``` Alternatively, install with [uv](https://docs.astral.sh/uv/) or [pipx](https://pipx.pypa.io/) (Node.js is bundled): ```bash uv tool install letta # or pipx install letta ``` Requires Python 3.9+. Wheels support glibc Linux 2.28+ (x86-64/ARM64), macOS 14+ (Intel/Apple Silicon), and Windows x64; Alpine/musl, 32-bit systems, and Windows ARM64 are unsupported. If `npm install -g` fails with `EACCES`, don't use `sudo`: root ownership prevents the CLI's `npm install -g` self-updates. Use uv/pipx, a user-owned npm prefix, or nvm. See the [CLI installation docs](https://docs.letta.com/platform/cli). Navigate to your project directory and run `letta` (see command-line options [in the docs](https://docs.letta.com/letta-code/commands)). You can also run the tutorial agent with: ``` letta --new-agent --personality tutorial ``` Letta Cloud is the default. On first launch, choose to sign in with Letta or proceed locally; your choice is saved for future runs. Run `letta setup` to choose again, or `letta backend cloud` / `letta backend local` to change the default. Use `--backend cloud` or `--backend local` for a one-off override without changing the saved default. Run `/connect` to configure your own LLM API keys (OpenAI / ChatGPT, Anthropic, Z.ai coding plan, etc.), and use `/model` to swap models. ## Letta Cloud Letta Cloud stores agents' memory, identity, and conversations while Letta Code runs on a laptop, [GitHub Actions](https://github.com/letta-ai/letta-code-action), a Cloud sandbox, or a remote computer. Chat with them through [chat.letta.com](https://chat.letta.com/). On resume, bundled default system prompts (including older versions) become Cloud-managed. Custom prompts stay explicit. Set `LETTA_CODE_PRESERVE_CLOUD_SYSTEM_PROMPT=1` to disable automatic prompt updates on Cloud. ```mermaid graph TD LettaCloud["Letta Cloud<br/>Agent state"] LettaCloud --> A["💻 Your Laptop"] LettaCloud --> B["☁️ Cloud VM"] LettaCloud --> C["🖥️ Mac Mini"] LettaCloud --> D["📦 Managed Sandbox"] ``` Run `/login` from the CLI to access agents in your Letta account. ### Remote computers Agents stored in Letta Cloud can run across multiple machines. Connect any machine by running: ```bash letta server letta server --computer-name "work-laptop" ``` List discoverable computers from the CLI: ```bash letta computers list --online-only ``` Get the current computer connection for routing another agent onto this same machine: ```bash letta computers current ``` Route a headless message through a specific computer: ```bash letta -p --agent <agent-id> --computer "work-laptop" "hello from that machine" ``` Use `--computer cloud` to start or reuse the target agent's cloud sandbox. Agent-to-agent headless messages without `--computer` run on the same computer. See our guides for using [Railway](https://docs.letta.com/letta-code/remote#railway), [DigitalOcean](https://docs.letta.com/letta-code/remote#digitalocean), and [Fly.io](https://docs.letta.com/letta-code/remote#flyio) as remote computers. The previous `environments`/`envs`, `--environment`/`--env`, and `--env-name` spellings remain available for backwards compatibility. ## AgentFile deprecation AgentFile (`.af`) export and import are deprecated and have been removed from Letta Code. The `/export` and `/download` slash commands and the `--import` and `--from-af` CLI flags are no longer supported, including imports from the agent registry. This does not affect memory import/export or conversation transcript export. ## Installing external skills Install skills into a specific agent's memory with `letta skills install <skill>`: | Source | Example | |---|---| | GitHub | `letta skills install https://github.com/owner/repo`<br>`letta skills install https://github.com/owner/repo/tree/main/path/to/skill`<br>`letta skills install https://github.com/owner/repo/blob/main/path/to/skill/SKILL.md` | | [ClawHub](https://clawhub.ai/) | `openclaw skills install <skill-slug>` → `letta skills install <skill-slug>` | | [Hermes Skills Hub](https://hermes-agent.nousresearch.com/docs/skills/) | `hermes skills install <skill-path>` → `letta skills install <skill-path>` | To view skills run `letta skills list --agent <agent-id>`, and delete skills with `letta skills delete <skill-name> --agent <agent-id>`. ## Research Letta Code is developed by the creators of [MemGPT](https://arxiv.org/abs/2310.08560) and [sleep-time compute](https://arxiv.org/abs/2504.13171) (now called "dreaming"), and driven by our [research](https://www.letta.com/research) in AI memory and continual learning. ## Other Community maintained packages are available for Arch Linux users on the [AUR](https://aur.archlinux.org/packages/letta-code): ```bash yay -S letta-code # release yay -S letta-code-git # nightly ``` Nix users can run or install Letta Code through the repository flake: ```bash nix run github:letta-ai/letta-code nix profile install github:letta-ai/letta-code ``` See [docs/nix.md](docs/nix.md) for Home Manager and NixOS service examples. --- Made with 💜 in San Francisco <img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=76801c33-8e75-4055-8eea-2c8092519a90&page=README.md" alt="" aria-hidden="true" />

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Skills في هذا المستودع

المهن الحاسوبية الأخرى مطوّرو البرمجيات المصممون الجرافيكيون فنيو الصوت والفيديو

٦ فئات مهنية · 57% مصنفة

skill

المهنة

الوصف

آخر تحديث

working-across-computers

غير مصنف

Guides work across Cloud, local, and other available computers, including teleporting conversations, running remote subagents, and transferring files. Load when a request needs the user's laptop or another machine's files, apps, or tools; when connecting a…

لغة النص الأصلي: الإنجليزية

2026-10-13

creating-skills

المهن الحاسوبية الأخرى

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Letta Code's capabilities with specialized knowledge, workflows, or tool integrations.

لغة النص الأصلي: الإنجليزية

2026-10-12

managing-agent-webhooks

غير مصنف

Creates, lists, tests, enables, disables, rotates, inspects, and deletes inbound webhooks for the current Letta Cloud agent. Use when a user asks to set up a webhook, send external events to an agent, test webhook delivery, inspect recent webhook requests,…

لغة النص الأصلي: الإنجليزية

2026-10-12

workflow-authoring

غير مصنف

Reference for writing a Workflow tool script (script API and gotchas, pipeline-vs-barrier rules, quality patterns, worked examples). Load before authoring a script for a workflow the user already opted into; it does not itself authorize running one.

لغة النص الأصلي: الإنجليزية

2026-10-12

speech-generation

غير مصنف

Convert text to speech using ElevenLabs voice AI through Letta. Use when generating audio from text, sending a voice message, reading text aloud, creating voiceovers, speaking in your own voice, or synthesizing speech in 90+ languages.

لغة النص الأصلي: الإنجليزية

2026-10-12

submitting-feedback

غير مصنف

Submits user-approved product feedback and bug reports about Letta Code to the Letta team. Load when the user reports a Letta Code bug, requests a product or developer change, or explicitly asks to send feedback. Do not load for corrections to the current…

لغة النص الأصلي: الإنجليزية

2026-10-10

self-configuration

غير مصنف

Inspect or modify Letta Code's own memory, model, context window, system prompt, compaction, permissions, toolsets, mods, skills, channels, schedules, agent secrets, and local runtime settings. Use when the user asks how this agent or conversation is…

لغة النص الأصلي: الإنجليزية

2026-10-04

creating-mods

المهن الحاسوبية الأخرى

Creates and edits trusted local Letta Code mods, including tools, slash commands, local-only model providers, lifecycle/turn events, scoped conversation helpers, panels, and capability-gated behavior. Use when asked to make a mod, add an agent-callable tool,…

لغة النص الأصلي: الإنجليزية

2026-10-04

context-doctor

غير مصنف

Investigate and repair an agent's context — memory, system prompt, and skills — using observed behavior as evidence. Use when the user asks to audit, clean up, or fix your memory or context, or runs /doctor. Do not load for routine memory reads or edits, or…

لغة النص الأصلي: الإنجليزية

2026-09-30

initializing-memory

غير مصنف

Comprehensive guide for initializing or reorganizing agent memory. Load this skill when running /init, when the user asks you to set up your memory, or when you need guidance on creating effective memory files.

لغة النص الأصلي: الإنجليزية

2026-09-30

curating-memory-palace

غير مصنف

Rules for the Memory Palace (palace/), the view on your Memory page in the Letta dashboard that shows the user where things stand, what you could do next, and how to make you more useful. Load it before creating or editing anything in palace/, when a message…

لغة النص الأصلي: الإنجليزية

2026-09-30

scheduling-tasks

غير مصنف

Advanced scheduling through the letta cron CLI for other conversations, computers, run history, and schedule replacement. Use Wake for ordinary create/list/cancel operations in the current conversation.

لغة النص الأصلي: الإنجليزية

2026-09-25

messaging-agents

غير مصنف

Send a message to another Letta agent, continue a thread with one, check on it, or reply to a message another agent sent you. Use when you need to ask, inform, or coordinate with another agent, or when a message from another agent arrives.

لغة النص الأصلي: الإنجليزية

2026-09-24

syncing-memory-filesystem

غير مصنف

Diagnose and repair MemFS repository setup, remote sync, authentication failures, optional backup remotes, or merge/rebase conflicts. Do not load for routine memory reads or edits.

لغة النص الأصلي: الإنجليزية

2026-09-23

letta-guide

مطوّرو البرمجيات

Read the official Letta documentation (docs.letta.com) through its cached, ETag-checked fetch route. Load before ANY docs.letta.com retrieval — answering how Letta works, what Letta (or you) can do, and looking up Letta API, Agent SDK, or Letta Code reference.

لغة النص الأصلي: الإنجليزية

2026-09-17

finding-agents

المهن الحاسوبية الأخرى

Find other agents on the same server. Use when the user asks about other agents, wants to migrate memory from another agent, or needs to find an agent by name or tags.

لغة النص الأصلي: الإنجليزية

2026-09-16

image-generation

المصممون الجرافيكيون

Generate images from text prompts (and optionally edit/remix input images). Use when the user asks to create, generate, draw, render, or edit an image, illustration, logo, icon, diagram, or photo.

لغة النص الأصلي: الإنجليزية

2026-09-12

adding-models

مطوّرو البرمجيات

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…

لغة النص الأصلي: الإنجليزية

2026-09-04

browser-use

مطوّرو البرمجيات

Control a real browser to navigate pages, click, type, fill forms, inspect rendered UI, take screenshots, or record video. Load only when the user asks to open or automate a browser, interact with or test rendered page UI, scrape a site that needs browser…

لغة النص الأصلي: الإنجليزية

2026-09-03

using-mcp-tools

المهن الحاسوبية الأخرى

Reference for the `letta mcp` CLI, which finds and invokes MCP tools available to this agent. A system reminder already lists your connected MCP servers and the basic search/schema/call commands; invoke this skill when you need more — browsing a server's…

لغة النص الأصلي: الإنجليزية

2026-09-01

managing-shared-memory

مصممو قواعد البيانات

Create and manage shared memory — git-tracked repositories hosted on Letta Cloud that are attached to one or more agents and projected into their filesystems. Use when the user wants to share memory or files across agents, store context outside your own…

لغة النص الأصلي: الإنجليزية

2026-08-28

editing-letta-code-desktop-preferences

مطوّرو البرمجيات

Edits Letta Code Desktop (LCD) preferences by safely reading and updating ~/.letta/desktop_preferences.json. Use only when the user asks to change current Desktop/LCD settings such as theme, default working directory, remote access preference, or remote…

لغة النص الأصلي: الإنجليزية

2026-08-27

capturing-tui-visual-proof

فنيو الصوت والفيديو

Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI. Use when a Letta Code PR changes interactive CLI rendering or behavior and needs terminal screenshots or GIFs in its PR body.

لغة النص الأصلي: الإنجليزية

2026-08-26

customizing-commands

مطوّرو البرمجيات

Creates, edits, and enables Letta Code mod-provided slash commands. Use when the user asks to add a custom /command, slash command, command shortcut, scoped conversation-backed command, or command-driven panel behavior.

لغة النص الأصلي: الإنجليزية

2026-08-20

customizing-statusline

مطوّرو البرمجيات

Creates, edits, and migrates Letta Code statusline mods. Use when handling the /statusline command or continuing work started by /statusline.

لغة النص الأصلي: الإنجليزية

2026-07-03

generating-mod-envs

محللو ضمان جودة البرمجيات والمختبرون

Generates and reviews mod learning env JSON files for Letta Code local mods. Use when asked to teach, learn, or optimize a mod behavior; create, draft, validate, improve, or explain envs for `/mods learn --env`; or design evaluation scenarios, memory…

لغة النص الأصلي: الإنجليزية

2026-06-28

acquiring-skills

المهن الحاسوبية الأخرى

Discover and install skills from Hermes, ClawHub, GitHub, and other registries. Load this skill whenever a user asks for a capability you don't already have — image generation, social media, email, calendar, finance, DevOps, search, browser automation, etc.

لغة النص الأصلي: الإنجليزية

2026-06-05

migrating-memory

المهن الحاسوبية الأخرى

Migrate memory blocks from an existing agent to the current agent. Use when the user wants to copy or share memory from another agent, or during /init when setting up a new agent that should inherit memory from an existing one.

لغة النص الأصلي: الإنجليزية

2026-05-09

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