letta-ai

Set up and run LettaBot - a multi-channel AI assistant for Telegram, Slack, Discord, WhatsApp, and Signal. Supports both interactive wizard and non-interactive (agent-friendly) configuration.

Reply with voice memos using text-to-speech. Use when the user sends a voice message, asks for an audio reply, or when a voice response would be more natural.

Post, reply, like, and repost on Bluesky using the lettabot-bluesky CLI. Read-only by default; explicit actions required.

Create and manage scheduled tasks (cron jobs) that send you messages at specified times.

Manage Linear issues via GraphQL API. List, filter, update, prioritize, comment, and search issues. Use when the user asks about Linear, issues, project management, or backlog.

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.

Manage Apple Notes via the `memo` CLI on macOS (create, view, edit, delete, search, move, and export notes). Use when a user asks Clawdbot to add a note, list notes, search notes, or manage note folders.

Manage Apple Reminders via the `remindctl` CLI on macOS (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output.

Test any GUI app or change on a Daytona Linux (Ubuntu xfce4 + noVNC) remote desktop sandbox. Use to launch a GUI program, sync a local project, take a screenshot, record a video, or share a clickable live-desktop link with a teammate. Generic — the only dependency is Daytona. For Windows, use remote-desktop-testing-windows.

Test any GUI app or change on a Daytona Windows remote desktop sandbox. Use to launch a GUI program, sync a local project, take a screenshot, record a video, or share a clickable live-desktop link with a teammate. Generic — the only dependency is Daytona. For Linux, use remote-desktop-testing-linux.

Configures Letta agents' own runtime behavior, including model, context window, system prompt, reasoning, conversation overrides, compaction settings, and compaction prompts. Use when an agent or user asks to self-modify, tune summarization/compaction, change identity/system instructions, adjust model settings, or test conversation-scoped overrides.

Sets Letta Desktop and Letta Code agent profile images by writing profile.png into an agent MemFS repository. Use when the user asks to add, change, generate, or fix an agent avatar, profile picture, profile image, or Desktop agent photo.

Navigates archived ChatGPT or Claude-style conversation exports and a MemFS reference archive on demand. Use when recalling what a past assistant knew, searching old conversations, rendering specific chats, seeding reference memory from export sidecars, or mining historical context without doing a full import.

Migrates deprecated Letta Filesystem folders/files to MemFS using markdown document corpora, chunking, local lexical search, and QMD semantic search via the memfs-search skill. Use when replacing folders.files.upload, working with PDFs or document QA, or emulating open_file, grep_file, and search_file behavior.

Semantic search over agent memory files. Use when you need to find conceptually related memory blocks, discover forgotten reference files, check what you already know before creating new memory, or search beyond exact keyword matching. Currently supports QMD (local, no API keys).

Builds and debugs Letta Code channels, including first-party channel adapters and dynamic user channel plugins under ~/.letta/channels. Use when adding Telegram, WhatsApp, Bluesky, Slack, Discord, or custom channel support; testing channel routing, pairing, MessageChannel, runtime dependencies, or channel plugin manifests.

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, add a slash command, add a local provider/model adapter, transform turns, react to app events, or add lightweight mod UI outside the dedicated /statusline flow.

Modify Letta Code's own memory, model, context window, system prompt, compaction, permissions, toolsets, mods, skills, channels, schedules, and local runtime settings. Use when the user asks you to change how you behave or how the harness runs you.

Answer questions about Letta itself from the official documentation. Use whenever the user asks how Letta works, what Letta (or you) can do, or how to set up or configure providers, models, channels, skills, memory, schedules, permissions, self-hosting, pricing, or billing — any "how do I…" or "can Letta…" question about the Letta product. Fetch the docs before answering; never answer Letta product questions from memory alone.

Schedules reminders and recurring tasks via the letta cron CLI. Use when the user asks to be reminded of something, wants periodic messages, or needs to manage scheduled tasks.

Connect to MCP (Model Context Protocol) servers and create skills for repeated use. Load when a user wants to use an MCP server, connect to external tools via MCP, or when they mention MCP, model context protocol, or specific MCP servers.

Send messages to other agents on your server. Use when you need to communicate with, query, or delegate tasks to another agent.

Identify and repair degradation in system prompt, external memory, and skills preventing you from following instructions or remembering information as well as you should.

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.

Social conduct and norms for AI agents operating on Bluesky and X through social-cli. Hard rules, platform-specific norms, and engagement principles. Load this before any posting, replying, following, liking, or DM behavior — especially from a new account or on a new network.

Create public source-tracking collections on Semble after posting threads. Creates a Semble collection linking the thread post and all cited sources with notes on what claims they support. Use after posting any thread with cited sources, or when the user asks to track sources on-protocol.

Publish long-form markdown content to GreenGale (ATProtocol-native blogging). Use when asked to publish a blog post, write an article, or post long-form content.

Skill for GitHub Actions CI environment. Use when running inside a GitHub Actions workflow to update tracking comments, commit code, and interact with GitHub.

Skill for handling PR code reviews. Use when triggered by a PR review comment, review request, or when asked to review code changes. Provides workflow for reading review comments, understanding feedback, and iterating on changes.

Manage Linear issues via GraphQL API. List, filter, update, prioritize, comment, and search issues. Use when the user asks about Linear, issues, project management, or backlog.

Verify factual claims before adding them to agent memory blocks. Use this skill when proposing FAQ entries, documentation updates, or any factual statements about Letta features, APIs, or behavior. Prevents confident-but-wrong assertions.

Contributes an agent to the letta-ai/agent-file directory. Use when setting up a new agent (.af file) for publication, including directory creation, avatar processing, file placement, and structure verification. Triggers on requests to release, publish, or contribute an agent file.

Creates and updates the public ezra-memory repository from Ezra's live MemFS using a strict allowlist, synthetic examples, privacy scans, fresh-history safeguards, and approval-gated publishing. Use when asked to sanitize, redact, review, package, or publish an Ezra memory snapshot.