kastalien-factory

Guide for safely discovering and installing skills from external repositories. Use when a user asks for something where a specialized skill likely exists (browser testing, PDF processing, document generation, etc.) and you want to bootstrap your understanding rather than starting from scratch.

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.

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.

Decomposes and reorganizes agent memory blocks into focused, single-purpose components. Use when memory has large multi-topic blocks, redundancy, or poor organization.

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.

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

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.

Search past messages to recall context. Use when you need to remember previous discussions, find specific topics mentioned before, pull up context from earlier in the conversation history, or find which agent discussed a topic.

Manage git-backed memory repos. Load this skill when working with git-backed agent memory, setting up remote memory repos, resolving sync conflicts, or managing memory via git workflows.

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.

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

Dispatch a development task to a headless letta-code agent. The task runs in the background and results are posted back to the originating channel when complete.

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.

Capture significant learnings from the current work session. Structures insights for future sessions and updates agent memory.

Extract reusable principles and decision frameworks from accumulated experience. Use after significant work sessions, project milestones, or when you notice recurring patterns worth codifying.

Format a structured escalation to the human decision-maker (Chief Agentic). Use when hitting an escalation threshold.

Orchestrate a multi-agent collaboration demo on the Thoughtbox Hub. Spawns COORDINATOR, ARCHITECT, and DEBUGGER agents that coordinate through shared workspaces, problems, proposals, and channels.

Implement a specification using a TDD-oriented workflow. Extracts requirements, generates tests first, then implements to pass the tests. Includes spiral detection and acceptance gates.

Execute a research task using compositional workflow planning. Characterizes the task, selects an approach from a library of research strategies, executes it, and self-evaluates output quality.

Generate a status report across all workstreams using beads issue tracking. Shows active work, blockers, and available tasks.

Fuse insights from multiple knowledge sources (code, docs, memory, research, web) into coherent understanding. Use when you have scattered information that needs integration.

Run a taste evaluation on a research proposal or technical direction. Determines whether to proceed, simplify, defer, or kill before committing research effort.