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Develop and migrate LangBot messaging adapters for Event-Based Agents, its event-driven architecture. Check conversion into shared event and message formats, implement platform APIs, and verify behavior through unit tests and real platform interactions.

• Adding a messaging platform adapter to LangBot
• Migrating an existing adapter to the EBA layout
• Testing event and message conversion in both directions

Build and debug LangBot plugins that handle messages, commands, and AI tool calls. The skill covers SDK usage, common errors, test environment setup, WebSocket message testing, and preparation for publishing to LangBot Space.

• Create a plugin that reacts to incoming messages
• Fix plugin SDK errors and missing responses
• Test group and private chats through WebSocket

Maintain LangBot skill assets by organizing operating rules, reference guides, test cases, fixtures, and troubleshooting entries. Check existing material before adding files, keep detailed instructions in one place, and verify that indexes stay current.

• Add a skill without duplicating existing guidance
• Organize reference guides and test cases
• Consolidate troubleshooting for shared causes

Deploy and configure LangBot with Docker Compose or Kubernetes. Set up application settings, plugin execution, the Box sandbox for isolated commands, and API authentication, with guidance on hosting choices and common deployment problems.

• Deploy LangBot on a self-hosted server
• Configure Box and the plugin runtime
• Enable API authentication for agent access

Search LangBot Space for plugins, MCP servers, and skills through MCP, a protocol for connecting agents to tools. Inspect item details, check plugin usage compatibility, and review model availability to support setup decisions.

• Find LangBot plugins for agent workflows
• Browse MCP servers and skills
• Check model availability during setup

Test LangBot through its WebUI and compare visible results with backend logs or network behavior. Use it to verify chat, model settings, bots, knowledge bases, and plugins, with recorded evidence for test results.

• Verify pipeline replies in Debug Chat
• Check model provider setup and test buttons
• Test bot, knowledge base, and plugin UI flows

Develop and debug LangBot's backend and web frontend. The skill guides environment setup, API additions, authentication, database migrations, and testing, including updates to matching MCP tools so agents can use changed API features.

• Set up the LangBot backend and frontend for development
• Add an API endpoint and its matching MCP tool
• Update the database schema with Alembic

Prepare a local LangBot environment for development and browser testing. The skill covers service startup, shared connection settings, browser access, proxy troubleshooting, and reusable login profiles, with guidance for Linux and WSL environments.

• Prepare a local Linux or WSL development environment
• Start services and verify WebUI access
• Choose Computer Use or Playwright MCP for browser control

Manage LangBot bots and processing workflows through MCP, a standard for connecting agents to tools. Configure authenticated access, inspect resources, update supported settings, and investigate execution histories, logs, and model request diagnostics.

• Connect an MCP client to LangBot
• Create or update bots and processing workflows
• Investigate execution logs and errors