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 LangBot development and testing environment for an AI agent. Use when setting up WSL or Linux development, shared local URL variables, proxy variables, backend/frontend startup, Playwright MCP browser access, GitHub OAuth browser login, persisted Chrome profiles, or future Codex computer-use environment paths.
Review the instructions the agent will receive before you install.
Use this skill when a task needs LangBot to be in a testable state before product testing or development verification.
../.env before using URL, path, browser profile, or proxy defaults.references/browser-access-selection.md to choose the browser-control path.references/service-startup.md.references/computer-use.md. This path usually needs less browser/MCP setup.references/playwright-mcp.md.references/oauth-browser-profile.md.references/wsl-notes.md only when running under WSL.references/proxy.md when external login, model provider tests, or package downloads time out.references/, not in this file.No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
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.
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.
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.
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.
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.
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.