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The Slack coder example is a small deployed agent that receives coding tasks in Slack. Mention it with a task; it clones the repository on its OpenComputer computer, changes code on a branch, runs the relevant checks, opens a draft pull request and replies with the result. Mention it again in the same thread to continue on the same branch and pull request. It keeps working after you close your terminal. The repository is two files:
OpenComputer supplies the rest: the coding harness and computer, deployed execution, conversation routing, GitHub credentials and the Slack app. There is no server, message parser, GitHub client or Slack reply code to write. Browse the source on GitHub.

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What the agent does

opencomputer/agents/coder/agent.ts declares a GitHub connection with write access to contents and pull requests, selects a model, enables the built-in shell tool and returns the instructions the agent works from: read the repository’s instructions, inspect the code, work on a branch, run the checks and report their actual results, push the branch and open a draft pull request, continue follow-ups on that branch, never merge, and never print credentials or put them in files or Git URLs. The example declares no Slack channel, so the agent gets a dedicated Slack app with the standard configuration: mentions and direct messages go to this one agent. To narrow or extend what the app can do, declare a channel under opencomputer/channels/ as described in Channels.

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Deploy it

You need Node.js 22 or later, an OpenComputer account with available usage, permission to install a Slack app in your workspace, and GitHub access to install the managed OpenComputer App on the repositories the agent may change.
The deploy command exits after publishing; nothing keeps running on your machine. Open the printed project URL and select Production.

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Connect GitHub

In Connections, install the managed OpenComputer GitHub App, select the repositories the agent may change, and attach the installation to Production. That selection is the complete boundary of what the agent can reach. Anyone who can message the bot can direct it at those repositories, so invite the bot to conversations accordingly. See GitHub App connections.

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Connect Slack

In the same Connections tab, the Slack panel shows the agent that will receive messages. Choose Create Slack bot, name it, paste an app configuration access token from your Slack apps, and approve the installation in Slack. You are returned to the same project and environment. Invite the bot to a channel and mention it once; the panel reports the first message received. Connect Slack covers the token and the manual alternative.

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Give it a task

Mention the bot by the name you gave it, in a channel it has been invited to, naming a repository the installation can reach. The examples call it Patch:
@Patch In acme/service, CSV export breaks when a customer’s name contains a comma. Reproduce it, fix it, run the tests and open a draft PR.
The reply reports what was run, the check results and the draft pull request link. Follow up in the same thread, from the same Slack account:
@Patch Also cover names containing newlines in that PR.
The same session continues on the same branch and updates the same pull request. A new thread starts independent work. Each conversation belongs to the Slack user and thread it started in.

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Change the agent

Edit the instructions or the model in agent.ts and run the deploy command again. New conversations use the promoted version; conversations already running keep the version they started with. Redeploying does not require reconnecting GitHub or Slack.