How I Added Goose as an External Agent to Entire

I just opened a that allows you self-serve add support for any agent you prefer to Entire. It gives you a completely self-serve way to add support for any agent you prefer. The user experience is identical to using a built-in agent. All the exact same commands and functionality just work. If Entire doesn't support your favorite agent yet, you don't have to wait on us. You can build the integration yourself directly in the , so now I could fulfill my dream.

What your agent needs

To wire your agent up to Entire, it needs to have the following:

1. 
   A hooks or lifecycle mechanism: You need a reliable way to run an external command when a session starts, a prompt is submitted, or a turn ends. Without this, Entire cannot observe the session.
   


2. 
   Readable session data: You need access to transcripts or an exportable session store containing the actual conversation. We need real assistant responses and precise tool calls, not generic placeholder text like "Working...".
   


3. 
   Stable session identity: A consistent session ID that you can extract from hook payloads, ideally paired with a resume command (like goose session --resume --session-id <id>).
   


4. 
   A non-interactive CLI mode: Running commands cleanly (for example, goose run -t "prompt") makes writing automated lifecycle tests dramatically easier.

What you need

You also need the following items on your device:

1. Your target agent’s CLI install and authenticated
   


2. Entire CLI installed
   


3. Go toolchain because external agents for Entire are written in Go.
   


4. Open an issue first to get alignment with the team at Entire requesting that you want to add this agent. Introducing a new agent means a long-term support commitment for us!
   


5. 
   Optional: An agent that you would use to implement this integration. I used Claude Code with Fable 5. This way, I didn’t have to manually write all the code. Claude Code just followed the pattern to integrate Goose with Entire.

The step-by-step workflow

1. Run the Agent skill

The . Clone the repository, open it up in your favorite AI development tool, and run:

/entire-external-agent

2. The three development phases

Phase 1: Research - The skill analyzes the protocol spec, probes your agent's binary commands, and, crucially, writes a verification script to capture real hook payloads.

For Goose, this script wired a capture plugin into a temporary workspace, executed a real goose run prompt, and dumped the exact stdin payloads to disk. Documentation can lie, but captured payloads never do. This phase also ensures the session data is clean and stores everything in an AGENT.md summary file.

This phase revealed that Goose sessions live in a global SQLite database rather than isolated files, meaning our binary had to materialize transcripts on the fly using goose session export --format json.

Phase 2: Write tests - The skill scaffolds a fresh Go binary that stubs out the required protocol subcommands with valid JSON shapes. It registers your agent in our end-to-end testing harness. At this point, the shared compliance suite (.

Resources

There’s some more resources from us about agent hooks and adding external agents:

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• this July 2026. See you soon!
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