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If you are building a coding agent, Autter gives you a standard way to record AI authorship without inventing a separate tracking system. The integration goal is simple:
  1. Capture an edit checkpoint before the agent changes files.
  2. Capture the agent’s edit after it writes files.
  3. Feed that data to autter checkpoint with a stable preset name.
  4. Let Autter write the authorship log on commit.

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What an integration needs

Build the hook payload in code. Do not assume utilities like jq or node are installed on the user’s machine.
If your agent supports before-edit and after-edit hooks, wire Autter into those hooks first.
1

Choose a preset name

Pick a name that matches the agent or workflow, such as cursor, claude, codex, github-copilot, or windsurf.
2

Emit the hook input

Serialize the edit event, workspace root, file list, and session identifiers in the format your integration already owns.
3

Call Autter

Run autter checkpoint <preset> --hook-input stdin from the hook or integration layer.
4

Test the full flow

Confirm that autter status shows the expected authorship and that autter stats counts the change correctly after commit.

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How to test

Test the same integration in the shells and operating systems you plan to support. Check these cases:
  • A single file edit
  • A multi-file edit
  • A human edit followed by an agent edit
  • A commit that lands on a branch, rebase, or cherry-pick path
Then verify:

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What to document for users

When you ship support for a new agent, tell users:
  • whether they need autter install-hooks
  • whether they should restart the editor or agent after install
  • which shell and OS combinations you tested
  • how to remove the integration with autter uninstall-hooks
Do not require users to hand-edit hook files unless there is no other path. The CLI should own the installation experience whenever possible.

CLI command reference

See the checkpoint command and related CLI flags.

Troubleshooting

Help users recover if attribution does not appear.