AI auto-fix

Auto-fix reads the stack trace, pulls the relevant source out of your repository, asks an AI provider for a patch, and opens a merge request with it. You review it like any other MR.

What you need first

1. A source-control integration connected and a repository linked to the project — see Integrations. Without it there is no source to read and nowhere to open an MR.
2. An AI configuration for the organization (or for one project).

Configure a provider

Settings → AI, or over the API:

curl -X POST "$ERRORA/api/v1/organizations/$ORG_ID/ai-configs" \
  -H "Authorization: Bearer $ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
        "name": "Default fixer",
        "provider": "claude",
        "model": "claude-opus-4-8",
        "api_key": "sk-…",
        "base_url": "",
        "project": null,
        "auto_trigger": false,
        "enabled": true
      }'

Field	Notes
provider	openai (any OpenAI-compatible endpoint), claude (Claude Agent SDK), cursor (Cursor Agents SDK)
model	Provider-specific model id
api_key	Stored encrypted; the API never returns it in full
base_url	For OpenAI-compatible gateways and custom endpoints
project	null = applies to the whole organization; set it to scope a config to one project
auto_trigger	Start a run automatically when a new issue is created
enabled	Turn a config off without deleting it

A project-scoped config wins over the organization-wide one.

Trigger a run

From the issue page, press AI auto-fix. Or:

curl -X POST "$ERRORA/api/v1/projects/$PROJECT_ID/issues/$ISSUE_ID/autofix" \
  -H "Authorization: Bearer $ACCESS_TOKEN"

Triggering requires the ai:trigger capability (owner, admin, member by default).

What happens

1. Errora gathers context: the exception, the stack frames, and the source files those frames point at, fetched from the linked repository.
2. The provider is asked for a patch plus an explanation.
3. Errora creates a branch (errora/autofix-<issue>-<timestamp>), commits the diff and opens a merge request.
4. The run is recorded with its status, diff, explanation, MR URL, model and token usage.

A run takes as long as the model does, and your events keep flowing meanwhile. Follow progress live on the issue page, or in AI fixes, which lists every run in the organization.

Each stage fires an alert event you can route to a channel: autofix.started, autofix.mr_created, autofix.failed — see Alerts.

Cost

Each run is metered as the AI Fix service (20,000 Toman per run by default) on top of whatever your AI provider charges. See Wallet.

Reviewing the patch

Treat it as a draft from a colleague who has read the stack trace and nothing else:

• It sees the frames and the files they point at — not your tests, your product decisions or the ticket.
• Run the tests. Read the diff. The MR is a starting point, not an authority.

Troubleshooting

Symptom	Cause / fix
Button disabled / 403	Your role lacks ai:trigger
"No repository linked"	Link a repo to the project in Integrations
Run fails immediately	Wrong API key or model id, or a base_url Errora cannot reach
MR not created	The integration token lacks write scope on the repository
Patch looks unrelated	The stack frames pointed at vendor code — link the right repo, and make sure source maps/releases resolve frames to your own files