music_library/backlog/tasks/ml-163 - Create-pi-tools-to-fetch-production-errors.md

id, title, status, assignee, created_date, updated_date, labels, dependencies, parent_task_id, priority, ordinal

id	title	status	assignee	created_date	updated_date	labels	dependencies	parent_task_id	priority	ordinal
ML-163	Create pi tools to fetch production errors	To Do		2026-05-04 08:08	2026-05-04 08:18	pi		DRAFT-1	medium	5000

Description

Create fetch_production_errors and fetch_production_error pi tools that call the /api/v1/errors JSON API endpoint.

These tools are registered via pi.registerTool() in a pi extension. They make authenticated HTTP requests to the production server using the same HURL variable pattern established by fetch_production_logs (ML-160).

Tools

fetch_production_errors — List/filter production errors

• Parameters: status (optional: "resolved" | "unresolved"), muted (optional: boolean), search (optional: string, substring match on reason), limit (optional: number, default 50), offset (optional: number, default 0)
• Calls GET /api/v1/errors with query params
• Returns: formatted list of errors with counts and timestamps
• Truncates output with truncateTail (50KB / 2000 lines)

fetch_production_error — Get a single error with full details

• Parameters: id (required: UUID string)
• Calls GET /api/v1/errors/:id
• Returns: error details with all occurrences, stacktraces, and context
• Truncates output with truncateTail

Tool guidelines (promptGuidelines)

• Use fetch_production_errors when investigating what errors are occurring in production
• Use fetch_production_error when you need full details on a specific error, including stacktraces and context
• Start with a small limit (e.g., 20) and filter by status or search before fetching large result sets

Auth

Uses the same HURL variable pattern as fetch_production_logs:

• PI_API_TOKEN — Bearer token for API auth
• PI_SERVICE_FQDN_WEB — Production domain

They need to be configured in the pi environment as local secrets.