What problem does it solve?
Manually monitoring Slack tech error alerts, cross-referencing Datadog metrics, logs, and GitHub deploy history, and deciding when to open fix PRs is slow, inconsistent, and distracts engineering teams from core work. This skill automates the entire end-to-end workflow for Pear tech error alerts.
Core Features & Use Cases
- Automated Alert Monitoring: Watches the #tech_errors and #tech_errors_high_priority Slack channels for active Datadog alerts, escalates unhandled alerts to deep analysis, and avoids duplicate work by checking existing triage and PR threads.
- Evidence-Based Fix Gating: Only proposes code or operational fixes when there is very high confidence a specific change caused the alert, using Datadog context, log samples, and GitHub deploy history as evidence, and routes all approval requests through a standardized Slack YES/NO workflow.
- End-to-End PR Automation: On approval, creates a scoped fix PR from a dedicated worktree, enables auto-merge, and sets up a watcher to handle review comments and CI failures until the PR is merged, posting concise status updates back to the original Slack alert thread.
- Self-Healing Automation: Includes a daily repair cron that ensures the core watcher automation is always active, recovering from accidental pauses or deletions without manual intervention.
Quick Start
Invoke the tech-errors-watcher skill to start, restart, or repair the automated Slack watcher for Pear tech error alert channels.