Audit the alert rules you inherited
Scores every alert in Datadog, Sentry, Cloudflare and Better Stack by how often it fires against how often it mattered.
I want to do this: Go through our alert rules: which ones fire the most, and which were ever real? ## Setup (skip if Polylane is already set up) Read and follow https://polylane.com/auth.md for non-interactive signup and setup. Start by checking whether I am already signed in; reuse my account and workspace. If the CLI is missing, bootstrap it without starting the interactive wizard: curl -fsSL 'https://polylane.com/setup?ref=prompts' | bash -s -- --install-only Then follow the guide through email verification, workspace selection, source connections, and MCP authentication. Ask me for an email code or OAuth consent only when needed. Verify each step; report pending setup instead of claiming success from installation alone. ## How to work Over MCP: searchTools lists what this workspace exposes, with each tool's schema; call it first. runTool runs one tool, runCode chains several in one call and returns just the answer. search and execute cover the full Polylane REST API: threads, issues, investigations, autofixes, memories. From the terminal: the polylane CLI wraps the same API, with structured output and non-interactive flags everywhere. Reads always work. Write tools appear only if I have opted in, and every write is screened. ## Task: Audit the alert rules you inherited Steps: 1. List the alert rules and monitors across connected providers 2. Pull each one's firing history for the window 3. Cross-reference firings against the issues that turned out real 4. Score each rule: signal rate, duplicate rate, last true positive 5. Deliver the audit with delete, tune, and keep recommendations Ground every claim in data you actually pulled: the query, the log line, the change record. If the data is inconclusive, say so. Ask me before anything that writes.
Every alert was somebody's good idea.
Rules accumulate: the 2023 migration, the incident that never recurred, the threshold set in a panic. Deleting one feels dangerous, so the noise compounds instead.
- Rules nobody remembers writing, firing weekly
- Real alerts buried under ceremonial ones
- "Just mute it" as alert management
One prompt, this much work. Every step on your real data.
- 1 List the alert rules and monitors across connected providers
- 2 Pull each one's firing history for the window
- 3 Cross-reference firings against the issues that turned out real
- 4 Score each rule: signal rate, duplicate rate, last true positive
- 5 Deliver the audit with delete, tune, and keep recommendations
Delete with confidence
Every rule scored against what actually happened, so pruning stops being guesswork. The pager gets quieter without getting blinder.
What broke overnight? 
“Triage everything that fired overnight: what was real, what was noise, and what's still open?” Root cause 
“P99 on checkout-api doubled at 14:10. Find the cause and show the evidence.” Postmortem “Write the postmortem for yesterday's incident: timeline, root cause, and the follow-ups.” First responder “We're seeing 500s on api.example.com. Start an investigation and post findings to #incidents.” What changed? 
“Did anything deploy or change config in the last two hours that could explain this latency?” War-room brief “Summarise the open incident for the exec channel: impact, cause so far, next steps.” Close the loop “The incident is resolved. Draft the permanent fix and link the evidence.” Which release? “Errors started around Tuesday. Which release introduced them?” Dedupe the pager “Group last month's pages into distinct issues. How many were the same thing twice?”
“Triage everything that fired overnight: what was real, what was noise, and what's still open?” Root cause 
“P99 on checkout-api doubled at 14:10. Find the cause and show the evidence.” Postmortem “Write the postmortem for yesterday's incident: timeline, root cause, and the follow-ups.” First responder “We're seeing 500s on api.example.com. Start an investigation and post findings to #incidents.” What changed? “Did anything deploy or change config in the last two hours that could explain this latency?” War-room brief “Summarise the open incident for the exec channel: impact, cause so far, next steps.” Close the loop “The incident is resolved. Draft the permanent fix and link the evidence.” Which release? “Errors started around Tuesday. Which release introduced them?” Dedupe the pager “Group last month's pages into distinct issues. How many were the same thing twice?”