Release 0.191.3: Monitoring Precision Enhancement

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Release Notes
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Introduction

Version 0.191.3 delivers a focused enhancement to our monitoring infrastructure, addressing a subtle but important issue where test data was polluting production monitoring alerts. This release demonstrates the importance of maintaining strict boundaries between test environments and production monitoring systems, ensuring that automated alerts remain accurate and actionable.

Key Features

Enhanced Monitoring Data Isolation

  • Mock Room Filtering: Controller health monitoring now explicitly excludes the mock room E54N39 used in test snapshots and screeps-server-mockup integration tests
  • Production Alert Accuracy: Prevents false positive controller downgrade warnings triggered by test data appearing in production monitoring snapshots
  • Explicit Test Boundaries: Introduces a dedicated MOCK_ROOM_NAME constant to establish clear separation between test fixtures and production data

Technical Details

Problem Analysis

The Screeps GPT monitoring system operates on a scheduled basis, collecting bot snapshots every 30 minutes to analyze room health, controller progression, and potential issues. These snapshots are processed by check-controller-health.ts, which scans for controller downgrade risks and generates alerts when timers fall below critical thresholds.

However, our test infrastructure uses screeps-server-mockup to validate monitoring logic with synthetic game data. These test snapshots include a fixture room E54N39 that mimics production room structures but contains artificial data. When test snapshots were accidentally committed or persisted in the monitoring artifacts directory, the health check script would process this mock room alongside genuine production rooms, triggering spurious alerts about controller downgrade risks in a room that doesn’t exist in production.

Implementation Approach

The fix implements a surgical filter at the room processing level in packages/utilities/scripts/check-controller-health.ts:

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/**
 * Mock room name used in test snapshots and screeps-server-mockup.
 * This room should be excluded from production monitoring notifications.
 */
const MOCK_ROOM_NAME = "E54N39";

// During room health analysis loop:
// Skip mock room used in test snapshots (screeps-server-mockup)
// This prevents test data from appearing in production notifications
if (roomName === MOCK_ROOM_NAME) {
  continue;
}

Why This Approach?

  1. Minimal Invasiveness: The filter operates at the room-level iteration, catching mock data before any analysis occurs
  2. Explicit Intent: The dedicated constant and comprehensive comments make the filtering behavior self-documenting
  3. Test Coverage: The constant is exported and validated in unit tests, ensuring the filter remains effective
  4. Future-Proof: If additional mock rooms are needed, the pattern is easily extensible to an array of room names

Alternative Approaches Considered:

  • Snapshot-level filtering: We could have prevented mock rooms from appearing in snapshots entirely, but this would complicate test setup and reduce test coverage of the snapshot collection logic itself
  • Alert-level suppression: Filtering at the notification stage would still waste CPU cycles analyzing mock data
  • Dynamic detection: Runtime heuristics to identify test data would be fragile and error-prone

The chosen approach strikes the optimal balance: test code continues to exercise the full monitoring pipeline with realistic fixtures, while production monitoring ignores known test artifacts with zero computational overhead.

Test Coverage Enhancement

The fix includes comprehensive test updates to validate the filtering behavior:

  • Renamed test fixtures: Changed test room from E54N39 to W1N1 to ensure tests now use a non-filtered room name
  • Exported constant validation: Unit tests import and validate the MOCK_ROOM_NAME constant
  • Coverage expansion: Tests now verify that mock rooms are properly excluded from health analysis results

These changes ensure that future refactoring won’t accidentally reintroduce test data pollution, and that the filtering logic remains robust as the monitoring system evolves.

Bug Fixes

Controller Downgrade Monitoring False Positives

Issue: Mock room E54N39 from test snapshots appeared in production monitoring alerts, causing false positive controller downgrade warnings.

Root Cause: The controller health check script processed all rooms in bot snapshots without distinguishing between production rooms and test fixtures used by screeps-server-mockup.

Resolution: Implemented explicit filtering in analyzeControllerHealth() to skip room E54N39, preventing test data from triggering production alerts. The filter is applied early in the room processing loop, with clear documentation and exported constant for test validation.

Files Modified:

  • packages/utilities/scripts/check-controller-health.ts: Added MOCK_ROOM_NAME constant and filtering logic
  • tests/unit/controller-health-check.test.ts: Updated test fixtures to use non-filtered room names and validate constant export

Pull Request: #1558

Impact

For Monitoring Reliability

This fix directly improves the signal-to-noise ratio of our autonomous monitoring system. By eliminating false positives from test data, monitoring agents can focus on genuine production issues:

  • Reduced Alert Fatigue: Operators no longer need to manually filter out mock room warnings
  • Improved Agent Accuracy: Strategic planning agents receive cleaner data for trend analysis
  • Faster Incident Response: When controller downgrade alerts fire, operators can trust they reflect real production risks

For Development Workflow

The clear separation between test fixtures and production data strengthens our testing infrastructure:

  • Test Isolation: Test snapshots can safely include mock rooms without polluting production monitoring
  • Reproducible Testing: The same test fixtures work reliably across different environments
  • Documentation Value: The explicit MOCK_ROOM_NAME constant serves as executable documentation of test boundaries

For Bot Operations

While this is a monitoring-only change with no impact on bot AI logic, the improved monitoring accuracy indirectly supports better operational decision-making. Accurate controller health alerts enable faster response to genuine downgrade risks, which is critical for maintaining room control level (RCL) progression in competitive Screeps gameplay.

What’s Next

This release is part of our ongoing commitment to monitoring system excellence. Future enhancements planned for the monitoring infrastructure include:

  • Multi-Shard Telemetry: Enhanced snapshot collection across multiple Screeps shards (tracked in #1503)
  • Historical Trend Analysis: 7-day and 30-day performance trend tracking with regression detection (completed in #1549)
  • Strategic Planning Integration: Autonomous agents using monitoring data for optimization recommendations

The foundation established in this release—clear test boundaries and robust filtering—will support these advanced features by ensuring data quality remains high as monitoring capabilities expand.

Release Statistics:

  • Files Changed: 2
  • Lines Added: 65
  • Lines Removed: 8
  • Test Coverage: Comprehensive unit tests validating filtering behavior
  • Deployment: Automatic deployment via CI/CD pipeline to Screeps MMO

Contributors: This release was developed through collaboration between the Copilot SWE Agent and repository maintainer @ralphschuler, demonstrating the autonomous development capabilities of the Screeps GPT agent swarm.