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Alertas de anomalias en scoring #45

@Kalebtron1

Description

@Kalebtron1

Why this matters

Detecting abnormal scoring behavior early helps prevent user-facing issues.

Problem

There is no alerting or thresholding for unusual score or rejection patterns.

Scope

  • Add a minimal anomaly signal or threshold check.
  • Document the expected normal range and what triggers an alert.
  • Keep the alert logic lightweight enough for the current stack.

Implementation guidance

  • Use api/calculate-score.js, api/evaluate-and-mint.js, src/components/CreditSection.tsx, and src/context/AppContext.tsx as the key touch points.
  • Keep the signal simple and easy to reason about.
  • Document how the threshold should be reviewed in future PRs.

Out of scope

  • A full production alerting platform.
  • Complex anomaly detection models that are hard to review.

Acceptance criteria

  • PR includes the alert or threshold logic and the validation path.
  • Reviewer can reproduce the trigger condition or understand how to simulate it.
  • The PR description explains what operational signal will be monitored.

Validation

  • Run the affected flow locally and observe the threshold path.
  • Run npm run build to confirm the change does not break the app.
  • Document how a reviewer can simulate the anomaly.

PR requirements

  • Include Closes #45.
  • State what normal behavior looks like.
  • Explain which signal should be watched after deploy.

Complexity

  • Medium (100 points)

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    Stellar WaveIssues in the Stellar wave programbackendBackend API and server workcomplexity:medium150 points - standard feature touching multiple areasobservabilityLogs, traces and monitoring

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