Repair Date And Time Bugs

The problem

Temporal bugs are notoriously difficult to track, often surfacing only during daylight-saving transitions, at the end of a month, or when users access the app from a different time zone. Hardcoding offsets or treating date-only values as UTC timestamps leads to shifting deadlines, incorrect booking times, and corrupted reports.

What it does

• Analyzes the flow of temporal data from input through storage to output to identify incorrect assumptions.
• Classifies values into instants, zoned date-times, local date-times, date-only values, or durations to apply the correct logic.
• Repairs UTC and local-time confusion without using brittle hardcoded hour offsets.
• Standardizes API serialization and database storage formats to prevent environment-specific drift.
• Implements boundary-focused tests for leap days, DST transitions, and midnight rollovers.

Frameworks & tools

Works across all stacks including Node.js, Python, Ruby, Go, and Java. Supports SQL and NoSQL databases, ORMs, and date-libraries like Luxon, Day.js, or date-fns.

Why this beats prompting it yourself

Generic prompts often suggest "just use UTC" without considering the business intent for local schedules or date-only values like birthdays. This skill enforces a strict temporal contract, ensuring that fixes for one time zone do not break the app for users in another.

Use cases

• Fixing appointments that shift by an hour after a daylight-saving change.
• Preventing "expired" flags from triggering too early for users in Western time zones.
• Standardizing mixed timestamp formats in legacy databases.
• Ensuring daily reports aggregate data based on the business time zone rather than server local time.

Known limitations

Cannot reliably fix historical data where the original time zone or intent was never recorded. Requires manual verification for irreversible production data migrations.