check-integrity

To audit a SQLite database for schema integrity and semantic staleness, you can run automated checks that validate mechanical schema formats and cross-tier consistency. This detects data corruption and identifies grades invalidated by recent profile updates.

Semantic grade staleness occurs when career profile changes, such as new projects or shifted preferences, invalidate existing job fit assessments. Detecting this staleness requires cross-referencing the current profile against stored grade evaluations to ensure accuracy.

You identify missing data and portfolio gaps by performing systematic sampling of job evaluations during a database audit. This process analyzes market patterns and updates career-coaching documentation to maintain accurate profile-driven assessments.

Yes, checking database integrity requires full access to the profile directory and reference guides. This access ensures the audit can validate cross-tier consistency and confirm that all grade assessments remain contextually accurate.

Yes, you can run automated schema checks and formatting on a SQLite database to prevent data corruption and token waste. These mechanical integrity checks ensure the database structure remains valid and optimized.

Database drift is the silent separation between your evolving career profile and your job search database. You resolve it by running an integrity audit that detects semantic staleness and updates relevance statements to match your current profile.