Douyin Account Diagnosis Master

Problem

When evaluating whether a Douyin account is suitable for partnership, whether content quality is stable, or how a competitor is performing, relying on profile browsing can be misleading. Follower count, peak likes, and a few viral posts can obscure weak engagement, inconsistent posting, or poor follower quality without a unified scoring baseline.

How It Works

The skill takes a Douyin nickname or account ID, retrieves the account profile and recent post data, and scores six dimensions: profile, productivity, interaction, content quality, trend, and follower quality. Each dimension is normalized to a 100-point scale, then weighted into an overall score with a rating, risk warnings, and weakness notes.

The report usually includes basic account info, per-dimension scores, key findings, a recent post interaction table, risk alerts, and optimization suggestions. For signals such as fake followers, inflated metrics, restricted reach, posting gaps, or dependence on one post, it explains the issue with supporting data rather than only a single score.

Boundaries

It is useful for self-audits, competitor checks, and early partnership screening, but it does not replace real-time data from Douyin official creator tools. Nickname search may use fuzzy matching; use a full nickname or Douyin ID for precise checks. Some fields may show as unknown when the upstream service does not return them, and trend scores can be affected by a small sample of recent posts.