story-long-scan

To scan web novel rankings for topic selection, this Skill collects ranking snapshots from platforms like Qidian, Fanqie, and Jinjiang, then analyzes genre trends to output structured market scan reports with actionable positioning guidance.

Analyzing long-form web novel genre trends involves cross-dimensional evaluation of ranking list composition and new book performance across paid and free tracks. This Skill infers reader preferences and delivers structured conclusions rather than scattered notes.

Yes, you can generate competitive positioning reports without manual collection. The Skill uses browsing automation via agent-browser to capture ranking data, with a manual data fallback mechanism if automated collection encounters barriers.

To get actionable topic directions from market data, the Skill formats findings into a Markdown scan report and provides 3 to 5 differentiated entry points, including recommended platforms and risk warnings for near-term genre trends.

Yes, agent-browser is required for automated multi-platform web novel market scanning. If browser automation fails, the Skill supports manual data fallback to ensure the market scan report is still generated.

Limitations when scanning competitive positioning include dependency on browser automation stability for accessing live platforms. The Skill relies on near-term ranking snapshots and provides manual fallback if automated browsing is blocked.