Reading Your Dashboards
Making sense of your manuscript analytics
Tension and Pacing Dashboards
The Tension Plot displays your manuscript's tension arc as a continuous line graph, similar to an EKG reading. Each scene contributes a data point based on its tension level, and the resulting shape shows the emotional trajectory of your story. A well-paced narrative typically shows a pattern of rising tension with periodic valleys for breathing room, building toward a climax near the end.
Look for long flat sections where tension neither rises nor falls significantly. These plateaus often correspond to stretches of the manuscript where the stakes feel static and readers may lose engagement. Similarly, watch for tension drops in unexpected places, which might indicate that a scene deflates momentum at a point where the story should be accelerating.
The Pacing Heatmap classifies each scene by its pacing type and displays the results as a color-coded grid across your manuscript. At a glance you can see whether your story alternates between fast and slow scenes or falls into monotonous stretches of the same pace.
The most common pacing problem visible on the heatmap is long runs of the same color, indicating multiple consecutive scenes at the same tempo. Even in a thriller, unbroken high-speed pacing exhausts readers. Even in literary fiction, an extended sequence of slow contemplative scenes can test patience. Effective pacing comes from contrast and variation.
The Character Dashboard
The Character dashboard offers five specialized tabs that analyze how your characters function throughout the manuscript. Character problems are among the hardest issues to diagnose through linear reading because they emerge from patterns across the entire book.
- Presence
- A matrix view showing which characters appear in which scenes. Gaps in presence reveal where characters vanish from the narrative for extended stretches, which can cause readers to forget about them or feel that their storylines were abandoned.
- Timeline
- Maps character appearances chronologically across your manuscript, showing the shape of each character's journey through the story. This view makes it easy to spot characters who cluster in the first half and disappear, or who arrive late and feel underdeveloped.
- Ranking
- Ranks characters by word count and scene frequency, giving you a quantitative measure of how much space each character occupies. If a character you consider secondary has more word count than your protagonist, this tab will surface that imbalance immediately.
- Evolution
- Tracks how character traits, relationships, and behaviors shift across the manuscript. This tab helps you verify that your characters are actually changing over the course of the story rather than remaining static despite the events they experience.
- Arc Notes
- A workspace for recording planned character development alongside what the analysis reveals. You can compare your intended arc against what the text actually delivers, identifying places where the execution drifts from the plan.
Key Findings
The Key Findings view is your executive summary. It synthesizes signals from across all dashboards into a single prioritized list of the most significant observations about your manuscript. Rather than requiring you to visit each dashboard individually and interpret raw charts, Key Findings surfaces the conclusions that matter most.
Each finding is drawn from one or more dashboard data sources and includes context explaining why it was flagged and what it might mean for your revision. Findings are ranked by potential impact, so the issues most likely to affect reader experience appear at the top of the list.
Use Key Findings as your starting point when you sit down for a revision session. Scan the top items, identify which ones align with problems you already sensed, and use the links to jump directly into the relevant dashboard for deeper investigation. This approach ensures you spend your revision energy on the issues that matter most rather than getting lost in data exploration.
Key Findings is especially powerful after you have made significant changes during a revision pass. Run the analysis again and check whether your top findings have shifted. Seeing previously flagged issues disappear from the list confirms that your revisions are working, while new findings may surface problems introduced by the changes.