this is a SHAXPIR project
how does it work?

Deep Black

  by Sean McFate


(about 334 pages)
83,577
total words
of all the books in our library
46.70%
vividness
of all the books in our library
7.62%
passive voice
of all the books in our library
2.10%
all adverbs
of all the books in our library
0.69%
ly-adverbs
of all the books in our library
1.41%
non-ly-adverbs
of all the books in our library

clippings from this book

We’ve analyzed hundreds of millions of words, from thousands of different authors, training our linguistic models to recognize the most vivid words in the English language… the words that create the most intense sensory experiences: colors, textures, sounds, flavors, and aromas.

Based on our analysis, we’ve scanned through the pages of this book to find the two pages at the extremes, both the most-passive and the most-vivid pages, so that you can compare them side-by-side and see the difference:

MOST PASSIVE PAGE
MOST VIVID PAGE
after Ukraine didn’t matter. I was never off the grid. Brad Winters knew where I was the entire time. Then the realization hit, harder than the one on the roof: Winters had hired me. Or he had told the majordomo to hire me, which amounted to the same thing. Winters hadn’t just been watching me. He had been playing me like a grand piano. He had been keeping an eye on me, waiting for me to become useful to him again. And I was useful to him, I admitted. How else did that Apollo team locate Farhan in Sinjar so quickly? After all, I was the company’s best man by far, and those yahoos at the house didn’t have the subtlety to develop the kind of contacts necessary. It had to be me. Was that pride? Hell yes. But I’d earned it. And what did you use it for? I chastised myself. Brad Winters was the mastermind, not me. He had been manipulating the situation all along. He manipulated every situation. It was what the man did. And I’d never realized it. In the nine years I’d worked with him, I’d never fully grasped who he was. And in the four months he’d been following me since Ukraine—laughing at my pathetic efforts to disappear, no doubt—I’d never suspected he could still control me. He had trapped me. Again. He had tried to kill me again, just like in Ukraine. He would have killed me if I hadn’t been un-enchant the broom. Even Mickey Mouse knew the feeling. And yet few, I kept reminding myself, could avoid the pitfalls. Nine gongs of the grandfather clock. Nine o’clock. Outside, London plodded along in a morning rush hour rain, the damp and rheumy opposite of the dry desert heat. Eventually, the large pocket doors slid open. “Mr. Winters,” an Indian gentleman said. He looked healthy, happy, and put together by a valet. “Kabir,” Winters said, rising to shake hands. He didn’t introduce me, and Kabir didn’t ask. He barely looked my way. It was only after I’d followed on Winters’s heel that I realized the young man serving tea had followed on mine. The private office looked extracted from a Pall Mall social club circa 1850. Lit portraits hung from crown molding along red silk damask walls and oak paneling. Floor-to-ceiling windows with polished brass fixtures and frothy curtains overlooked an English garden. A four-tier crystal chandelier hung from a twelve-foot coffered ceiling, and wall-to-wall Persian carpets obscured the parquet floor. Decanters lined a credenza near a Venetian marble fireplace. At the far end of the room sat an enormous carved desk that could have been plucked from the lord chancellor’s personal office. We took the leather chairs across from it, as Kabir seated himself behind the desk. “Tea?” he asked, as the young man slid to the silver set on the credenza. He poured carefully and stirred in a cube of sugar. He was late twenties, dressed in Savile Row

emotional story arc

Click anywhere on the chart to see the most significant emotional words — both positive & negative — from the corresponding section of the text…
This chart visualizes the the shifting emotional balance for the arc of this story, based on the emotional strength of the words in the prose, using techniques pioneered by the UVM Computational Story Lab. To create this story arc, we divided the complete manuscript text into 50 equal-sized chunks, each with 1671.54 words, and then we scored each section by counting the number of strongly-emotional words, both positive and negative. The bars in the chart move downward whenever there’s conflict and sadness, and they move upward when conflicts are resolved, or when the characters are happy and content. The size of each bar represents the positive or negative word-count of that section.

similar books by different authors

other books by Sean McFate

something missing?

Our library is always growing, so check back often…

If you’re an author or a publisher,
contact us at submissions@prosecraft.io to help grow the library.