Run: 2026-02-19-01KHTYKZ8RGH32YK9N3FG8J56X

Run Details

Duration:
1m 46s
Cost:
$0.001555
Provider:
DeepInfra

Model input

System
You are an expert fiction writer. Always keep the following rules in mind: - Write in past tense and use General English spelling, grammar, and colloquialisms/slang. - Write in active voice - Always follow the "show, don't tell" principle. - Avoid adverbs and cliches and overused/commonly used phrases. Aim for fresh and original descriptions. - Convey events and story through dialogue. - Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. - Skip "he/she said said" dialogue tags and convey people's actions or face expressions through their speech - Avoid mushy dialog and descriptions, have dialogue always continue the action, never stall or add unnecessary fluff. Vary the descriptions to not repeat yourself. - Put dialogue on its own paragraph to separate scene and action. - Reduce indicators of uncertainty like "trying" or "maybe" When writing text: - NEVER conclude the scene on your own, follow the beat instructions very closely. - NEVER end with foreshadowing. - NEVER write further than what I prompt you with. - AVOID imagining possible endings, NEVER deviate from the instructions. - STOP EARLY if the continuation contains what was required in the instructions. You do not need to fill out the full amount of words possible.
User/Human
Take into account the following glossary of characters/locations/items/lore... when writing your response: <codex> <character id="4412" name="Aurora Carter" aliases="Rory, Laila, Aurora, Carter, Malphora" pronouns="she/her" species="Human" storyRole="Protagonist"> <eyeColor>bright blue</eyeColor> <hair>straight shoulder-length black</hair> <height>5'6"</height> <age>25</age> <scar>small crescent-shaped scar on her left wrist from a childhood accident</scar> <description>Aurora, referred to by her friends as Rory, is cool-headed, intelligent, and known for quick out-of-the-box thinking.</description> <backstory>Born in Cardiff to an Irish barrister father (Brendan Carter) and Welsh teacher mother (Jennifer Carter née Ellis), Rory reluctantly pursued Pre-Law at Cardiff University. She fled to London at the behest of her childhood friend Eva after leaving an abusive ex named Evan. By day, Rory works part-time as a delivery person for Yu-Fei Cheung's Golden Empress restaurant. She lives in a flat above Silas' bar.</backstory> </character> <character id="4413" name="Silas Blackwood" aliases="Silas, Si, the Spymaster" pronouns="he/him" species="Human" storyRole="Mentor"> <eyeColor>hazel</eyeColor> <hair>grey-streaked auburn</hair> <height>6'1"</height> <age>58</age> <beard>neatly trimmed, matching his grey-streaked auburn hair</beard> <limp>slight limp in his left leg from an old knee injury</limp> <signetRing>silver signet ring, always worn on his right hand</signetRing> <description>Silas is a retired intelligence operative turned bar owner. He carries himself with quiet authority.</description> <backstory>Former MI6 field agent who retired after a botched operation in Prague left him with a permanent knee injury. He opened "The Raven's Nest" bar in Soho as a front for his network of contacts.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the literary fiction genre. Two old friends who haven't seen each other in years run into each other unexpectedly at a bar. One of them has changed significantly. Through their conversation and the tension between who they were and who they've become, reveal the weight of time and unspoken regret. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary. </instructions>

Model response

AI
The air in The Raven’s Nest was thick with the scent of old wood and spilled whiskey. Aurora Carter wiped a damp cloth over the mahogany bar, her movements rhythmic and practiced. The low hum of a Miles Davis record spun on the turntable behind her, a familiar comfort in the dim light. Silas was in the back, inventorying stock, leaving her alone with the handful of late afternoon regulars nursing their pints in quiet corners. The door swung open, slicing a brief rectangle of grey London light across the floor. A man stepped in, shaking rain from a dark overcoat. He hesitated just inside, his eyes adjusting to the gloom, scanning the room with a slow, deliberate sweep. His gaze passed over her once, then snapped back, locking onto her face. A flicker of something—shock, recognition—passed over his features. Aurora went still, the cloth frozen in her hand. The years fell away in a dizzying rush. The set of his shoulders was broader, the lines around his eyes deeper, but it was him. Evan. He approached the bar, his footsteps silent on the worn floorboards. He didn’t smile. He slid onto a stool, placing his hands flat on the bar top. His knuckles were scarred now, the hands of a man who’d done more than push paper. “Rory,” he said. Her name sounded foreign in his mouth, a relic from a life she’d boxed up and left behind. “Evan.” Her voice was even, cooler than she felt. She resumed wiping the bar, focusing on a sticky ring of condensation. “Didn’t figure you for a Soho pub.” “Business,” he said, his voice a low rumble. It had lost its old, easy cadence, replaced by a clipped, guarded tone. “Meeting got cancelled. Saw the sign. Thought I’d wait out the rain.” She nodded toward the green neon glow beyond the door. “It’s stopped.” A faint, humorless smile touched his lips. “So it has.” Silence stretched between them, taut and heavy. The man she’d known was all restless energy and loud opinions, a live wire that constantly sought a ground. This man was a closed book, his stillness unnerving. “You work here?” he finally asked, watching her polish a glass. “Part-time. I deliver for a restaurant, too. Yu-Fei’s. Golden Empress.” “Delivering noodles.” He said it flatly, a statement, not a question. There was no judgment in it, just a dull sort of surprise. “It pays the rent. The flat’s upstairs.” She gestured vaguely toward the ceiling. His eyes followed the gesture, then returned to her. “You live above a bar.” “It’s quiet. Silas is a good landlord.” “Silas?” “The owner.” She didn’t elaborate. The less Evan knew, the better. The less he could find, if he ever went looking. He was studying her now, really looking, and she fought the urge to shrink back. His eyes traced the line of her shoulder, the way she held herself, the small crescent scar on her wrist she’d gotten falling off her bike at ten. He was cataloging the differences. “You cut your hair,” he said. Her free hand went instinctively to the ends of her black hair, now resting on her shoulders. It used to tumble down her back. “Easier.” “It suits you.” The compliment sounded rote, something he felt obligated to say. “You’ve changed too,” she countered, her tone carefully neutral. She wouldn’t give him the satisfaction of asking how, or why. He let out a short, sharp breath that wasn’t quite a laugh. “Yeah. I have.” He’d filled out, the lanky frame of his youth now solid, almost bulky. His suit was expensive, a sharp, dark wool that didn’t quite hide the tension in his shoulders. The boy who’d wanted to be a poet, who’d read Yeats to her on the banks of the Taff, was gone. This man smelled of crisp cologne and the metallic hint of rain. “What kind of business?” she asked, because the silence was becoming a physical weight. “Consulting.” The answer was immediate, smooth. Too smooth. “Consulting,” she repeated, letting the word hang in the air between them. “Vague.” “It pays the rent,” he echoed her earlier words, a hollow mimicry. His eyes finally left her face and scanned the bar—the maps on the walls, the black-and-white photos of a London long gone, the hidden door to Silas’s office disguised as a bookshelf. His gaze lingered there a moment too long, a predator noting an exit, a potential threat. “This is a strange place for you.” “I like it. It’s honest. People come here to drink, to talk, to be left alone. No pretensions.” “Unlike me.” She didn’t deny it. She just held his gaze. The unspoken words piled up in the space between them: the frantic phone calls, the slammed doors, the way he’d curl his hand into a fist when he was frustrated, the sharp, cruel things he’d say that he’d always apologize for later. The apologies that got quieter, less frequent, until they stopped altogether. “You left,” he said. It wasn’t an accusation. It was a fact, heavy with consequence. “Cardiff was… small.” “For both of us, apparently.” He finally looked away, down at his own hands on the bar. He turned his right hand over, studying the palm as if reading a fate he didn’t like. “I heard you were in London. From your mum. Ran into her at the market, must be… Christ, two years ago now.” The image of her mother making polite, strained conversation with him, of him walking away knowing where she was, sent a cold trickle down her spine. “She never said.” “I asked her not to.” He looked up, and for a fraction of a second, the mask slipped. She saw not the angry boy or the hardened man, but someone tired, burdened by a regret so deep it had carved grooves in his soul. “I thought about… looking you up. Wanted to.” “But you didn’t.” “No.” The mask was back. The consultant. The closed book. “Wouldn’t have been right.” The truth, the one they were both dancing around, settled over them. It hadn’t been right then, either. Her leaving wasn’t about the size of the city. It was about the size of his anger, the shrinking space he allowed her to occupy. He pushed back from the bar, the stool legs scraping against the floor. He pulled a wallet from his inside coat pocket, crisp black leather, and laid a fifty-pound note on the counter. “For your time.” “I didn’t pour you a drink.” “Keep it.” He stood, buttoning his coat. He looked every inch the successful man he’d become, a world away from the girl wiping down a bar. Yet he seemed smaller somehow, diminished by the performance. “It was good to see you, Rory. Really.” He was lying. It had been awful for both of them. A glimpse into a shared grave. “You too, Evan.” She left the money on the bar. He gave a curt nod, then turned and walked out. The door sighed shut behind him, cutting off the distant sound of traffic. The rectangle of light was gone. The bar felt darker, quieter. Aurora picked up the fifty-pound note. It felt cold between her fingers. She folded it neatly, once, twice, and slipped it into the tip jar. She watched the rain begin to sheet down the window, blurring the world outside into streaks of green neon and grey stone. She picked up her cloth and started wiping the bar again, right where he had been sitting, erasing the faint imprint of his presence.
created_at"2026-02-19T12:39:54.91Z" 2/19/2026, 12:39:54 PM
model"deepseek/deepseek-chat-v3.1"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency605
moderation_latency(null)
generation_time105482
tokens_prompt1110
tokens_completion1941
native_tokens_prompt992
native_tokens_completion1705
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached5
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.00155487
router(null)
provider_responses
0
endpoint_id"012f7d1f-23d4-4d03-9aa3-432d8ad82757"
id"cmpl-7127af65b3344b008efc1b9c01e11594"
is_byokfalse
latency76
model_permaslug"deepseek/deepseek-chat-v3.1"
provider_name"DeepInfra"
status200
api_type"completions"
id"gen-1771504794-gWryXAlbq5jDYld7q8e5"
upstream_id"cmpl-7127af65b3344b008efc1b9c01e11594"
total_cost0.00155487
cache_discount3.99e-7
upstream_inference_cost0
provider_name"DeepInfra"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags17
adverbTagCount2
adverbTags
0"he finally asked [finally]"
1"She gestured vaguely [vaguely]"
dialogueSentences43
tagDensity0.395
leniency0.791
rawRatio0.118
effectiveRatio0.093
88.20% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1271
totalAiIsmAdverbs3
found
0
adverb"really"
count2
1
adverb"carefully"
count1
highlights
0"really"
1"carefully"
100.00% AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0"Blackwood"
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
25.26% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1271
totalAiIsms19
found
0
word"rhythmic"
count1
1
word"familiar"
count1
2
word"gloom"
count1
3
word"scanning"
count1
4
word"flicker"
count1
5
word"footsteps"
count1
6
word"silence"
count2
7
word"traced"
count1
8
word"tension"
count1
9
word"weight"
count1
10
word"echoed"
count1
11
word"scanned"
count1
12
word"predator"
count1
13
word"potential"
count1
14
word"unspoken"
count1
15
word"down her spine"
count1
16
word"dancing"
count1
17
word"grave"
count1
highlights
0"rhythmic"
1"familiar"
2"gloom"
3"scanning"
4"flicker"
5"footsteps"
6"silence"
7"traced"
8"tension"
9"weight"
10"echoed"
11"scanned"
12"predator"
13"potential"
14"unspoken"
15"down her spine"
16"dancing"
17"grave"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells1
narrationSentences94
matches
0"was frustrated"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences94
filterMatches(empty)
hedgeMatches
0"begin to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences117
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen42
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1263
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions14
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions16
wordCount1069
uniqueNames11
maxNameDensity0.28
worstName"Aurora"
maxWindowNameDensity1
worstWindowName"Aurora"
discoveredNames
Raven1
Nest1
Carter1
Miles1
Davis1
London2
Evan2
Yeats1
Taff1
Silas2
Aurora3
persons
0"Carter"
1"Davis"
2"Evan"
3"Silas"
4"Aurora"
places
0"Raven"
1"London"
globalScore1
windowScore1
18.42% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences76
glossingSentenceCount4
matches
0"quite a laugh"
1"quite hide the tension in his shoulders"
2"as if reading a fate he didn’t like"
3"seemed smaller somehow, diminished by the performance"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.792
wordCount1263
matches
0"not the angry boy or the hardened man, but someone tired, burdened by a regret so deep it had carved gr"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences117
matches
0"say that he’d"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs47
mean26.87
std20.6
cv0.767
sampleLengths
076
164
235
343
421
528
633
712
810
935
1011
1110
1223
1313
1414
157
161
1721
1848
196
2025
2113
2220
2315
2463
2514
268
2713
2867
2918
302
3162
3215
333
3456
3529
3652
373
3814
3943
4036
416
4243
4317
4410
4534
4671
86.60% Passive voice overuse
Target: ≤2% passive sentences
passiveCount5
totalSentences94
matches
0"were scarred"
1"was gone"
2"was frustrated"
3"was, sent"
4"was gone"
44.05% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount4
totalVerbs171
matches
0"was studying"
1"was cataloging"
2"was becoming"
3"was lying"
94.02% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount0
flaggedSentences2
totalSentences117
ratio0.017
matches
0"A flicker of something—shock, recognition—passed over his features."
1"His eyes finally left her face and scanned the bar—the maps on the walls, the black-and-white photos of a London long gone, the hidden door to Silas’s office disguised as a bookshelf."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1076
adjectiveStacks0
stackExamples(empty)
adverbCount42
adverbRatio0.03903345724907063
lyAdverbCount10
lyAdverbRatio0.00929368029739777
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences117
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences117
mean10.79
std7.1
cv0.658
sampleLengths
017
115
221
323
415
510
618
713
88
99
108
1117
121
1311
143
1513
1616
173
1818
199
2012
217
228
2313
2412
2510
262
277
283
297
3019
319
3211
3310
3411
3512
3613
379
385
397
401
415
426
4310
4415
4528
465
476
4817
497
38.46% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats15
diversityRatio0.3076923076923077
totalSentences117
uniqueOpeners36
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences88
matches(empty)
ratio0
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount55
totalSentences88
matches
0"He hesitated just inside, his"
1"His gaze passed over her"
2"He approached the bar, his"
3"He didn’t smile."
4"He slid onto a stool,"
5"His knuckles were scarred now,"
6"Her name sounded foreign in"
7"Her voice was even, cooler"
8"She resumed wiping the bar,"
9"he said, his voice a"
10"It had lost its old,"
11"She nodded toward the green"
12"he finally asked, watching her"
13"He said it flatly, a"
14"She gestured vaguely toward the"
15"His eyes followed the gesture,"
16"She didn’t elaborate"
17"He was studying her now,"
18"His eyes traced the line"
19"He was cataloging the differences."
ratio0.625
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount86
totalSentences88
matches
0"The air in The Raven’s"
1"Aurora Carter wiped a damp"
2"The low hum of a"
3"Silas was in the back,"
4"The door swung open, slicing"
5"A man stepped in, shaking"
6"He hesitated just inside, his"
7"His gaze passed over her"
8"A flicker of something—shock, recognition—passed"
9"Aurora went still, the cloth"
10"The years fell away in"
11"The set of his shoulders"
12"He approached the bar, his"
13"He didn’t smile."
14"He slid onto a stool,"
15"His knuckles were scarred now,"
16"Her name sounded foreign in"
17"Her voice was even, cooler"
18"She resumed wiping the bar,"
19"he said, his voice a"
ratio0.977
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences88
matches(empty)
ratio0
80.75% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences46
technicalSentenceCount4
matches
0"He hesitated just inside, his eyes adjusting to the gloom, scanning the room with a slow, deliberate sweep."
1"His suit was expensive, a sharp, dark wool that didn’t quite hide the tension in his shoulders."
2"The apologies that got quieter, less frequent, until they stopped altogether."
3"The image of her mother making polite, strained conversation with him, of him walking away knowing where she was, sent a cold trickle down her spine."
36.76% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags17
uselessAdditionCount3
matches
0"he said, his voice a low rumble"
1"she countered, her tone carefully neutral"
2"she asked, because the silence was becoming a physical weight"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags8
fancyCount1
fancyTags
0"she repeated (repeat)"
dialogueSentences43
tagDensity0.186
leniency0.372
rawRatio0.125
effectiveRatio0.047
73.7506%