Run: 2026-03-25-01KMJ88PKC2BXECHR62CAJ7FMV

Run Details

Duration:
41.4s
Cost:
$0.000620
Provider:
Nebius

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="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</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> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. 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 rain had turned Soho into a slick labyrinth of reflections. Detective Harlow Quinn’s boots splashed through oil-stained puddles, her jacket clumping to her back like a second skin. The green neon sign of *The Raven’s Nest* flickered over a narrow alley, casting staccato shadows where a dark shape had just vanished. She flicked open her wristwatch—2:17 a.m.—then slammed it shut. Three years and six months since Morris. A shout echoed down the alley. She hit the corner and skidded to a halt. Tomás Herrera crouched halfway down a fire escape, his Saint Christopher medallion glinting as he palmed the rusted ladder and shoved it sideways. The steps crumpled like paper. Quinn’s jaw tightened. He’d known she’d be there. “Give it up, Quinn.” Herrera’s voice carried over the rain. “You don’t want to be down here when the tides turn.” *The tides.* She’d heard that phrase before. In the debrief after Morris’s body was pulled from the Thames, eyes wide under a leaden sky. The medallion dangled from Herrera’s neck as he descended the next flight, the flashlight in his hand carving a hole in the gloom. Quinn’s fingers closed around the butt of her gun. “NHS regulations don’t cover alchemical tinctures, Herrera. Hand over the merchandise.” He laughed, the sound short and brittle. “Regulations?” He gestured to the cracked bricks around them, the damp breath of the city rising in clouds. “You think I’m selling elixirs in a bodega?” Gunfire cracked over the sound of his retreating footsteps. Quinn lunged forward, but Herrera had already ducked into the mouth of an overgrown tunnel, where moss clung to brick like some slow, deliberate invasion. The flashlight beam vanished. She exhaled, sharp. This wasn’t official police business. The tunnel wasn’t listed in any records. But her feet were already moving, boots thudding against the damp floor. Herrera’s trail would be a straight line to *it*. The Veil Market. Her instincts tightened. This was the kind of chase that ended with a badge in the trash and a body in a body bag. The tunnel sloped downward for what felt like forever, the air growing colder. Herrera’s flashlight had left a trail through his own footprints. Quinn’s breath came in measured inhales. *No more Morris’s ghosts. Just the job.* She found the service door ajar, the hinges screeching like a trapped thing. The Tube station beyond was a ruin of shattered tile and broken escalators. Herrera had gone left—toward the tracks. Footsteps. Faint. Her fingers brushed the cold railing of the platform. The station was a tomb of graffiti and pigeon excrement, the tunnel walls slick with condensation. She could see the flicker of Herrera’s flashlight now, dancing across a mosaic of stained brick. “Stop, Herrera!” The light stilled. Quinn counted to three. Nothing. She crept forward. A low hum vibrated through the tracks. Herrera’s shadow danced on the wall. And then the train came—screams of metal, a wind that shoved her back against the platform. Herrera disappeared into the belly of the carriage. The doors closed. The train lurched forward, dragging a chain of shadows. Quinn stared at the empty space where it had been. Her chest felt hollowed out. The Market. She could turn back now, file a report, let the brass figure out who’d sanctioned a black site beneath the Tube. But Herrera was moving toward it, and if the Market was where Morris had gone quiet… Her hand went to her watch, thumbing the cracked bezel. *The tides turn.* The tunnel’s far wall pulsed with a low red glow. A doorway, half-buried in debris, marked the junction. Herrera’s flashlight had left a trail in the dust. Inside, the air was thick with the mingling stenches of mildew, burnt sage, and something metallic. A cavernous space stretched before her, its rafters strung with fairy lights and barbed wire. Stalls lined the concrete floor, draped in velvet and tarps. A woman in a moth-eaten tailcoat weighed herbs on a scale, eyes half-lidded. A man in a lab coat muttered over a vial of liquid as black as oil. Quinn’s breath caught. Herrera was at a stall near the back, his scarred forearm flexed as he handed over a vial to a seller with the elongated face of a weasel. The deal was done, the coins exchanged. Herrera turned. Her pulse throbbed in her ears. *Don’t panic, Quinn.* She’d been in enough alley brawls to know when someone was about to turn the tables. Herrera’s hand wasn’t on his weapon—it was on his medallion. A trick. He moved toward her like he’d been expecting her all along. “You’re not here for the tinctures,” he said. “You’re here for the story.” She gripped her gun tighter. “What’s in the vial?” “Something to keep a friend breathing.” He glanced at the seller, then at her. “You don’t want to know that, Quinn. You want to know who pulled the strings after they sank Morris.” The vial slipped from his hand. The weasel-faced seller lunged—a knife in her fingers, the blade etched with symbols. Quinn ducked. Herrera cursed. The knife slashed a shallow gash across his cheek. “Stay down!” Quinn shot the seller in the shoulder. The woman screamed and crumpled. Herrera caught her wrist as she turned. “We’re done here,” he hissed, eyes blazing. “This isn’t your war.” Her jaw set. “I’m done leaving bodies in the dark.” The Market had gone still. Stalls watched them. Herrera released her wrist and stepped back, the vial now in his palm like a relic. “Then follow the tides, Detective.” His voice dropped to a whisper. “But don’t expect to recognize the shore when you get there.” He turned, dissolving into the shadows.
created_at"2026-03-25T10:22:26.927Z" 3/25/2026, 10:22:26 AM
model"qwen/qwen3-32b-04-28"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency388
moderation_latency(null)
generation_time41334
tokens_prompt1164
tokens_completion1988
native_tokens_prompt1008
native_tokens_completion1732
native_tokens_completion_images(null)
native_tokens_reasoning467
native_tokens_cached0
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"
usage0.0006204
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provider_responses
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endpoint_id"aaa39b6c-e488-491a-91e4-e5fb66f86601"
id"cmpl-bb0070d72a471b1f"
is_byokfalse
latency388
model_permaslug"qwen/qwen3-32b-04-28"
provider_name"Nebius"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer(null)
api_type"completions"
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total_cost0.0006204
cache_discount(null)
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provider_name"Nebius"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags7
adverbTagCount0
adverbTags(empty)
dialogueSentences17
tagDensity0.412
leniency0.824
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount952
totalAiIsmAdverbs0
found(empty)
highlights(empty)
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
0.00% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount952
totalAiIsms20
found
0
word"flickered"
count1
1
word"flicked"
count1
2
word"echoed"
count1
3
word"glinting"
count1
4
word"gloom"
count1
5
word"footsteps"
count2
6
word"measured"
count1
7
word"shattered"
count1
8
word"flicker"
count1
9
word"dancing"
count1
10
word"mosaic"
count1
11
word"vibrated"
count1
12
word"lurched"
count1
13
word"pulsed"
count1
14
word"velvet"
count1
15
word"pulse"
count1
16
word"throbbed"
count1
17
word"etched"
count1
18
word"whisper"
count1
highlights
0"flickered"
1"flicked"
2"echoed"
3"glinting"
4"gloom"
5"footsteps"
6"measured"
7"shattered"
8"flicker"
9"dancing"
10"mosaic"
11"vibrated"
12"lurched"
13"pulsed"
14"velvet"
15"pulse"
16"throbbed"
17"etched"
18"whisper"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"air was thick with"
count1
highlights
0"the air was thick with"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences94
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences94
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences104
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen28
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans6
markdownWords19
totalWords947
ratio0.02
matches
0"The Raven’s Nest"
1"The tides."
2"it"
3"No more Morris’s ghosts. Just the job."
4"The tides turn."
5"Don’t panic, Quinn."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions2
unquotedAttributions0
matches(empty)
42.60% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions47
wordCount838
uniqueNames13
maxNameDensity2.15
worstName"Herrera"
maxWindowNameDensity3
worstWindowName"Herrera"
discoveredNames
Soho1
Harlow1
Quinn11
Raven1
Morris4
Herrera18
Saint1
Christopher1
Thames1
Gunfire1
Veil1
Market4
Tube2
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Morris"
4"Herrera"
5"Saint"
6"Christopher"
7"Gunfire"
8"Market"
places
0"Soho"
1"Thames"
globalScore0.426
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences62
glossingSentenceCount1
matches
0"felt like forever, the air growing cold"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount947
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences104
matches
0"heard that phrase"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs35
mean27.06
std16.96
cv0.627
sampleLengths
068
115
236
321
424
543
633
738
839
924
1036
1132
1243
132
147
151
163
1737
1827
192
2037
2113
2227
2370
2440
2537
2624
279
2833
2932
3021
3111
3210
3346
346
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences94
matches
0"was pulled"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs142
matches
0"were already moving"
5.49% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount6
semicolonCount0
flaggedSentences5
totalSentences104
ratio0.048
matches
0"She flicked open her wristwatch—2:17 a.m.—then slammed it shut."
1"Herrera had gone left—toward the tracks."
2"And then the train came—screams of metal, a wind that shoved her back against the platform."
3"Herrera’s hand wasn’t on his weapon—it was on his medallion."
4"The weasel-faced seller lunged—a knife in her fingers, the blade etched with symbols."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount848
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.01650943396226415
lyAdverbCount1
lyAdverbRatio0.0011792452830188679
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences104
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences104
mean9.11
std5.98
cv0.656
sampleLengths
011
118
223
39
47
56
69
723
85
93
105
1110
1211
137
1417
1523
169
1711
187
1918
208
219
2225
234
243
255
267
2712
289
293
303
3121
3213
3310
346
354
363
3713
3813
396
401
411
429
4316
4416
452
463
474
481
493
49.68% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.3269230769230769
totalSentences104
uniqueOpeners34
39.22% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences85
matches
0"Just the job.*"
ratio0.012
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount22
totalSentences85
matches
0"She flicked open her wristwatch—2:17"
1"She hit the corner and"
2"He’d known she’d be there."
3"He laughed, the sound short"
4"He gestured to the cracked"
5"She exhaled, sharp."
6"Her instincts tightened."
7"She found the service door"
8"Her fingers brushed the cold"
9"She could see the flicker"
10"She crept forward."
11"Her chest felt hollowed out."
12"She could turn back now,"
13"Her hand went to her"
14"Her pulse throbbed in her"
15"He moved toward her like"
16"She gripped her gun tighter."
17"He glanced at the seller,"
18"he hissed, eyes blazing"
19"Her jaw set."
ratio0.259
18.82% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount75
totalSentences85
matches
0"The rain had turned Soho"
1"Detective Harlow Quinn’s boots splashed"
2"The green neon sign of"
3"She flicked open her wristwatch—2:17"
4"A shout echoed down the"
5"She hit the corner and"
6"Tomás Herrera crouched halfway down"
7"The steps crumpled like paper."
8"Quinn’s jaw tightened."
9"He’d known she’d be there."
10"Herrera’s voice carried over the"
11"*The tides.* She’d heard that"
12"The medallion dangled from Herrera’s"
13"Quinn’s fingers closed around the"
14"He laughed, the sound short"
15"He gestured to the cracked"
16"Gunfire cracked over the sound"
17"Quinn lunged forward, but Herrera"
18"The flashlight beam vanished."
19"She exhaled, sharp."
ratio0.882
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences85
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences33
technicalSentenceCount0
matches(empty)
53.57% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount1
matches
0"he hissed, eyes blazing"
91.18% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount1
fancyTags
0"he hissed (hiss)"
dialogueSentences17
tagDensity0.118
leniency0.235
rawRatio0.5
effectiveRatio0.118
80.0188%