Run: 2026-09-23-01M36R6YSDS77YQHNJJ0JTA1PK

Run Details

Duration:
59.8s
Cost:
$0.002483
Provider:
OpenAI

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
The man saw her in the rain-smeared glass of the Raven’s Nest. For half a second, neither of them moved. Behind him, the bar’s green neon bled across the pavement; inside, the old maps and black-and-white photographs sat in their smoky gloom. Quinn watched his eyes shift from her reflection to her face. Then he ran. She shoved away from the brick wall and went after him. He cut across the street between two taxis. A horn blared. Quinn slipped on the slick curb, caught herself with one hand against a lamppost, and kept going. The man’s dark coat flashed between pedestrians on Shaftesbury Avenue. He had a narrow lead and knew how to use it: through the crowd, under umbrellas, over a low iron rail where Quinn had to go around. “Police!” she shouted. Nobody turned. The rain swallowed her voice. She touched the radio at her shoulder as she ran. “Quinn. Pursuit northbound from Soho. One male, dark coat, grey scarf. Requesting units to Camden High Street.” Static rasped back at her. She’d get an answer when she got an answer. The man glanced over his shoulder. His face was pale, his mouth open with effort. He looked less like a hardened criminal than someone who had seen the shape of what was coming and couldn’t make himself believe it. Quinn knew that look. She’d seen it in interview rooms, in hospital corridors, at the edge of a crime scene when the body was still warm. Usually the fear had a name. A warrant. A knife. A friend who’d decided to talk. Three years ago, DS Morris had worn that same look outside a derelict warehouse in Deptford. He’d said, “It’s not right,” and gone through the door anyway. Quinn pushed the memory down. The man was turning into a narrow passage between two shuttered shops. She followed. The passage stank of wet cardboard and sour beer. He clipped a stack of crates with his hip. They crashed across the paving. Quinn stepped over them, jaw set, the worn leather watch on her left wrist slick with rain. Her stride stayed measured even as her lungs began to burn. In. Out. Don’t chase his panic. Chase his choices. He burst onto Charing Cross Road, dodging a bus as it hissed past. Quinn came out behind him, one hand raised against the wash of water thrown from its wheels. A cyclist cursed her. She barely heard him. The man ran north. At Tottenham Court Road he cut west, then north again, threading the side streets with a certainty that tightened something in her chest. This wasn’t blind flight. He knew where he was going. He’d picked a route, and the rain was helping him: blurring faces, emptying the pavements, turning every curb and stair into a hazard. Quinn’s calves knotted. She didn’t let her pace break. “Stop!” she called again. He flung one hand out as he ran. A silver glint spun through the air and struck the pavement. Quinn saw it bounce near a drain but didn’t slow. Whatever he’d dropped could wait. The man couldn’t. At Warren Street he plunged across Euston Road on the last second of the signal. A car braked hard, its tyres shrieking on the wet asphalt. Quinn followed close enough to feel the blast of its horn against her back. A passenger leaned out to yell at her. Then the city narrowed into Camden Road, rain shining on the shopfronts and bus lanes. The man was slower now. So was she. His shoulders hitched with each breath. He looked back once, and Quinn saw no calculation in his face anymore. Only terror. He ducked through a gap in a fence beside a boarded-up entrance, half-hidden by a row of bins. Quinn cleared the fence after him and landed hard on the other side. The mouth of an old station stairwell yawned beneath the pavement. Water ran down its steps in thin black ribbons. A rusted sign hung above it, too worn to read. The man slowed at the top. Quinn drew her pistol. “Hands where I can see them.” He turned. Rain ran off his hair and down his cheeks. “You don’t want to come down here.” “That’s not your decision.” A red light winked at the bottom of the stairwell. Quinn caught the smell then, sharp and chemical beneath the damp: hot metal, crushed herbs, something sweet enough to make her throat tighten. Somewhere below, voices murmured in a steady, overlapping hum. The man reached inside his coat. “Don’t.” He froze. His hand came back out holding a small pale object. A finger bone, polished smooth and drilled at one end to take a brass ring. He clutched it in his fist. Quinn had seen the same thing once before—in a photograph tucked into an evidence file tied to the clique she’d been watching. A grainy image of a hand holding a bone token, the report dismissing it as a prop. She’d kept the picture because it bothered her. Because Morris had once laughed at her for keeping things that bothered her. The man backed toward the stairs. “Drop it,” she said. He did. The token struck stone, clattered down three steps, and stopped against the wall. He lunged after it. Quinn closed the distance and caught his coat. They hit the railing together. He twisted with a strength she hadn’t expected, drove an elbow into her ribs, and tore free. She felt the impact jar her teeth. He grabbed the token and vanished down the stairs. Quinn didn’t fire. The stairwell was too narrow, too crowded with echoes. Her finger stayed outside the trigger guard as she went after him. At the bottom, a narrow corridor ended at a steel door. The man lifted the bone token to a dark slit in the wall. Something clicked on the other side. The door swung inward, and a wash of amber light spilled across his face. A woman stood in the opening. Her clothes were layered and old-fashioned, her hair wrapped in a red scarf. She took the token from him without looking at Quinn. The man slipped past her. The woman’s eyes settled on Quinn. “You don’t have one.” Quinn raised her badge, though the woman seemed less interested in the shield than in the pistol. “Metropolitan Police. Step aside.” The woman smiled. Her teeth were dark at the edges. “That isn’t a token.” Behind her, the voices swelled. Quinn heard the clink of glass, the shuffle of many feet. The corridor smelled of rain, dust, and the same bitter sweetness that had followed her from the stairs. The door framed a place that had no business existing beneath Camden: a platform strung with lanterns, crowded with stalls and moving figures. A London Underground roundel hung at the far end, but its lettering had been scraped away. The man in the dark coat was already disappearing into the crowd. Quinn glanced back up the steps. No blue lights. No backup. Her radio gave a thin crackle, then silence. She could wait. Hold the entrance. Call for more units. Secure the stairwell. By the time anyone arrived, the man would be gone. She looked down at the bone token. The woman had dropped it beside her foot. The token was cold when Quinn picked it up. Not stone-cold. Colder than the rain had any right to make it, as though it had been resting in a freezer. She turned it once in her gloved hand. A small dark groove ran through its length. It looked real. “Where does this go?” she asked. The woman’s smile vanished. “Not where you think.” For an instant, the noise from below thinned to a single hollow note. It struck some buried place in Quinn, an old bruise she’d never managed to name. Morris, outside the warehouse. The words he’d said. The look on his face. Not right. Quinn’s left hand tightened around the token until its edges pressed through her glove. She could leave now and call in the whole of the Metropolitan Police. She could stand at the top of the stairs with her pistol raised and pretend that would be enough. Instead, she stepped through the door. The woman caught her sleeve. Quinn turned, pistol lifting between them. “Once you’re in,” the woman said, “they’ll know what you are.” “They already do.” The woman released her. Quinn crossed onto the abandoned platform. The door shut behind her with a weighty clang, sealing off the rain and the city noise. For a breath she heard only her own breathing, rough and close in her ears. Then the market closed around it. Stalls crowded the platform, their tops draped in canvas and old railway signs. Jars glowed with cloudy light. Bundles of dried roots hung beside knives whose blades reflected no lanterns. A man in a velvet coat weighed something pale and twitching on a brass scale. Somewhere, someone laughed too loudly. Somewhere else, a child cried. Quinn lowered the token into her coat pocket and kept her pistol close to her thigh. People watched her pass. Some looked away too late. One stallkeeper paused with a silver spoon held over a steaming bowl. The steam curled against the pull of the tunnel air, then reversed and streamed toward Quinn. She found the dark coat near a row of locked cabinets. He was speaking to a broad-shouldered man whose face was hidden behind a mesh veil. Quinn pushed through the crowd, shoulder first, her eyes fixed on the suspect. The man in the coat glanced up and saw her. He broke into a run again, vanishing between the stalls. Quinn followed. Behind her, the market’s murmur closed like a door.
created_at"2026-09-23T09:05:41.177Z" 9/23/2026, 9:05:41 AM
model"openai/gpt-6-luna-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency4154
moderation_latency(null)
generation_time59786
tokens_prompt888
tokens_completion3111
native_tokens_prompt810
native_tokens_completion4804
native_tokens_completion_images0
native_tokens_reasoning2759
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"completed"
service_tier"default"
usage0.002483
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1790154341-0b7tWl35KSf1UIj25Jbx"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790154341-zRizpJEVYbK1VmeCEaro"
upstream_id"resp_04d75ec813e1af46016ab396654a1c87d192cce7e02ec49c09"
provider_responses
0
endpoint_id"05e94e02-b9c2-4bbb-ba55-4082ee9ad687"
id"resp_04d75ec813e1af46016ab396654a1c87d192cce7e02ec49c09"
is_byokfalse
latency748
model_permaslug"openai/gpt-6-luna-20260922"
provider_name"OpenAI"
status200
total_cost0.002483
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
75.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags6
adverbTagCount1
adverbTags
0"she called again [again]"
dialogueSentences16
tagDensity0.375
leniency0.75
rawRatio0.167
effectiveRatio0.125
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1625
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)
81.54% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1625
totalAiIsms6
found
0
word"gloom"
count1
1
word"measured"
count1
2
word"glint"
count1
3
word"echoes"
count1
4
word"silence"
count1
5
word"velvet"
count1
highlights
0"gloom"
1"measured"
2"glint"
3"echoes"
4"silence"
5"velvet"
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
emotionTells0
narrationSentences174
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences174
filterMatches
0"watch"
hedgeMatches
0"began to"
1"managed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences184
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen27
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1624
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions9
unquotedAttributions0
matches(empty)
50.06% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions56
wordCount1551
uniqueNames20
maxNameDensity2
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Raven1
Nest1
Shaftesbury1
Avenue1
Quinn31
Morris3
Deptford1
Charing1
Cross1
Road4
Tottenham1
Court1
Warren1
Street1
Euston1
Camden2
London1
Underground1
Metropolitan1
Police1
persons
0"Raven"
1"Quinn"
2"Morris"
places
0"Shaftesbury"
1"Avenue"
2"Deptford"
3"Charing"
4"Cross"
5"Road"
6"Tottenham"
7"Court"
8"Warren"
9"Street"
10"Euston"
11"Camden"
12"London"
globalScore0.501
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences113
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1624
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences184
matches
0"knew that look"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs68
mean23.88
std19.87
cv0.832
sampleLengths
012
141
23
311
465
53
67
727
814
939
1042
1127
1217
132
1460
1538
164
1756
189
194
2037
2148
2244
2361
246
2510
2618
274
2842
296
301
3133
3260
336
344
3515
364
3746
3824
3944
4029
415
4210
4321
4414
4573
4612
4732
4810
4915
99.21% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences174
matches
0"were layered"
1"been scraped"
2"was hidden"
55.07% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount6
totalVerbs276
matches
0"was coming"
1"was turning"
2"was going"
3"was helping"
4"was already disappearing"
5"was speaking"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount1
flaggedSentences2
totalSentences184
ratio0.011
matches
0"Behind him, the bar’s green neon bled across the pavement; inside, the old maps and black-and-white photographs sat in their smoky gloom."
1"Quinn had seen the same thing once before—in a photograph tucked into an evidence file tied to the clique she’d been watching."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1560
adjectiveStacks0
stackExamples(empty)
adverbCount46
adverbRatio0.029487179487179487
lyAdverbCount5
lyAdverbRatio0.003205128205128205
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences184
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences184
mean8.83
std5.62
cv0.636
sampleLengths
012
18
222
311
43
511
68
73
817
910
1027
113
122
135
1410
1517
165
179
186
199
2024
214
2222
236
242
252
266
2716
2811
295
3012
312
329
339
345
3517
3611
371
381
394
403
4113
4217
434
444
454
4623
474
486
4923
44.57% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.29347826086956524
totalSentences184
uniqueOpeners54
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount8
totalSentences157
matches
0"Then he ran."
1"Usually the fear had a"
2"Then the city narrowed into"
3"Somewhere below, voices murmured in"
4"Instead, she stepped through the"
5"Then the market closed around"
6"Somewhere, someone laughed too loudly."
7"Somewhere else, a child cried."
ratio0.051
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount45
totalSentences157
matches
0"She shoved away from the"
1"He cut across the street"
2"He had a narrow lead"
3"She touched the radio at"
4"She’d get an answer when"
5"His face was pale, his"
6"He looked less like a"
7"She’d seen it in interview"
8"He’d said, and gone through"
9"He clipped a stack of"
10"They crashed across the paving."
11"Her stride stayed measured even"
12"He burst onto Charing Cross"
13"She barely heard him."
14"He knew where he was"
15"He’d picked a route, and"
16"She didn’t let her pace"
17"she called again"
18"He flung one hand out"
19"His shoulders hitched with each"
ratio0.287
55.54% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount127
totalSentences157
matches
0"The man saw her in"
1"Quinn watched his eyes shift"
2"She shoved away from the"
3"He cut across the street"
4"A horn blared."
5"Quinn slipped on the slick"
6"The man’s dark coat flashed"
7"He had a narrow lead"
8"The rain swallowed her voice."
9"She touched the radio at"
10"Static rasped back at her."
11"She’d get an answer when"
12"The man glanced over his"
13"His face was pale, his"
14"He looked less like a"
15"Quinn knew that look."
16"She’d seen it in interview"
17"A friend who’d decided to"
18"He’d said, and gone through"
19"Quinn pushed the memory down."
ratio0.809
63.69% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences157
matches
0"Because Morris had once laughed"
1"By the time anyone arrived,"
ratio0.013
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences70
technicalSentenceCount1
matches
0"At Tottenham Court Road he cut west, then north again, threading the side streets with a certainty that tightened something in her chest."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount0
matches(empty)
25.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount2
fancyTags
0"she shouted (shout)"
1"He’d (would)"
dialogueSentences16
tagDensity0.375
leniency0.75
rawRatio0.333
effectiveRatio0.25
88.3230%