Run: 2026-09-23-01M37HKB99KB8F9T3J1D784BXQ

Run Details

Duration:
46.2s
Cost:
$0.024400
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 came out of the Raven’s Nest with blood on his cuff and looked straight at Harlow Quinn. For half a second, neither of them moved. Rain fell between them, silver in the green neon above the bar door. Then Tomás Herrera turned and ran. Quinn shoved off the wall. “Herrera! Police!” He cut across the pavement, nearly taking a woman off her feet, and sprinted toward the junction. Quinn followed, one hand inside her coat to keep her warrant card from slapping against her ribs. A taxi leaned on its horn as Herrera darted in front of it. Quinn went behind, skidding on the white paint of a crossing, and heard the driver shout something through his open window. Herrera was fast. He had several inches of stride on her and the recklessness of a man who knew the road better than the people driving on it. But he glanced back too often. Quinn kept him in sight past the dark shopfronts and the late-night queues outside clubs, through the wash of headlights and rain. Three hours earlier, she had watched him enter the Raven’s Nest carrying a medical case. He had stayed in its hidden back room for eleven minutes. He had come out without the case, carrying a folded paper bag that had left a dark stain across his cuff. She had been waiting to see who collected it. Now she had to catch him before he got rid of it. Herrera swung left into a narrow street lined with delivery doors. Quinn followed close enough to hear the slap of his shoes through puddles. He knocked over a stack of empty beer crates. Plastic cracked against the pavement in front of her. She cleared the first crate and kicked the second aside. “Herrera, stop!” He didn’t answer. At the far end of the street he grabbed the handlebars of a parked bicycle and dragged it across her path. Quinn jumped the rear wheel, landed badly, and felt a sharp pull in her right knee. By the time she straightened, he had reached the corner. She saw his face in profile as he looked back. Short curls plastered to his forehead. Fear in his eyes, plain even at that distance. He clutched the paper bag beneath his coat. Quinn gave chase. Two streets later, Herrera tried to board a bus as it pulled away. The driver shut the doors before he reached them. Quinn gained ten yards while Herrera stood there pleading through the glass. He saw her reflection in the bus window and ran again. At the next junction he disappeared into a black cab. Quinn slapped the boot as it pulled out, shouted for the driver to stop, and got a spray of gutter water across her legs for the effort. She caught the registration. Her radio was in her hand before the cab reached the traffic lights. “Control, this is DC Quinn. Suspect in a black cab, registration Lima Delta—” A bus pulled between them. By the time it cleared, the cab had turned north. Quinn gave the rest of the plate, her position, and Herrera’s name. She asked traffic units to locate the cab and ran toward the main road, where she might flag down another. Rain worked its way under her collar. Her right knee began to stiffen. The cab had been a good move. Herrera could change vehicles twice before a patrol car found the first driver. Quinn slowed at the kerb, scanning the traffic. No empty taxis. A night bus groaned to a halt up the road. Her phone buzzed. Control had the cab on a camera heading toward Camden. Quinn looked at the approaching bus, then at the route displayed above its windscreen. Camden Town. She got on. By the time she reached the high street, the rain had thinned to a cold mist. Control had found the cab driver. He had dropped a man matching Herrera’s description near a boarded-up Tube entrance five minutes ago. The driver said his passenger had paid cash and left by the passenger-side door before the cab had quite stopped. Quinn thanked Control and asked for a unit to meet her there. The entrance stood between a shuttered pawnbroker’s and the hoardings around a demolition site. Plywood covered the old station sign, but the familiar red curve of the Underground roundel showed through where rain had peeled one corner loose. A chain hung across the gate. Its padlock lay open on the ground. Herrera’s shoe print showed in the pale mud beyond it. Quinn stopped. Traffic hissed along the high street behind her. Down the stairwell, she could hear water dripping and, beneath it, something she could not place. Voices, perhaps. Too many of them for an abandoned station. She checked her phone. No signal. Her radio gave a short burst of static when she keyed it. “Control, I’m at the old entrance on—” The static swallowed her words. The sensible course was to wait for the unit. She had Herrera’s name and address. She had the cab driver. If he had taken evidence underground, uniformed officers could seal the exits once they knew where those exits were. But Herrera knew she had seen the bag. The stain on his cuff had looked like blood. Waiting might give him time to hand it to someone else, or destroy whatever he had carried out of that room. Quinn unclipped the torch from her belt and stepped over the chain. The stairs descended farther than she expected. Modern graffiti gave way to old cream tiles, then to bare concrete sweating moisture. Her footsteps rang against the walls. At the bottom, a ticket hall opened beneath a ceiling webbed with cables. The ticket windows were boarded shut. Beyond the barriers, faint amber light touched the walls of a passage. Quinn switched off her torch. Someone laughed ahead. A woman replied in a language Quinn didn’t recognise. A bell rang once, small and clear. She moved along the wall and looked around the corner. The passage ended at a platform crowded with stalls. Canvas awnings had been strung beneath the old station signs. Lamps burned blue and yellow above tables laden with glass jars, locked wooden boxes, bundles of herbs and lengths of bright wire. People moved shoulder to shoulder between them. Quinn saw a man in a business suit with wet trouser cuffs, two young women sharing an umbrella they had not bothered to close, an elderly vendor counting coins under a magnifying lens. Somewhere, meat sizzled. The air smelled of damp stone, hot fat and sharp medicinal chemicals. At the entrance to the platform, a woman sat behind a narrow desk. A queue had formed in front of her. Each person placed a small object in her palm before being allowed through the turnstile. Herrera stood third from the front. Quinn stayed in the shadow of the passage. He had taken off his coat and held it over one arm. His shirtsleeve was soaked red from cuff to elbow. So the blood was his. Quinn felt a brief, unwanted jolt of concern. Herrera’s left forearm bore an old knife scar; this was new, higher up and still bleeding. The person ahead of him passed a pale disk to the woman at the desk. She examined it and handed it back. As Herrera reached into his pocket, he looked over his shoulder. Their eyes met. He went still. Then he pushed past the turnstile before the woman could stop him and vanished into the crowd. Quinn swore and stepped out of the passage. The woman at the desk stood. “Token,” she said. Quinn held up her warrant card. “Police. Move aside.” The woman looked at the card, then at Quinn. She had silver rings on every finger, including the thumbs. “Token.” “I’m pursuing a suspect.” “Then he should have one.” Quinn put her card away. Herrera was already lost among the awnings. Behind her, heavy footsteps sounded on the stairs. Backup, she thought, until a man rounded the corner carrying a crate of bottles. He passed without looking at her, set the crate down by the desk and produced a small white disk from his pocket. Bone, Quinn realised. The woman waved him through. Quinn touched her radio. Static. “How do I get a token?” “You don’t.” The woman sat down again. Quinn could force her way past. The turnstile was waist-high, and the woman had no visible weapon. But the crowd beyond had begun to notice the argument. Several faces turned toward Quinn, then away too quickly. She was alone, with no reliable radio, pursuing a man into a place whose only exit she knew stood behind her. She looked back at the empty passage. Rainwater ran in a thin line down the centre of the floor. DS Morris had died after following a witness alone into a derelict building. Three years of reports and interviews had never made sense of the evidence. His last call had broken up in static too. Quinn had promised herself she would never mistake impatience for courage again. A crash came from the far end of the platform. People shouted. Between two awnings, Quinn saw Herrera stumble into a table. Glass broke at his feet. He caught himself with his good arm, then kept moving toward a dark tunnel beyond the stalls. He was leaving blood on the ground. The woman at the desk followed Quinn’s gaze. Her expression changed, just slightly. “He won’t get far like that.” “Then let me through.” “I can’t.” “You mean you won’t.” The woman glanced toward the tunnel. For the first time, Quinn noticed the gate that blocked it: iron bars set deep into the old tiled arch. Herrera stopped there and struck the bars with his palm. Someone on the other side spoke to him. The gate did not open. He turned. Even from the entrance Quinn could see how pale he was. She looked at the woman at the desk. “If he bleeds out down here, I’m coming back for you.” “Then you’d best be quick.” The woman reached under the desk. Quinn shifted her weight, ready to move, but all the woman brought out was a shallow wooden tray. Three bone disks lay in it. “One use,” she said. “You return it on your way out.” Quinn picked one up. It was warm. She almost dropped it. The woman watched her closely. “Name?” “Harlow Quinn.” The woman’s pen paused above a ledger. “Of course.” Quinn leaned forward. “What does that mean?” The woman wrote something down and pushed the turnstile open. From the tunnel, Herrera shouted, “Quinn! Don’t come in!” Then the lights above the stalls went out, one after another, and something hit the iron gate hard enough to shake the tiles under Quinn’s feet. People surged toward the entrance. Quinn caught the turnstile before it could swing shut against her. For one heartbeat she stood between the empty passage and the crush of strangers coming off the platform. Herrera shouted again, but the words disappeared beneath the noise. She put the bone disk in her pocket and forced her way through.
created_at"2026-09-23T16:29:21.59Z" 9/23/2026, 4:29:21 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2480
moderation_latency(null)
generation_time46134
tokens_prompt888
tokens_completion2721
native_tokens_prompt810
native_tokens_completion2278
native_tokens_completion_images0
native_tokens_reasoning0
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"
usage0.0244
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790180961-tk3gCToEf5aVWUsbgjyt"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790180961-FBQRHmzf7DGQOMC1AbK9"
upstream_id"resp_0e554e5bdce0b87d016ab3fe61cfc487d1aeda89cf6ca1c17f"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_0e554e5bdce0b87d016ab3fe61cfc487d1aeda89cf6ca1c17f"
is_byokfalse
latency462
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.0244
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
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags4
adverbTagCount0
adverbTags(empty)
dialogueSentences24
tagDensity0.167
leniency0.333
rawRatio0
effectiveRatio0
94.64% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1864
totalAiIsmAdverbs2
found
0
adverb"quickly"
count1
1
adverb"slightly"
count1
highlights
0"quickly"
1"slightly"
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)
83.91% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1864
totalAiIsms6
found
0
word"scanning"
count1
1
word"familiar"
count1
2
word"footsteps"
count2
3
word"sense of"
count1
4
word"weight"
count1
highlights
0"scanning"
1"familiar"
2"footsteps"
3"sense of"
4"weight"
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
narrationSentences178
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount2
narrationSentences178
filterMatches(empty)
hedgeMatches
0"tried to"
1"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences198
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen33
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1864
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions80
wordCount1764
uniqueNames14
maxNameDensity2.21
worstName"Quinn"
maxWindowNameDensity4
worstWindowName"Quinn"
discoveredNames
Raven2
Nest2
Harlow1
Quinn39
Tomás1
Herrera20
Camden2
Town1
Tube1
Control3
Underground1
Morris1
Three3
People3
persons
0"Raven"
1"Nest"
2"Harlow"
3"Quinn"
4"Tomás"
5"Herrera"
6"Control"
7"Underground"
8"Morris"
9"People"
places
0"Camden"
1"Town"
globalScore0.395
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences136
glossingSentenceCount1
matches
0"looked like blood"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1864
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences198
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs84
mean22.19
std18.87
cv0.85
sampleLengths
019
127
27
368
456
547
621
752
82
93
1047
1133
123
1345
1437
1517
1613
1715
1845
1941
2013
2116
223
2358
2412
2551
2610
272
2834
2918
307
315
3239
3338
3412
3558
365
3719
3810
399
4087
4136
426
4329
4429
4533
463
4720
4814
493
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences178
matches
0"were boarded"
1"being allowed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs303
matches
0"was leaving"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences198
ratio0.005
matches
0"Herrera’s left forearm bore an old knife scar; this was new, higher up and still bleeding."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1768
adjectiveStacks0
stackExamples(empty)
adverbCount45
adverbRatio0.025452488687782805
lyAdverbCount7
lyAdverbRatio0.003959276018099547
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences198
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences198
mean9.41
std5.79
cv0.615
sampleLengths
019
18
213
36
45
52
617
717
813
921
103
1125
126
1322
1415
1511
1621
179
1812
1911
2013
219
229
2310
242
253
2621
2716
2810
2910
306
319
328
333
3413
359
3612
3711
3810
3927
404
4113
4213
435
4410
4512
4620
477
486
497
50.84% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.32323232323232326
totalSentences198
uniqueOpeners64
98.62% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount5
totalSentences169
matches
0"Then Tomás Herrera turned and"
1"Too many of them for"
2"Somewhere, meat sizzled."
3"Then he pushed past the"
4"Then the lights above the"
ratio0.03
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount42
totalSentences169
matches
0"He cut across the pavement,"
1"He had several inches of"
2"He had stayed in its"
3"He had come out without"
4"She had been waiting to"
5"He knocked over a stack"
6"She cleared the first crate"
7"He didn’t answer."
8"She saw his face in"
9"He clutched the paper bag"
10"He saw her reflection in"
11"She caught the registration."
12"Her radio was in her"
13"She asked traffic units to"
14"Her right knee began to"
15"Her phone buzzed."
16"She got on."
17"He had dropped a man"
18"Its padlock lay open on"
19"She checked her phone."
ratio0.249
72.43% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount131
totalSentences169
matches
0"The man came out of"
1"Rain fell between them, silver"
2"Quinn shoved off the wall."
3"He cut across the pavement,"
4"Quinn followed, one hand inside"
5"A taxi leaned on its"
6"Quinn went behind, skidding on"
7"Herrera was fast."
8"He had several inches of"
9"Quinn kept him in sight"
10"He had stayed in its"
11"He had come out without"
12"She had been waiting to"
13"Herrera swung left into a"
14"Quinn followed close enough to"
15"He knocked over a stack"
16"She cleared the first crate"
17"He didn’t answer."
18"Quinn jumped the rear wheel,"
19"She saw his face in"
ratio0.775
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount6
totalSentences169
matches
0"Now she had to catch"
1"By the time she straightened,"
2"By the time it cleared,"
3"By the time she reached"
4"If he had taken evidence"
5"Even from the entrance Quinn"
ratio0.036
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences82
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount1
fancyTags
0"the tunnel Herrera shouted (shout)"
dialogueSentences24
tagDensity0.125
leniency0.25
rawRatio0.333
effectiveRatio0.083
94.4587%