Run: 2026-07-09-01KX40J776Z6GGWJVREDBAVK1G

Run Details

Duration:
59.9s
Cost:
$0.091410
Provider:
OpenAI

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
Rain polished the black bricks outside the Raven’s Nest and broke the green neon sign into trembling pieces beneath Detective Harlow Quinn’s shoes. She stood across the road under the torn awning of a closed tailor’s, coat collar raised, watching the bar’s entrance between the red smears of passing buses. Old maps and black-and-white photographs covered the walls inside. Beyond them, drinkers shifted through amber light, their faces vanishing whenever the door swung shut. Her worn leather watch read 23:17. Tomás Herrera had entered at 21:06 carrying nothing. He emerged with a grey medical case in his right hand and a canvas satchel strapped across his chest. Quinn touched the radio clipped beneath her coat. “Control, target’s mobile. Wardour Street, northbound on foot.” Static scratched her ear. “Do you require support, Bravo Four?” “Not yet.” Herrera stepped off the kerb without looking. A taxi struck its horn. He slipped between the headlamps, coat flapping around his knees, short dark curls flattened by rain. Quinn waited for the taxi to pass, then crossed. Herrera never glanced behind him. He didn’t need to. Reflections did the work: shop windows, puddles, the chrome flank of a parked motorbike. At Brewer Street, his head tilted towards the dark glass of a restaurant. His pace changed. Quinn saw it in the set of his shoulders. “Control, he’s clocked me.” “Units are seven minutes out.” “He won’t give us seven.” Herrera broke into a run. Quinn went after him. Her shoes hammered the wet pavement. He cut across Brewer Street, vaulted a stack of rubbish bags and sent a cyclist swerving into the gutter. The cyclist’s curse followed them towards Lexington Street. “Herrera!” He looked back. Warm brown eyes. Olive skin. Rain coursing over a face she knew from a suspended licence photograph and three months of surveillance stills. A silver medallion bounced at his throat. “Metropolitan Police. Stop.” “You’ve got the wrong man.” His Seville accent clipped the words. He shoved through a knot of smokers outside a pub, tipping one man’s pint down his shirt. “Oi!” Quinn shouldered past. “Police. Move.” Herrera kicked open a service gate and plunged into an alley where bins crowded the walls. Quinn followed close enough to hear his breath. The medical case clipped a drainpipe with a hard crack. Its latches held. He reached the alley’s far end and found a delivery van blocking half the exit. Quinn gained three strides. “Put the case down.” Herrera spun and flung a bin lid. She ducked. The lid struck brick and rang like a cracked bell. Herrera planted one hand on the van’s bonnet, slid across it and landed in the road. A black cab bore down on him. Brakes shrieked. Herrera slapped the bonnet, twisted past the headlamp and ran north. Quinn cleared the van through the gap beside its bumper. Her left shoulder scraped metal. Heat stung through her coat. “Control, suspect heading north from Lexington. Grey coat, medical case. Dangerous driving caused, no injuries seen.” “You are directed to wait for support.” “No.” “Harlow—” She pulled the earpiece free. The chase lengthened through Soho, then broke into fragments: Herrera’s grey coat beyond a bus shelter, the medical case flashing under sodium lamps, his shadow sliding across shuttered shops. He knew where cameras failed. He used arcades, service lanes and narrow cuts between buildings that Quinn had never found on any council map. At Great Marlborough Street, he stole a bicycle from outside a takeaway. The courier who owned it lunged from the doorway. “My bike!” Herrera threw the medical case into the front basket and mounted. Quinn caught the rear carrier. The bicycle jerked sideways. Herrera drove an elbow back. It struck her cheekbone and filled her mouth with iron. She held on, boots skidding across paint-slick tarmac. “Let go.” “Get off the bike.” “You don’t know what’s in the case.” “Give me five minutes and a warrant.” A bus roared past close enough to tug at her coat. Herrera stamped down on the pedal. Quinn lost her grip and hit the road on one knee. The bicycle shot away. She rose before the pain settled. Her palm had opened on the grit, blood threading through rainwater. She wiped it on her trousers and ran for the unmarked car she had left two streets back. By the time she reached it, control had filled her radio with demands. Quinn ignored them, started the engine and followed Herrera’s route north. Traffic trapped her at Oxford Street. She watched the pedestrian signal count down while buses clogged the junction and umbrellas streamed across the road. No sign of the bicycle. Her hand tightened on the steering wheel. Three years earlier, DS Morris had vanished beneath a condemned block in Southwark. Quinn had found his warrant card, one shoe and a trail of blood that ended against an unbroken concrete wall. The case file called it an unresolved death. The pathologist had called the marks on the shoe animal contamination. No animal in Britain had left six parallel claws in leather. Herrera had treated a patient in that same building two nights before Morris disappeared. The light changed. Quinn drove north. She found the stolen bicycle abandoned beside a locked playground near Camden High Street. One wheel spun beneath the rain. Fresh mud marked the pavement, leading towards a fenced entrance sunk below street level. The sign above it had lost most of its lettering. CAM— TOW— ghosted through rust. Council chains looped around the gates, secured with a heavy padlock. Herrera stood on the far side. He had opened the gate without cutting the chain. Quinn braked across a loading bay and got out. “Herrera.” He looked over his shoulder. Rain shone on the scar along his left forearm where his sleeve had ridden up. The Saint Christopher medallion rested against his throat. He held a small white object between his fingers. Bone. “Go home, Detective.” “You’re under arrest.” “For riding a stolen bicycle?” “For evading arrest, assaulting a police officer and whatever you’ve packed in that case.” “Medicine.” “You lost your licence.” “People didn’t stop bleeding when the panel took my name off a register.” He backed towards the station steps. Quinn drew her baton. “Put the case down. Hands where I can see them.” “You followed me from the Raven.” “I’ve followed you for ninety-three days.” “That’s no way to meet someone.” “You met Morris.” Herrera stopped. The city pressed around them: tyres hissing through standing water, music leaking from a car at the lights, rain drumming on the metal hoarding. His fingers closed around the bone token. “Where did you hear that name?” “His diary.” “That wasn’t in the evidence disclosure.” “Neither was half of what he kept from me.” Herrera’s face tightened. “What did the diary say?” “It said you treated a man with no pulse.” A train passed underground. The pavement trembled beneath Quinn’s feet, though the station beyond the gate had been sealed for years. Herrera glanced towards the steps. “Detective, listen to me. The people down there don’t care about your badge. Some won’t understand it. A few will understand and take offence.” “Down where?” “Walk away.” “Open the gate.” “It’s open for me.” Quinn shoved the chained gate. It moved six inches, no more. The chain should have stopped Herrera too, yet he stood beyond it with the medical case at his feet. He raised the bone token and pressed it against the rusted bars. The chain slackened. Not broke. Slackened, each iron link softening like wet rope. Quinn stared at it. Morris’s shoe sat in her mind, sole turned upwards, six cuts scored through the leather. She had spent three years placing that shoe beside knives, machinery, industrial shredders and zoo escape reports. None had matched. Herrera slipped through the gate. The chain hardened behind him with a clank. Quinn forced her hand between the bars before the gap sealed. Iron crushed her knuckles. She bit down and shoved her shoulder through. Herrera caught her wrist. “Don’t.” “Take your hand off me.” “If you cross without a token, the gate takes payment.” “It can invoice the Met.” The bars tightened. Pain climbed her arm. Herrera swore in Spanish and pressed the bone token against her wrist. The pressure vanished. Quinn tore free and stumbled onto the landing. Herrera snatched up his case and sprinted down the tiled stairs. She followed. Water spilled over each step. Dead fluorescent tubes hung from the ceiling in wire cages, yet a dull blue light breathed through the tunnel below. Old posters peeled from the walls. Their printed faces had swollen in the damp, eyes stretched across paper blisters. “Herrera, stop.” “You’re past the gate. Shouting won’t improve things.” He cleared the ticket hall and vaulted a bank of corroded barriers. Quinn climbed over after him. Her coat snagged on a metal tooth. She ripped it free. Beyond the barriers, the tunnel split. One passage ended in brick. The other descended towards the platforms, where voices rose beneath the pulse of generators and the chime of struck glass. Herrera took the stairs two at a time. Quinn reached the top and halted. The station below did not resemble an abandoned ruin. Canvas awnings stretched along both platforms. Hundreds of lamps floated without chains or cables, each flame trapped inside a glass sphere. Stalls crowded the tracks themselves, connected by planks laid over the rails. Buyers moved between them beneath umbrellas made from stitched skins and lacquered paper. A woman with antlers examined a row of stoppered bottles. A child in a yellow raincoat held its own shadow on a lead. At the nearest stall, a butcher raised a cleaver over something that continued to blink. Quinn’s baton hung useless in her hand. Herrera had reached the platform. He pushed through the crowd, but heads turned as Quinn appeared above him. Conversations thinned. Faces lifted. Some looked human until the light caught their eyes. A broad man guarded the foot of the stairs. Gold wire stitched his lips shut. He extended one palm. Herrera showed the bone token. The guard let him pass. Quinn looked back. The ticket hall lay empty above her. Rainwater ran down the stairs and curled around her shoes. Her radio gave one burst of static, then a voice forced its way through. “Bravo Four, confirm location.” Quinn lifted the radio. Her thumb rested on the transmit button. Herrera glanced back from the crowd. For the first time that night, fear stripped the control from his face. “Don’t give them your name.” The guard held out his palm to Quinn. She checked the stairs behind her, then the market below. Herrera moved farther between the stalls, grey coat swallowed by silk banners and drifting blue smoke. Quinn clipped the radio back inside her coat. The guard’s palm remained open. “I don’t have a token.” Gold thread pulled at the corners of his mouth. A voice emerged from somewhere inside his chest. “Then pay with memory.” Quinn’s fingers closed around the worn leather strap of her watch. Morris had given it to her after her promotion, dropping it on her desk with a complaint about police salaries and cheap gifts. The leather still bore a dark notch from his thumbnail. She released it. “No.” The guard lowered his hand. “No token. No memory. No passage.” Herrera vanished behind a stall hung with cages. Quinn drew her warrant card and held it up. “Detective Harlow Quinn, Metropolitan Police.” The guard studied the card. Gold wire cut deeper into his flesh when his mouth curved. Herrera’s warning came back too late. The market repeated her name. It moved from stall to stall in whispers, croaks and voices that scraped like cutlery across stone. Harlow Quinn. Harlow Quinn. Harlow Quinn. The guard stepped aside. Quinn passed him and descended into the Veil Market.
created_at"2026-07-09T17:59:44.622Z" 7/9/2026, 5:59:44 PM
model"openai/gpt-5.6-sol-20260709"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency6785
moderation_latency(null)
generation_time59804
tokens_prompt1140
tokens_completion3356
native_tokens_prompt984
native_tokens_completion2883
native_tokens_completion_images0
native_tokens_reasoning335
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"
usage0.09141
router(null)
provider_responses
0
endpoint_id"a54c5de0-89bf-4ad7-a212-cf977eed918a"
id"resp_0f2bdaf6ee694924016a4fe190b03481958a63c9494903bbef"
is_byokfalse
latency216
model_permaslug"openai/gpt-5.6-sol-20260709"
provider_name"OpenAI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1783619984-4ucvraJoWUjPgkFwNAgX"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1783619984-sYxtCb8SRvCsEhRPAFV2"
upstream_id"resp_0f2bdaf6ee694924016a4fe190b03481958a63c9494903bbef"
total_cost0.09141
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1977
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)
89.88% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1977
totalAiIsms4
found
0
word"pulse"
count2
1
word"trembled"
count1
2
word"silk"
count1
highlights
0"pulse"
1"trembled"
2"silk"
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
narrationSentences192
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences192
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences250
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen29
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1977
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions106
wordCount1676
uniqueNames26
maxNameDensity2.15
worstName"Quinn"
maxWindowNameDensity4
worstWindowName"Quinn"
discoveredNames
Raven1
Nest1
Detective1
Harlow4
Quinn36
Herrera30
Brewer2
Street6
Lexington1
Seville1
Soho1
Great1
Marlborough1
Oxford1
Morris4
Southwark1
Britain1
Camden1
High1
Saint1
Christopher1
Spanish1
Veil1
Market1
Rain3
Gold3
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Morris"
4"Saint"
5"Christopher"
6"Market"
7"Rain"
places
0"Raven"
1"Brewer"
2"Street"
3"Lexington"
4"Seville"
5"Soho"
6"Great"
7"Marlborough"
8"Oxford"
9"Southwark"
10"Camden"
11"High"
12"Spanish"
13"Veil"
globalScore0.426
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences125
glossingSentenceCount1
matches
0"appeared above him"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1977
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences250
matches
0"placing that shoe"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs168
mean11.77
std11.76
cv1
sampleLengths
023
151
26
327
48
58
64
76
82
928
109
1136
123
139
144
155
165
175
184
1933
201
213
2230
233
245
2523
261
273
282
2937
3015
314
324
337
3428
357
3613
3720
3816
397
401
411
425
4353
4412
459
462
4711
485
4927
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences192
matches
0"been sealed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs311
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences1
totalSentences250
ratio0.004
matches
0"CAM— TOW— ghosted through rust."
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1679
adjectiveStacks1
stackExamples
0"lay empty above her."
adverbCount25
adverbRatio0.014889815366289458
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences250
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences250
mean7.91
std5.29
cv0.669
sampleLengths
023
127
29
315
46
58
619
78
88
94
106
112
127
135
1416
159
165
174
1814
1913
203
219
224
235
245
255
264
276
2819
298
301
313
323
332
3418
357
363
375
386
3917
401
413
422
4316
448
4510
463
4715
484
494
50.27% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.316
totalSentences250
uniqueOpeners79
18.52% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences180
matches
0"Dead fluorescent tubes hung from"
ratio0.006
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount45
totalSentences180
matches
0"She stood across the road"
1"Her worn leather watch read"
2"He emerged with a grey"
3"He slipped between the headlamps,"
4"He didn’t need to."
5"His pace changed."
6"Her shoes hammered the wet"
7"He cut across Brewer Street,"
8"He looked back."
9"His Seville accent clipped the"
10"He shoved through a knot"
11"Its latches held."
12"He reached the alley’s far"
13"Her left shoulder scraped metal."
14"She pulled the earpiece free."
15"He knew where cameras failed."
16"He used arcades, service lanes"
17"It struck her cheekbone and"
18"She held on, boots skidding"
19"She rose before the pain"
ratio0.25
26.67% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount156
totalSentences180
matches
0"She stood across the road"
1"Her worn leather watch read"
2"Tomás Herrera had entered at"
3"He emerged with a grey"
4"Quinn touched the radio clipped"
5"Static scratched her ear."
6"Herrera stepped off the kerb"
7"A taxi struck its horn."
8"He slipped between the headlamps,"
9"Quinn waited for the taxi"
10"Herrera never glanced behind him."
11"He didn’t need to."
12"Reflections did the work: shop"
13"His pace changed."
14"Quinn saw it in the"
15"Herrera broke into a run."
16"Quinn went after him."
17"Her shoes hammered the wet"
18"He cut across Brewer Street,"
19"The cyclist’s curse followed them"
ratio0.867
27.78% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences180
matches
0"By the time she reached"
ratio0.006
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences70
technicalSentenceCount2
matches
0"The chase lengthened through Soho, then broke into fragments: Herrera’s grey coat beyond a bus shelter, the medical case flashing under sodium lamps, his shadow…"
1"At the nearest stall, a butcher raised a cleaver over something that continued to blink."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
88.0149%