Run: 2026-09-23-01M37HEH6K3RH9E2DKK7TT7072

Run Details

Duration:
52.8s
Cost:
$0.028980
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 a white disc clenched in his fist. Detective Harlow Quinn pushed away from the wall opposite the bar. Rain had soaked through the shoulders of her coat. Above the entrance, green neon turned every puddle the colour of old glass. “Herrera.” Tomás Herrera stopped. For half a second he looked straight at her, and she saw that the blood was fresh. Then he ran. Quinn crossed the road behind a taxi, close enough to feel its tyres throw water across her shins. Herrera cut left into the stream of late-night drinkers on Wardour Street. He was fast, but he kept his right hand pressed to his jacket pocket. Whatever he’d taken out of the Nest mattered more to him than balance. “Police. Stop!” A woman stepped aside. Herrera slipped past her and disappeared around the corner. Quinn followed, boots striking wet pavement. Eighteen years on the job had taught her not to sprint blind after a man who knew where he was going. She took the corner wide, checked his hands, checked the alley mouth beyond him. No weapon she could see. He vaulted a low chain at the far end of the lane. Quinn went around the post without slowing. Her radio crackled against her shoulder. “Control, this is Quinn. In foot pursuit of Tomás Herrera, heading north from the Raven’s Nest. Blood on his clothing. Request units to—” Static swallowed her. She tried again. The transmission light blinked red, then went dark. Ahead, Herrera looked back. His short curls were plastered to his forehead. Even from twenty yards, Quinn could see the fear in his face. That bothered her more than the running. For six weeks she’d watched people go in and out of the Nest. Herrera had been among the regulars: a former paramedic with no licence, a talent for arriving shortly before injured people vanished from hospital records. He’d smiled politely when she questioned him. He’d told her he worked nights because some people couldn’t afford to be seen. Tonight, a young man had gone into the bar under his own power. Twenty minutes later Herrera had emerged with blood on his cuff. He reached a bus stop, changed direction sharply and darted across the road in front of a cyclist. Quinn caught a glimpse of silver at his throat: the Saint Christopher medallion he always wore. The cyclist shouted. Quinn raised a hand in apology and followed. She got within arm’s reach outside a shuttered pharmacy. Herrera glanced back at the movement and swung an elbow. She caught his sleeve. The fabric tore between her fingers, and her grip slid down his left forearm. He hissed in pain. A long pale scar ran beneath her thumb. Then he twisted free. “I need to get this there,” he said. “Get what where?” He kept running. A night bus pulled up ahead. Herrera cut behind it, and Quinn lost him for three seconds in a wall of red metal and spray. By the time she cleared the bus, he was climbing into a black cab. “Camden,” she heard him tell the driver. Quinn slapped her palm against the rear window. Herrera ducked his head. The cab surged into traffic, leaving her standing in its exhaust. She got the registration. Her phone had one bar of signal. She sent the number and destination to the night desk, then flagged down the next cab. “Follow that one,” she said. The driver glanced at her warrant card and pulled out without a word. Through the smeared windscreen, Herrera’s cab drifted in and out of view. Quinn held her phone by the window, trying to make a call. No connection. She looked at the time on the dash. Well past midnight. The white disc troubled her. She had seen one like it on Morris’s desk three years ago, the morning before he died. Bone, he’d said, though she’d thought he was joking. It had a small hole bored near one edge and a notch that looked cut by hand. Morris had been tracing missing people through addresses that didn’t stay occupied. He’d gone to meet a source alone. They’d found him beneath a railway arch with no wound anyone could explain and rainwater in his lungs, though the street had been dry. Quinn had kept his case file when they told her to close it. The cab ahead turned north. She leaned forward. “Don’t lose him.” At Camden, Herrera paid and ran before the driver had stopped counting change. Quinn shoved a note at her own driver and got out into harder rain. Herrera crossed an empty street market, ducking between chained stalls and bins stacked for collection. Quinn followed at a measured run, close enough to hear his shoes slap through standing water. He didn’t look back now. He passed a locked service gate beneath the railway line and headed for a tiled entrance between two boarded shopfronts. No station name remained above it. Someone had painted over the sign in black, but the rain picked out the raised outlines of old letters. Herrera reached a steel door inside the entrance. He knocked three times, paused, then twice. A slot opened at eye level. Quinn stopped behind a pillar, breathing through her nose. A hand extended through the slot. Herrera placed the white disc in its palm. The door opened just wide enough to admit him. Light spilled over the tiles: warm yellow, moving shadows. She heard voices from below, too many for an abandoned station. The door shut. Quinn drew her phone. No signal. Her radio gave one sharp burst of static when she keyed it. She was alone under the old station canopy, with traffic a muffled wash behind her and Herrera on the other side of a locked door. She could wait for backup. That was the sensible choice. Whoever guarded the door might refuse her, but a team could cover the exits, obtain a warrant, make the place answer to a name and an address. Going in alone gave her no such advantage. A thin line of red appeared at the bottom of the door. For an instant she thought it was light. Then it lengthened across the tile and settled into a grout line. Blood. Herrera had not been bleeding when he left the Nest. Not enough for that. Quinn walked to the door and tried the handle. Locked. She struck the panel with the heel of her hand. The slot opened. A narrow face appeared behind it, one grey eye fixed on her. “Closed,” the man said. She held up her warrant card. “Metropolitan Police. Open the door.” The eye dropped to her badge, then to her empty hand. “Token.” “I need to speak to the man who just went in.” “Token.” Behind him someone cried out. The sound was cut short, though not before Quinn heard the raw strain in it. She pictured Herrera’s bloody cuff and the young man entering the Nest. “There’s an injured person in there.” “Then leave us to help them.” The slot shut. Quinn considered forcing the lock. Metal door, frame set into masonry. She had neither the tools nor the time. At her feet, the blood continued its slow passage through the grout. She stepped back into the rain and studied the entrance. To the right, a rusted railing bordered a stairwell choked with rubbish. On the other side of the rail, behind an old advertisement board, she found a maintenance gate held shut with wire. The knot was new. She pulled it loose. The gate gave enough for her to squeeze through sideways. Dark stairs fell away beneath her. Quinn used her phone’s torch and descended, keeping one hand free. Water dripped somewhere below. After twenty steps, the smell changed from wet brick to hot oil, smoke and something medicinally sweet. At the bottom, the passage opened onto a platform bright with lamps. She stopped in the shadow of an arch. Stalls filled the length of the abandoned station. Tarpaulins hung between tiled pillars. Glass bottles, bundles of dried roots and rows of small sealed boxes crowded tabletops. People moved through the aisles in raincoats, evening clothes, hospital scrubs. A woman with silver pins in her hair argued over a jar whose contents struck the glass from inside. Farther along, an old man sold maps from a suitcase, each sheet weighted at the corners with coins. A black sign above a ticket booth read THE VEIL MARKET in flaking gold letters. Beneath it, a board listed prices Quinn couldn’t make sense of. Some were in pounds. Others named favours. The place had electricity, security and customers. It had been operating beneath Camden while her missing-person inquiries sent her through empty buildings all over London. Quinn saw Herrera halfway down the platform. He pushed through a curtain beside a stall stacked with enamel basins. A heavyset woman followed him carrying a canvas medical bag. Quinn moved. She kept to the outer edge of the platform, where the stalls cast deeper shadows. Several people watched her. One man turned his face to the wall as she passed. She wanted to stop him, ask his name, demand to know how long the market had been here. Instead she followed the spot of fresh blood at the base of a pillar. A voice spoke close to her ear. “You have come down without paying.” Quinn turned. The grey-eyed man from the door stood behind a table of bone discs. Each had the same bored hole and hand-cut notch. He was taller than she’d thought, with a leather apron over a dark suit. “Then you know who I am,” she said. “I know what you showed me.” “I’m here for Herrera.” “He came to work.” A shout rose behind the curtain. Herrera’s voice, low and urgent. “Hold him still.” Quinn pushed past the man. He caught her wrist. His fingers closed over the worn leather strap of her watch. “You’ll frighten the sellers,” he said. She looked at his hand until he let go. Beyond the curtain, an alcove had been turned into a treatment room. A young man lay on a table under a bright work lamp. His shirt was cut open. Blood soaked the towels packed against his ribs. Herrera stood beside him with both hands inside the wound, pressing hard, while the woman from the platform worked a needle through torn skin. The patient’s eyes opened. They were dark and frightened. He tried to sit up. “Don’t,” Herrera said. He glanced at Quinn. Surprise crossed his face, then irritation. “If you’re going to arrest me, wait.” Quinn stepped closer. “Is he the man from the bar?” “Yes.” Herrera took a breath. “His name’s Ellis. He was attacked on the way out.” “By whom?” “I didn’t see.” The woman tied off a stitch. “Pressure, Tomás.” Herrera obeyed. His own cuff was soaked because he had held the wound. Quinn could see that now. The patient had a pulse beating visibly in his throat, much too fast. “Why bring him here?” she asked. “There’s an A&E ten minutes from the Nest.” “Because the last one we took to hospital disappeared before morning.” Quinn looked at him. His warm brown eyes held hers. She had heard him give evasive answers before; this wasn’t one. The woman cut another length of thread. Ellis made a broken sound through his teeth. “He needs blood,” Quinn said. “We have it.” Herrera nodded towards a cooler under the table. “He needs me to finish.” Quinn moved aside. Outside the curtain, feet hurried past. The market’s noise had changed. Traders were calling to one another in short, clipped phrases. Metal shutters rattled down somewhere along the platform. The grey-eyed man appeared at the entrance to the alcove. “Herrera. How long?” “Ten minutes.” “You have five.” Quinn stepped into his path. “What’s happening?” He looked beyond her at Ellis, then down the tunnel. “Someone followed you.” “I followed him.” “No,” he said. “Someone followed you.” The lights along the platform went out one by one. In the last spill of yellow, Quinn saw figures running for the stairwells. A shutter crashed between the treatment room and the market. She drew her phone again and hit the emergency call button. The screen showed no service. From the dark tunnel came a sound like a train taking a bend. The rails were brown with rust. Dust trembled on the platform edge. Herrera looked up from the table. “Quinn.” She turned towards him. “Help me move him.” The noise in the tunnel grew louder. Quinn put her phone away, stripped off her coat and took hold of the table’s far end. Ellis cried out when they lifted it. Herrera kept one hand pressed to his ribs as they carried him towards a narrow door at the back of the alcove. Quinn glanced over her shoulder. At the end of the platform, past the falling shutters, two lights appeared in the tunnel. They rode at the height of a train’s headlamps, growing brighter on rails that had not carried a train in years. She tightened her grip and helped Herrera get Ellis through the door.
created_at"2026-09-23T16:26:43.804Z" 9/23/2026, 4:26:43 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2033
moderation_latency(null)
generation_time52789
tokens_prompt888
tokens_completion3284
native_tokens_prompt810
native_tokens_completion2736
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"
usage0.02898
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790180803-IgOJkWKS3Jp12sbta77z"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790180803-flpHkA6S95srVou1Z1J2"
upstream_id"resp_035f3cbc6b71c8ee016ab3fdc3ed2087d1a47314c4fff71957"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_035f3cbc6b71c8ee016ab3fdc3ed2087d1a47314c4fff71957"
is_byokfalse
latency488
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.02898
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
totalTags12
adverbTagCount0
adverbTags(empty)
dialogueSentences46
tagDensity0.261
leniency0.522
rawRatio0
effectiveRatio0
97.74% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount2208
totalAiIsmAdverbs1
found
0
adverb"sharply"
count1
highlights
0"sharply"
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)
88.68% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount2208
totalAiIsms5
found
0
word"tracing"
count1
1
word"measured"
count1
2
word"sense of"
count1
3
word"pulse"
count1
4
word"trembled"
count1
highlights
0"tracing"
1"measured"
2"sense of"
3"pulse"
4"trembled"
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
narrationSentences220
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences220
filterMatches
0"watch"
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences254
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
totalWords2208
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions17
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions81
wordCount2010
uniqueNames13
maxNameDensity1.69
worstName"Quinn"
maxWindowNameDensity4
worstWindowName"Quinn"
discoveredNames
Raven1
Nest5
Harlow1
Quinn34
Herrera27
Wardour1
Street1
Saint1
Christopher1
Morris2
Camden2
London1
Ellis4
persons
0"Raven"
1"Nest"
2"Harlow"
3"Quinn"
4"Herrera"
5"Saint"
6"Christopher"
7"Morris"
8"Ellis"
places
0"Wardour"
1"Street"
2"Camden"
3"London"
globalScore0.654
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences151
glossingSentenceCount2
matches
0"appeared behind it, one grey eye fixed on her"
1"pulse beating visibly in his throat, much"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.453
wordCount2208
matches
0"neither the tools nor"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences254
matches
0"saw that the"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs106
mean20.83
std17.09
cv0.821
sampleLengths
021
133
21
323
457
52
659
725
823
914
1024
117
1258
1324
1445
1537
1616
178
183
193
2039
217
2223
2327
245
2513
2637
2748
2843
2913
3011
3127
3256
3325
3421
359
3643
373
3843
3945
4012
4121
4214
4320
4415
454
4611
4712
4811
491
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences220
matches
0"were plastered"
1"been turned"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount4
totalVerbs347
matches
0"was going"
1"was climbing"
2"was joking"
3"were calling"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences254
ratio0.004
matches
0"She had heard him give evasive answers before; this wasn’t one."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount2015
adjectiveStacks0
stackExamples(empty)
adverbCount41
adverbRatio0.020347394540942927
lyAdverbCount5
lyAdverbRatio0.0024813895781637717
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences254
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences254
mean8.69
std5.37
cv0.617
sampleLengths
021
111
29
313
41
53
617
73
818
912
1014
1113
122
134
149
156
1621
1714
185
1912
207
216
2223
233
243
258
264
278
2812
297
3013
3124
327
3314
3413
3511
3618
3716
383
398
409
4110
424
4314
444
458
464
478
483
493
56.17% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.3464566929133858
totalSentences254
uniqueOpeners88
81.30% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount5
totalSentences205
matches
0"Then he ran."
1"Then he twisted free."
2"Well past midnight."
3"Then it lengthened across the"
4"Instead she followed the spot"
ratio0.024
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount57
totalSentences205
matches
0"He was fast, but he"
1"She took the corner wide,"
2"He vaulted a low chain"
3"Her radio crackled against her"
4"She tried again."
5"His short curls were plastered"
6"He’d smiled politely when she"
7"He’d told her he worked"
8"He reached a bus stop,"
9"She got within arm’s reach"
10"She caught his sleeve."
11"He hissed in pain."
12"He kept running."
13"she heard him tell the"
14"She got the registration."
15"Her phone had one bar"
16"She sent the number and"
17"She looked at the time"
18"She had seen one like"
19"It had a small hole"
ratio0.278
50.24% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount168
totalSentences205
matches
0"The man came out of"
1"Detective Harlow Quinn pushed away"
2"Rain had soaked through the"
3"Tomás Herrera stopped."
4"Quinn crossed the road behind"
5"Herrera cut left into the"
6"He was fast, but he"
7"Whatever he’d taken out of"
8"A woman stepped aside."
9"Herrera slipped past her and"
10"Quinn followed, boots striking wet"
11"She took the corner wide,"
12"He vaulted a low chain"
13"Quinn went around the post"
14"Her radio crackled against her"
15"Static swallowed her."
16"She tried again."
17"The transmission light blinked red,"
18"His short curls were plastered"
19"That bothered her more than"
ratio0.82
97.56% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount4
totalSentences205
matches
0"Even from twenty yards, Quinn"
1"By the time she cleared"
2"Whoever guarded the door might"
3"To the right, a rusted"
ratio0.02
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences95
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags9
fancyCount0
fancyTags(empty)
dialogueSentences46
tagDensity0.196
leniency0.391
rawRatio0
effectiveRatio0
93.5007%