Run: 2026-09-23-01M37HX050Q5E2B2HTMPGHS5ZF

Run Details

Duration:
45.1s
Cost:
$0.023950
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
Tomás Herrera came out of the side door of The Raven’s Nest carrying a black medical bag and looking over his shoulder. Detective Harlow Quinn watched from the opposite pavement. Rain slid off the bar’s green neon sign and broke against the kerb. Through the front window she could see old maps on the walls, black-and-white photographs, a woman laughing into a glass. Herrera had spent forty minutes inside. He had gone in empty-handed. He turned north and walked fast. Quinn waited until a delivery van passed, then crossed behind it. At the corner, Herrera stopped beneath a dead streetlamp. For a moment she thought he’d made her. He fished something from his pocket instead: a pale disc no bigger than a pound coin. He rubbed it between his fingers, put it away, and started walking again. Quinn followed him through Soho’s late-night crowds to Tottenham Court Road. She had two uniformed officers in a car three streets over and grounds enough to stop him. A man matching Herrera’s description had been seen at a burglary scene in Bloomsbury that afternoon, where an antique dealer had been found unconscious in a locked room. The dealer’s stock was untouched. His ledgers were gone. She wanted to know where Herrera was taking them. He went down to the Northern line. Quinn bought a ticket at the machine while he passed through the barriers, then caught sight of his dark curls on the escalator below. On the platform, he stood well back from the edge, one hand pressed against his bag. At Camden Town, he got off. Quinn let two passengers step between them. By the time she reached the street, he was halfway across the road. A bus forced her to wait. Its windows, bright with passengers, crawled past her face. When it cleared, Herrera was running. “Police! Stop!” He glanced back once and cut between a minicab and a line of parked scooters. Quinn ran after him. Rain needled her eyes. Her shoes struck water pooled around the paving slabs, and her coat dragged at her knees. Herrera had the advantage of ten years and a head start. She had spent eighteen years learning what people did when they ran: the instinctive turn toward home, the bad choice at a blind corner, the glance that told her exactly where they meant to go. He was aiming east, away from the crowded high street. “Control, this is Quinn.” She keyed her radio as she ran. “Pursuing one male on foot from Camden Town station. Herrera, Tomás. Dark jacket, black medical bag. Heading toward Kentish Town Road.” Static crackled. A dispatcher asked her to repeat her location. Quinn did, but the end of the transmission vanished beneath the squeal of brakes. Herrera had darted across a junction against the light. A cyclist swore and swerved around him. Quinn crossed behind a taxi, slapped a palm on its wet bonnet when the driver leaned on the horn, and kept going. He took a narrow lane she wouldn’t have noticed from the road. Brick walls hemmed it in, tagged and glossy with rain. Bins crowded one side. At the far end stood a chain-link gate, padlocked to a fence. Herrera didn’t slow. He turned sharply before the gate and disappeared behind a skip. Quinn reached it three seconds later. Beyond the skip, steps dropped into darkness. An old Underground roundel, stripped of its name, hung crooked above them. She drew her torch. “Herrera.” Something clattered below. She started down. The first flight ended at a metal security door propped open with a brick. Fresh scratches marked the paint around the lock. Past it lay a service corridor lined with pipes. Water ticked from a joint overhead. Herrera’s footsteps ran ahead of her, quick and uneven. Quinn took the brick and shoved the door wider. It scraped across concrete, loud enough to warn him. There was no help for that. She would not let a door close at her back. At the end of the corridor, Herrera appeared under a bare bulb. His olive face shone with rain and sweat. He had stopped at a tiled archway, where a broad man in a long coat blocked his path. Herrera held up the pale disc. The man looked at it, then at Quinn. Herrera said something she couldn’t hear. The man moved aside. “Herrera!” Quinn raised her warrant card. “Met Police. Stay where you are.” Herrera’s expression changed—not surprise, as she’d expected, but dismay. He ducked through the arch. The broad man stepped into the middle of it. Quinn kept coming. “Move.” “Market’s closed to you,” he said. Up close, she saw that the coat was made of heavy canvas and that he wore gloves despite the mild night. His face was battered, his nose crooked. He looked past her at the empty corridor, counting the officers who weren’t there. She could arrest him for obstruction. She could call for backup. She could also watch Herrera disappear. Quinn took one step to his left. The man shifted with her. She drove her shoulder into his chest before he had settled his weight, caught his wrist when he grabbed for her coat, and twisted it behind him. He hit the tiled wall with a grunt. “Don’t,” she said. His other hand opened. A thin blade fell and rang against the floor. Quinn backed through the arch, leaving him bent over. She heard him curse behind her, then call out a name. The passage beyond opened onto an abandoned platform beneath a high, soot-dark ceiling. No trains ran on the tracks. Stalls lined both sides of them, built from packing crates, folding tables, lengths of railway shelving. Lamps burned in glass jars. Voices filled the station: bargaining, laughter, a child crying somewhere out of sight. Quinn stopped. She had expected a squat, perhaps a deal in some forgotten piece of Tube property. She had not expected a crowd. A woman in a fur coat held a tiny brass cage up to the light. Something inside struck the bars with the sound of fingernails on a window. At the next stall, rows of stoppered bottles glowed dull red beneath handwritten labels Quinn couldn’t read. A seller swept a cloth over them when he saw her warrant card. Herrera was thirty yards away, forcing a path through the crowd. “Police!” Quinn shouted. “Clear the way.” Heads turned. No one moved aside. She pocketed the warrant card. A mistake, showing it here. She pushed between a man carrying bundles of dried roots and a woman whose umbrella dripped black water. The woman caught Quinn’s sleeve. “You need a token,” she said. Quinn pulled free. “Then complain to management.” The woman stared at her as if she’d said something dangerously stupid. Herrera glanced back from the far end of the platform. Under the lamps, Quinn could see blood on his hand. He pressed it against the medical bag, trying to conceal the stain, and vanished down a second stairway. Quinn followed until a sharp voice behind her said, “He hasn’t stolen anything from you.” A young man stood at a stall of old photographs. He held one between thumb and forefinger, ready to hand it to a customer. Quinn glimpsed the face in it and nearly collided with the table. Morris. Not a resemblance. Morris in his cheap wedding suit, the same crooked smile he’d worn in the photograph on his desk. He had died three years ago. Quinn had seen what they brought out of the river. She seized the edge of the table. “Where did you get that?” The young man turned the photograph facedown. “You want to buy?” “Answer me.” He looked toward the archway. The man in the canvas coat had come through it. Two others stood beside him now. Quinn checked her radio. The display was dark. She thumbed the power button; nothing happened. She could remember charging it in the car. The young man slid the photograph into a drawer. “Go back upstairs, detective.” A cry rose from below the platform, brief and raw. It cut through the market noise. Quinn looked toward the stairway where Herrera had gone. He was a former paramedic with a medical bag and blood on his hand. Someone down there might be hurt. He might be the one hurting them. Either way, she could not stand at a stall arguing over a photograph. The man in the coat started toward her. Quinn left the table and ran for the stairs. Halfway down, she heard the crowd close behind her. A gate rattled above; someone was pulling it across the stairhead. She cleared the last steps and came into a tiled passage, lit by a single work lamp on the floor. Herrera stood at an open door ten feet away. Blood ran along the scar on his left forearm. His Saint Christopher medallion had slipped out over his collar. He stared at Quinn, breathing hard. “You shouldn’t be here,” he said. “You’re coming with me.” “Not yet.” He stepped back from the door. Through it Quinn saw a person on a narrow cot, covered to the chest with a grey blanket. A woman knelt beside the cot, pressing both hands to a wound Quinn could not see. Blood had soaked through the blanket and was dripping steadily onto the floor. Herrera opened his bag. Above them, the gate slammed shut. Quinn looked at the blood, then at Herrera. He pulled out a pair of gloves with shaking hands. Whatever had happened in the dealer’s locked room, whatever these people sold beneath Camden, the person on the cot had minutes. She went through the door and took the other side of the bed. “Tell me where to press,” she said.
created_at"2026-09-23T16:34:37.865Z" 9/23/2026, 4:34:37 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency7510
moderation_latency(null)
generation_time45099
tokens_prompt888
tokens_completion2401
native_tokens_prompt810
native_tokens_completion2233
native_tokens_completion_images0
native_tokens_reasoning203
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"
usage0.02395
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790181277-5eQ9OTfrU5s2HldzQjRm"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790181277-D2EDz9QnzFAfycdCnJXi"
upstream_id"resp_0dd1df224cdfc2e9016ab3ff9dfd3087d1830dcc5f65e443d6"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_0dd1df224cdfc2e9016ab3ff9dfd3087d1830dcc5f65e443d6"
is_byokfalse
latency1212
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.02395
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
totalTags9
adverbTagCount0
adverbTags(empty)
dialogueSentences22
tagDensity0.409
leniency0.818
rawRatio0
effectiveRatio0
96.93% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1628
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)
93.86% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1628
totalAiIsms2
found
0
word"footsteps"
count1
1
word"weight"
count1
highlights
0"footsteps"
1"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
narrationSentences163
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences163
filterMatches(empty)
hedgeMatches
0"started to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences176
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen35
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1627
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions70
wordCount1538
uniqueNames19
maxNameDensity2.02
worstName"Quinn"
maxWindowNameDensity4
worstWindowName"Quinn"
discoveredNames
Herrera21
Raven1
Nest1
Harlow1
Quinn31
Soho1
Tottenham1
Court1
Road1
Bloomsbury1
Northern1
Camden2
Town1
Static1
Underground1
Tube1
Heads1
Saint1
Christopher1
persons
0"Herrera"
1"Raven"
2"Nest"
3"Harlow"
4"Quinn"
5"Static"
6"Heads"
7"Saint"
8"Christopher"
places
0"Soho"
1"Tottenham"
2"Court"
3"Road"
4"Bloomsbury"
5"Northern"
6"Camden"
7"Town"
globalScore0.492
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences125
glossingSentenceCount1
matches
0"appeared under a bare bulb"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.615
wordCount1627
matches
0"not surprise, as she’d expected, but dismay"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences176
matches
0"saw that the"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs72
mean22.6
std18.27
cv0.808
sampleLengths
022
152
217
346
465
59
647
76
841
92
1015
1170
1210
1332
1424
1538
1638
1714
1825
194
201
216
2246
2334
2438
256
2618
2712
2823
294
306
3142
3217
3347
343
3513
3620
3753
3823
3958
4011
416
426
4333
446
457
4612
4738
4815
4936
96.65% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences163
matches
0"been seen"
1"been found"
2"were gone"
3"was made"
4"was battered"
78.79% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs275
matches
0"was taking"
1"was running"
2"was aiming"
3"was pulling"
4"was dripping"
94.16% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount2
flaggedSentences3
totalSentences176
ratio0.017
matches
0"Herrera’s expression changed—not surprise, as she’d expected, but dismay."
1"She thumbed the power button; nothing happened."
2"A gate rattled above; someone was pulling it across the stairhead."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1545
adjectiveStacks0
stackExamples(empty)
adverbCount32
adverbRatio0.020711974110032363
lyAdverbCount5
lyAdverbRatio0.003236245954692557
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences176
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences176
mean9.24
std5.61
cv0.607
sampleLengths
022
18
213
320
46
55
66
711
89
98
1016
1113
1211
1317
1428
155
164
179
187
1924
2016
216
227
2313
246
259
266
272
2815
294
304
3116
3211
3335
3410
3511
3621
372
388
3914
409
417
4222
4312
4410
454
4612
473
4811
496
51.89% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.3352272727272727
totalSentences176
uniqueOpeners59
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences153
matches(empty)
ratio0
84.05% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount52
totalSentences153
matches
0"He had gone in empty-handed."
1"He turned north and walked"
2"He fished something from his"
3"He rubbed it between his"
4"She had two uniformed officers"
5"His ledgers were gone."
6"She wanted to know where"
7"He went down to the"
8"Its windows, bright with passengers,"
9"He glanced back once and"
10"Her shoes struck water pooled"
11"She had spent eighteen years"
12"He was aiming east, away"
13"She keyed her radio as"
14"He took a narrow lane"
15"He turned sharply before the"
16"She drew her torch."
17"She started down."
18"It scraped across concrete, loud"
19"She would not let a"
ratio0.34
35.16% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount130
totalSentences153
matches
0"Tomás Herrera came out of"
1"Detective Harlow Quinn watched from"
2"Rain slid off the bar’s"
3"Herrera had spent forty minutes"
4"He had gone in empty-handed."
5"He turned north and walked"
6"Quinn waited until a delivery"
7"He fished something from his"
8"He rubbed it between his"
9"Quinn followed him through Soho’s"
10"She had two uniformed officers"
11"A man matching Herrera’s description"
12"The dealer’s stock was untouched."
13"His ledgers were gone."
14"She wanted to know where"
15"He went down to the"
16"Quinn bought a ticket at"
17"Quinn let two passengers step"
18"A bus forced her to"
19"Its windows, bright with passengers,"
ratio0.85
65.36% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences153
matches
0"By the time she reached"
1"Either way, she could not"
ratio0.013
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences65
technicalSentenceCount2
matches
0"Tomás Herrera came out of the side door of The Raven’s Nest carrying a black medical bag and looking over his shoulder."
1"She had spent eighteen years learning what people did when they ran: the instinctive turn toward home, the bad choice at a blind corner, the glance that told he…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount0
matches(empty)
59.09% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags7
fancyCount2
fancyTags
0"Quinn shouted (shout)"
1"Quinn followed (follow)"
dialogueSentences22
tagDensity0.318
leniency0.636
rawRatio0.286
effectiveRatio0.182
86.3092%