Run: 2026-09-23-01M37PG11M4MEN3FSKZPP4H9TC

Run Details

Duration:
1m 1s
Cost:
$0.074544
Provider:
Claude Platform on AWS

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
Rain came sideways off the Regent's Canal and found every gap in Harlow Quinn's collar. She had followed him for forty minutes. She had picked him up under the green neon of the Raven's Nest in Soho, where he'd come out with his hood up and his shoulders hunched, and she had stayed on him down the Northern line, two carriages back, watching his reflection in the black window. Tomás Herrera. Twenty-nine. Struck off the medical register fourteen months ago for reasons the General Medical Council had buried under three pages of redactions. No convictions. No warrants. Nothing she could put a hand on except the fact that his name kept surfacing around people who bled in ways the A&E reports couldn't explain. At Camden Town he'd climbed the escalator two steps at a time. At the top, under the ticket hall's buzzing strip lights, he had turned his head. She hadn't looked away fast enough. Now he was running, and so was she. Camden High Street at half past one on a Tuesday was a smear of shuttered shopfronts and neon bleeding into puddles. A kebab shop threw yellow light across the pavement. Herrera cut through it, trainers slapping, and swerved around a man vomiting quietly into a bin. Quinn went wide and kept her line. Her breath came hard but even. Eighteen years on the job had taught her that most people ran like they'd never have to run again. They burned everything in the first two hundred metres and then they stopped. Herrera didn't stop. He crossed against the lights at the junction and a night bus leaned on its horn, a long, furious bray. Quinn caught a glimpse of the driver's face, white with outrage, and then she was across too, her shoes skidding on the painted lines. "Police!" The word came out ragged. "Tomás! Stop!" He glanced back. For half a second, under a streetlamp, she saw his face clearly: olive skin slick with rain, dark curls plastered flat, his mouth open, gulping air. He didn't look like a man with something to hide. He looked frightened. Not of her, she thought. Of something past her. Then he was gone, around the corner by the lock. She followed him into the market. The stalls were locked down for the night, a maze of corrugated shutters and tarpaulins that snapped and boomed in the wind. The smell of wet cardboard and old frying oil hung everywhere. Water sheeted off awnings in cold ropes. She heard his footsteps ahead, echoing and doubling, so she couldn't tell left from right. Quinn stopped. Listened. Metal rattled. Somewhere to her left, a chain-link fence shivered. She ran for it and came out onto a service road behind the railway arches just in time to see him vault the fence. His jacket snagged at the top. He tore it free with a grunt, dropped, stumbled, and something fell from his pocket and bounced on the tarmac with a small, dry click. He didn't go back for it. Quinn hit the fence, hauled herself up, and felt the wire bite into her palms. She came down hard on the other side, knees jarring. Her hand closed over the thing he'd dropped before she'd consciously decided to pick it up. It was a bone. Small, yellowed, about the size of a domino. Someone had carved it. Under the orange sodium glow she could make out an eye, crudely cut, and a ring of marks around it that weren't quite letters. It was warm. Not body-warm, not pocket-warm. It was warmer than that, as though it had been sitting in the sun, and the rain beaded on it and rolled off without soaking in. She pushed it into her coat and ran on. The service road ended in a dead brick wall, black with a century of soot. Herrera was nowhere. Quinn slowed, chest heaving, and turned in a full circle. Arches, bins, a rusted skip. A door set into the brickwork, half hidden behind a buddleia bush that had punched its way out of the mortar. The door was old, municipal green gone grey, with a faded enamel sign above it. The sign bore the red ring and blue bar of the Underground roundel, but the station name had been scraped off. The padlock hung open on its hasp. Quinn put her back to the wall beside the door and checked her watch out of pure habit. The old leather strap was dark with water. 1:47. She'd been off the clock for five hours. Nobody at the Yard knew she was here. Nobody knew she'd been tailing Herrera for three weeks, building a file in her own spare bedroom because the last time she'd brought something like this to her DCI, he'd looked at her with a kind of careful pity and asked whether she'd been sleeping. She pulled out her phone. One bar. She could call it in. Suspect entered disused railway property, request uniform support. They'd send two probationers in a panda car in twenty minutes, and by then Herrera would be gone and she'd have to explain why she'd been chasing a man who wasn't wanted for anything. She put the phone away. The door swung inward on a breath of air that shouldn't have been there. It was warm and dry and smelled of cloves, hot metal, and something sweet and rotten underneath, like fruit left too long in a bowl. Stairs went down. Old tiled stairs, cream and oxblood, cracked and furred with dust at the edges but worn clean in the middle, as though a great many feet used them often. From far below came a sound. Not a train. Voices. Hundreds of them, layered over each other, a murmur like the sea. Quinn went down. The stairs turned twice. The light changed as she descended, the grey spill from the doorway giving way to something amber and flickering, lanterns or candles, she couldn't tell. The murmur grew. She heard laughter, and haggling, and a thin, high piping that might have been music. Her hand went to the small of her back where her baton sat, and she found that her fingers were not quite steady. Three years ago she had followed Morris down a set of steps like these. Not these, a basement in Deptford, but the same smell had been there. Cloves and rot. She had been six seconds behind him. She had heard him say, very clearly, "Harlow, don't," in a voice she had never heard him use before, and then she had come round the corner into an empty room with his radio lying on the floor, still transmitting. They'd never found him. The inquest recorded an open verdict. She had read the file forty times, and every time the six seconds got longer. At the foot of the stairs the passage opened onto an old platform, and someone was waiting. The figure sat on a stool beside a turnstile that had no business being there, a brass antique polished to a shine. The figure was tall and thin and wrapped in a coat that seemed to be stitched from several other coats. A wide-brimmed hat hid the face. Beyond the turnstile the tunnel mouth glowed. Quinn could see stalls strung along the platform and down onto the tracks, awnings of patched silk and canvas, lanterns in jars, shapes moving between them. Some of the shapes were people. Some of them she wasn't sure about. Halfway down the platform, a curly dark head turned. Herrera. He had stopped by a stall hung with glass bottles. He saw her, and his face went slack with something that looked, to her astonishment, like horror. He shook his head. Once. Small and urgent. *Don't.* The figure on the stool lifted one gloved hand, palm up. "Token," it said. Its voice was soft and pleasant and came from slightly too far away. Quinn's fingers found the bone in her pocket. It was warmer now, almost hot, pulsing faintly against her skin like a second heartbeat. This was the moment, she knew. Everything she'd been since Deptford had been building to it. She could turn around, walk back up those stairs into the rain, and write this down as exhaustion and adrenaline and a woman who had finally gone the way her DCI feared. She could keep her job, her pension, her sanity as the world measured it. Or she could find out what had taken Morris. "Last chance, Detective," Herrera called across the platform. His voice cracked on the title. "Please. You don't know what this place is." "No," Quinn said. "That's rather the point." She laid the bone in the gloved palm. The fingers closed over it. Somewhere beneath the hat, something that might have been a smile moved in the dark. "Welcome to the Market," the figure said, and the turnstile turned.
created_at"2026-09-23T17:54:55.684Z" 9/23/2026, 5:54:55 PM
model"anthropic/claude-opus-5.5-20260921"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency7606
moderation_latency(null)
generation_time60729
tokens_prompt888
tokens_completion2383
native_tokens_prompt1266
native_tokens_completion3474
native_tokens_completion_images(null)
native_tokens_reasoning689
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"end_turn"
service_tier"default"
usage0.074544
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790186095-58XFgU3PXzByvY4riOW7"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790186095-9J3jcoNaKlPHyTeC1esL"
upstream_id"msg_011CfLoP54zFeFdwUUbdMMGz"
provider_responses
0
endpoint_id"3a2388bc-3740-4e64-a1f5-4e301726b6b9"
id"msg_011CfLoP54zFeFdwUUbdMMGz"
is_byokfalse
latency3064
model_permaslug"anthropic/claude-opus-5.5-20260921"
provider_name"Claude Platform on AWS"
status200
total_cost0.074544
cache_discount(null)
upstream_inference_cost0
provider_name"Claude Platform on AWS"
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
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences9
tagDensity0.667
leniency1
rawRatio0
effectiveRatio0
93.28% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1487
totalAiIsmAdverbs2
found
0
adverb"very"
count1
1
adverb"slightly"
count1
highlights
0"very"
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)
86.55% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1487
totalAiIsms4
found
0
word"footsteps"
count1
1
word"echoing"
count1
2
word"silk"
count1
3
word"measured"
count1
highlights
0"footsteps"
1"echoing"
2"silk"
3"measured"
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
narrationSentences130
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences130
filterMatches
0"watch"
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences133
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen47
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords1487
ratio0.001
matches
0"Don't."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions10
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions41
wordCount1461
uniqueNames21
maxNameDensity0.75
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Herrera"
discoveredNames
Regent1
Canal1
Harlow1
Quinn11
Raven1
Nest1
Soho1
Northern1
Herrera8
General1
Medical1
Council1
Camden2
Town1
High1
Street1
Tuesday1
Underground1
Yard1
Morris2
Deptford2
persons
0"Regent"
1"Harlow"
2"Quinn"
3"Raven"
4"Herrera"
5"Council"
6"Morris"
places
0"Soho"
1"Camden"
2"Town"
3"High"
4"Street"
globalScore1
windowScore1
65.73% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences89
glossingSentenceCount3
matches
0"quite letters"
1"something like this to her DCI, he'd looked"
2"coat that seemed to be stitched from several other coats"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.672
wordCount1487
matches
0"Not these, a basement in Deptford, but the same smell had been there"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences133
matches
0"found that her"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs43
mean34.58
std32.07
cv0.927
sampleLengths
015
1108
227
36
48
591
63
744
88
951
1010
1161
123
1310
1455
156
1641
174
1869
199
2090
217
2288
2354
245
2571
2622
273
2870
29102
3017
3194
3237
339
3411
3516
3623
3762
389
3922
407
4128
4211
97.17% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences130
matches
0"was gone"
1"were locked"
2"been scraped"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs243
matches
0"was running"
1"was waiting"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences133
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1466
adjectiveStacks0
stackExamples(empty)
adverbCount44
adverbRatio0.030013642564802184
lyAdverbCount9
lyAdverbRatio0.006139154160982265
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences133
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences133
mean11.18
std9.18
cv0.821
sampleLengths
015
17
247
32
41
521
62
72
826
912
1015
116
128
1321
149
1516
167
176
1819
1913
203
2120
2224
236
242
253
2626
2710
283
295
304
3110
326
3322
3411
357
3615
372
381
392
408
4124
426
4325
446
4515
4610
4716
484
498
59.09% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats17
diversityRatio0.4318181818181818
totalSentences132
uniqueOpeners57
86.96% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences115
matches
0"Then he was gone, around"
1"Somewhere to her left, a"
2"Somewhere beneath the hat, something"
ratio0.026
73.91% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount42
totalSentences115
matches
0"She had followed him for"
1"She had picked him up"
2"She hadn't looked away fast"
3"Her breath came hard but"
4"They burned everything in the"
5"He crossed against the lights"
6"He glanced back."
7"He didn't look like a"
8"He looked frightened."
9"She followed him into the"
10"She heard his footsteps ahead,"
11"She ran for it and"
12"His jacket snagged at the"
13"He tore it free with"
14"He didn't go back for"
15"She came down hard on"
16"Her hand closed over the"
17"It was a bone."
18"It was warm."
19"It was warmer than that,"
ratio0.365
68.70% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount90
totalSentences115
matches
0"Rain came sideways off the"
1"She had followed him for"
2"She had picked him up"
3"Nothing she could put a"
4"She hadn't looked away fast"
5"Camden High Street at half"
6"A kebab shop threw yellow"
7"Herrera cut through it, trainers"
8"Quinn went wide and kept"
9"Her breath came hard but"
10"They burned everything in the"
11"Herrera didn't stop."
12"He crossed against the lights"
13"Quinn caught a glimpse of"
14"The word came out ragged"
15"He glanced back."
16"He didn't look like a"
17"He looked frightened."
18"She followed him into the"
19"The stalls were locked down"
ratio0.783
43.48% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences115
matches
0"Now he was running, and"
ratio0.009
91.84% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences56
technicalSentenceCount4
matches
0"A door set into the brickwork, half hidden behind a buddleia bush that had punched its way out of the mortar."
1"Old tiled stairs, cream and oxblood, cracked and furred with dust at the edges but worn clean in the middle, as though a great many feet used them often."
2"The figure sat on a stool beside a turnstile that had no business being there, a brass antique polished to a shine."
3"He saw her, and his face went slack with something that looked, to her astonishment, like horror."
41.67% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount1
matches
0"the figure said, and the turnstile turned"
50.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount1
fancyTags
0"She had (have)"
dialogueSentences9
tagDensity0.556
leniency1
rawRatio0.2
effectiveRatio0.2
88.6120%