Run: 2026-09-23-01M37PZNZ0969J5BGNE807ASZC

Run Details

Duration:
46.8s
Cost:
$0.059964
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
The rain had been falling since Soho, and by Camden it had stopped pretending to be anything but a flood. Harlow Quinn stood in the doorway of a shuttered phone shop on Chalk Farm Road with water running off the brim of her collar and down the back of her neck, and she watched the man across the street light a cigarette he couldn't keep lit. Short dark curls plastered flat. Olive skin gone sallow under the sodium lamps. A canvas holdall slung across his body, the strap cinched tight, the way you carried something you couldn't afford to lose. Tomás Herrera. Twenty-nine. Former paramedic, struck off eighteen months ago for reasons the General Medical Council's files described as *unauthorised clinical interventions* and then declined to explain. She had read that phrase eleven times. Nobody had been able to tell her what it meant. She had picked him up outside the Raven's Nest two hours ago, under the green wash of its neon sign, when he'd come out through the side door with the holdall and a face like a man walking to his own sentencing. She'd followed his black cab north in her own car, left it on a double yellow on Parkway, and kept thirty metres behind him on foot since then. He was bad at being followed. He checked shop windows too obviously and never once looked up. He gave up on the cigarette, flicked it into the gutter, and started walking. Quinn checked the worn leather watch on her left wrist. 23:47. She pushed off the doorway and went after him. He turned off the main road into a side street that narrowed to a service lane behind the market stalls, all shutters and bins and the sweet rot of wet cardboard. Quinn slowed at the corner. Old habit. Morris had always teased her for it: *You clear corners like you're still in Basra, Harlow.* She had never been to Basra. She had never corrected him. Three years, and she still heard his voice at corners. She stepped into the lane. Herrera was twenty metres ahead, and he had stopped, and he was looking straight back at her. For a second neither of them moved. Rain drummed on the lids of the bins. Somewhere a drainpipe gargled and spat. "Mr Herrera," she called. Her voice came out level. "Detective Inspector Quinn, Metropolitan Police. I'd like a word." He ran. He was fast. Faster than she'd expected from a man who carried himself like his whole spine hurt, but she'd run the Met's fitness test at forty with times that embarrassed the probationers. She went after him with her arms tight and her breath measured, feet slapping through the black puddles. He cut left, through a gap in a chain-link fence where the wire had been peeled back like a tin lid, and she followed without breaking stride. The raw ends of the wire snagged her coat and tore it. They came out onto a stretch of dead ground behind a boarded-up building, brick the colour of old liver, windows bricked in. A railway bridge loomed overhead, and from under it a smell rose that was not rain or rubbish or diesel. It was older than that. Wet stone, a cellar left shut too long, and under it something sharp and chemical that caught the back of her throat like struck matches. Herrera reached the building and dropped to his knees at a steel hatch set into the ground beside the wall. He was fumbling with something at his neck. A chain. A medallion flashed, silver, and he swore in Spanish and tucked it back under his shirt, and his hand went into his jacket pocket instead. "Stop," Quinn said. She was ten metres away. Five. "Tomás. Stop. You're not under arrest. I only want to talk." He looked up at her. His brown eyes were wide and wet, and she was startled to see that he wasn't afraid of *her*. He was afraid *for* her. "Go home, Detective," he said. "Please. You don't want to come down here." Then he pressed something small and pale against the hatch, and the hatch opened. It didn't swing open. It didn't lift on hinges. Quinn would go over this moment later, in the grey hours, and she'd keep coming back to that. The steel simply stopped being in the way. There was a rectangle of dark where it had been, and a flight of tiled steps going down, and a flickering amber light rising from the bottom like the glow off a cooker hob. Herrera went down the stairs two at a time. Quinn reached the edge and stopped. The tiles on the stairwell walls were the old London Underground pattern, cream and oxblood, cracked and furred with black mould. She knew the station maps of this city better than most drivers did, and there had been no working station on this spot for eighty years. A ghost stop. Closed before the war, sealed after it. There should have been nothing down there but rats and asbestos. She could hear voices. Many voices, a low marketplace murmur, and under them something that might have been music played on instruments that were slightly wrong. A bell rang somewhere below, one clear note, and the amber light pulsed with it. Her hand went to her radio. Stopped. What would she say? *Control, I'm in pursuit of a suspect who has entered a disused Tube station through a hatch that dissolved.* She could picture Superintendent Aldous's face. She could picture the referral to Occupational Health, the gentle voice asking how she'd been sleeping since the Morris case, whether she'd taken up the counselling sessions yet. She hadn't. She thought about Morris instead. About the warehouse in Deptford. About the report that said *cardiac event* on a thirty-four-year-old who ran half-marathons, and the bruises on his throat the coroner had called *post-mortem lividity* without quite meeting her eyes. About the smell in that warehouse, which she'd told no one about because she had no words for it. Wet stone. Struck matches. The same smell was coming up these stairs. Quinn's pulse, steady through the whole chase, began to climb. Something lay on the top step, small and white against the grimy tile. She crouched and picked it up. A disc of bone, smooth and warm, as though someone had held it a long time. It was about the size of a fifty-pence piece. There were marks carved into one face that weren't letters in any alphabet she recognised, and when she turned it over the marks seemed to have moved. Herrera had dropped it. Or left it. She thought of his face as he said *please*, and she couldn't decide which. Behind her the rain hissed across the dead ground. Ahead, the voices rose and fell. Her training ran through her head in the flat tones of a Hendon instructor: *Unknown premises. No backup. No comms. No authority to enter. Withdraw, observe, report.* Every rule she had ever built her life on, and she'd built it on rules because rules were what kept you alive when the world stopped making sense. The world had stopped making sense three years ago. The rules had not brought Morris back. She closed her fist around the bone token. It pulsed once against her palm, like a second heartbeat. Quinn stood, straightened her torn coat, and checked her watch again. 23:52. She committed the time to memory the way she would at any scene, because someone would need to know it later, and it might have to be her. Then Detective Inspector Harlow Quinn, eighteen years' decorated service, stepped off the last solid ground she understood and went down into the light.
created_at"2026-09-23T18:03:28.624Z" 9/23/2026, 6:03:28 PM
model"anthropic/claude-opus-5.5-20260921"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency5577
moderation_latency(null)
generation_time46791
tokens_prompt888
tokens_completion2073
native_tokens_prompt1266
native_tokens_completion2745
native_tokens_completion_images(null)
native_tokens_reasoning329
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"
usage0.059964
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790186608-JmMyVjpCL15yGD1ohF09"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790186608-fRFj46a6CoTIq1CV7QG6"
upstream_id"msg_011CfLp2tqPfakbeMTyShvVt"
provider_responses
0
endpoint_id"3a2388bc-3740-4e64-a1f5-4e301726b6b9"
id"msg_011CfLp2tqPfakbeMTyShvVt"
is_byokfalse
latency2161
model_permaslug"anthropic/claude-opus-5.5-20260921"
provider_name"Claude Platform on AWS"
status200
total_cost0.059964
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
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences6
tagDensity0.5
leniency1
rawRatio0
effectiveRatio0
96.14% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1295
totalAiIsmAdverbs1
found
0
adverb"slightly"
count1
highlights
0"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)
76.83% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1295
totalAiIsms6
found
0
word"flicked"
count1
1
word"measured"
count1
2
word"loomed"
count1
3
word"pulsed"
count2
4
word"pulse"
count1
highlights
0"flicked"
1"measured"
2"loomed"
3"pulsed"
4"pulse"
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
emotionTells1
narrationSentences105
matches
0"was afraid"
88.44% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount2
narrationSentences105
filterMatches
0"watch"
hedgeMatches
0"began to"
1"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences108
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen46
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans9
markdownWords51
totalWords1295
ratio0.039
matches
0"unauthorised clinical interventions"
1"You clear corners like you're still in Basra, Harlow."
2"her"
3"for"
4"Control, I'm in pursuit of a suspect who has entered a disused Tube station through a hatch that dissolved."
5"cardiac event"
6"post-mortem lividity"
7"please"
8"Unknown premises. No backup. No comms. No authority to enter. Withdraw, observe, report."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions9
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions47
wordCount1244
uniqueNames29
maxNameDensity0.72
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Soho1
Camden1
Quinn9
Chalk1
Farm1
Road1
Herrera5
General1
Medical1
Council1
Raven1
Nest1
Parkway1
Basra2
Met1
Spanish1
London1
Underground1
Tube1
Superintendent1
Aldous1
Occupational1
Health1
Morris4
Deptford1
Hendon1
Detective1
Inspector1
Harlow3
persons
0"Quinn"
1"Herrera"
2"Council"
3"Met"
4"Aldous"
5"Morris"
6"Harlow"
places
0"Soho"
1"Chalk"
2"Farm"
3"Road"
4"Raven"
5"Basra"
6"Spanish"
7"London"
8"Occupational"
9"Deptford"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences68
glossingSentenceCount1
matches
0"op windows too obviously and never once look"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1295
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount2
totalSentences108
matches
0"read that phrase"
1"see that he"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs37
mean35
std26.78
cv0.765
sampleLengths
020
180
244
387
414
520
665
710
822
921
1018
112
1290
1372
1455
1520
1629
1713
1814
1969
209
216
2268
2341
247
2559
2659
274
288
2910
3071
3121
3270
3316
3418
3540
3623
95.24% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences105
matches
0"being followed"
1"been peeled"
2"was startled"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs204
matches
0"was looking"
1"was fumbling"
2"was coming"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences108
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1252
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.019968051118210862
lyAdverbCount3
lyAdverbRatio0.0023961661341853034
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences108
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences108
mean11.99
std9.79
cv0.817
sampleLengths
020
146
25
38
421
52
61
724
87
910
1042
1128
126
1311
1414
1510
161
179
1831
195
202
2122
225
2310
245
2517
267
278
286
294
305
319
322
333
3430
3518
3627
3712
3822
3920
405
4125
4220
438
442
4525
463
475
481
4911
60.06% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.4339622641509434
totalSentences106
uniqueOpeners46
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences88
matches
0"Somewhere a drainpipe gargled and"
1"Then he pressed something small"
2"Then Detective Inspector Harlow Quinn,"
ratio0.034
60.91% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount35
totalSentences88
matches
0"She had read that phrase"
1"She had picked him up"
2"She'd followed his black cab"
3"He was bad at being"
4"He checked shop windows too"
5"He gave up on the"
6"She pushed off the doorway"
7"He turned off the main"
8"She had never corrected him."
9"She stepped into the lane."
10"Her voice came out level."
11"He was fast."
12"She went after him with"
13"He cut left, through a"
14"They came out onto a"
15"It was older than that."
16"He was fumbling with something"
17"She was ten metres away."
18"He looked up at her."
19"His brown eyes were wide"
ratio0.398
90.68% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount65
totalSentences88
matches
0"The rain had been falling"
1"Harlow Quinn stood in the"
2"Olive skin gone sallow under"
3"A canvas holdall slung across"
4"She had read that phrase"
5"Nobody had been able to"
6"She had picked him up"
7"She'd followed his black cab"
8"He was bad at being"
9"He checked shop windows too"
10"He gave up on the"
11"Quinn checked the worn leather"
12"She pushed off the doorway"
13"He turned off the main"
14"Quinn slowed at the corner."
15"Morris had always teased her"
16"She had never corrected him."
17"She stepped into the lane."
18"Herrera was twenty metres ahead,"
19"Rain drummed on the lids"
ratio0.739
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences88
matches(empty)
ratio0
66.87% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences47
technicalSentenceCount5
matches
0"He turned off the main road into a side street that narrowed to a service lane behind the market stalls, all shutters and bins and the sweet rot of wet cardboar…"
1"Faster than she'd expected from a man who carried himself like his whole spine hurt, but she'd run the Met's fitness test at forty with times that embarrassed t…"
2"Many voices, a low marketplace murmur, and under them something that might have been music played on instruments that were slightly wrong."
3"*Control, I'm in pursuit of a suspect who has entered a disused Tube station through a hatch that dissolved.* She could picture Superintendent Aldous's face."
4"About the report that said *cardiac event* on a thirty-four-year-old who ran half-marathons, and the bruises on his throat the coroner had called *post-mortem l…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount0
fancyTags(empty)
dialogueSentences6
tagDensity0.5
leniency1
rawRatio0
effectiveRatio0
91.1723%