Run: 2026-07-25-01KYCPWS4PGJFZRS71R6AP6TM8

Run Details

Duration:
53.3s
Cost:
$0.077150
Provider:
Amazon Bedrock

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="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <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> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. 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 call had come in at 4:12 a.m., which was the hour Quinn trusted least. Anything before three was still last night's business. Anything after five belonged to the milk vans and the bakers. But 4:12 was the dead middle of nowhere, and in eighteen years she'd learned that nowhere was where the strange things happened. She came down the service stairs at the old Camden Road platform with her torch low, because the emergency lighting the response team had rigged was doing that thing bad lighting does — it lit the floor and the ceiling and left everything at eye level in a kind of brown fog. The air smelled of rust and wet chalk. Below her, somebody's radio crackled and cut out. "Morning, guv," said PC Adeyemi at the bottom, holding the tape aside. He looked green under the work lamps. "Watch the third step from the bottom, it's gone soft." "How long's this station been shut?" "Nineteen-sixteen, apparently. Sealed in the seventies. Nobody's got a key that works." Quinn stopped with one hand on the rail. "Then how'd we get in?" "Door was open, guv." "Open how?" Adeyemi hesitated. "Open like it was never shut." She logged that, the way she logged everything, in the small tidy filing cabinet at the back of her skull, and went down. The platform was longer than she expected and curved away into black at both ends. Old tiles, cream and oxblood, half of them fallen. Advertisements from another century, ghosted down to their bones: a woman's gloved hand, the word RELIABLE, a shoe. Somebody had swept the platform. That was the first wrong thing. Not swept recently — swept a long time ago and kept swept, the dust pushed into neat berms along the tunnel wall the way a man sweeps a shop floor at the end of a shift, over and over, for years. The body lay eleven feet from the platform edge, on its back, arms at its sides. DI Marcus Pell was crouched beside it with his coat pooled on the concrete, which told her he didn't care about the coat, which told her he'd already decided what this was. "Harlow." He didn't get up. "You look like you slept." "I did. Two hours, sitting up. What have we got?" "Male, mid-forties, no wallet, no phone, no keys. Blunt force to the back of the skull, one blow, hard. Somebody brought him down here, hit him, and left." Pell straightened, knees cracking. "You want my read? He came down to buy something he shouldn't. Rough sleepers, dealers, that scene. There's a whole economy in these dead stations. Kid told me last year there's a fella sells stolen bikes out of a ventilation shaft at Aldwych. Deal went bad, someone panicked, done." Quinn crouched where he had been. She took her time. That was the whole of her method, if she was honest, and she never was, not in front of Pell: she took her time and let the scene talk before she asked it any questions. The man wore a wool overcoat, good quality, twenty years out of fashion. His shoes were dress shoes, polished, worn down evenly at both heels. Hands soft, nails clean, one callus on the middle finger of the right hand where a pen sits. His face had the settled look of a man who'd been about to explain something. "No defensive wounds," she said. "Never saw it coming." "Mm." She lifted the near hand with two gloved fingers. The sleeve rode up. The wrist was unmarked. "Where's his watch?" "No watch." "There's a watch." She turned the arm slightly into the light. A pale band of skin, two inches wide, on a wrist otherwise the same dull colour as the rest of him. "He wore one every day for years. Somebody took it. But they left the coat, which is worth more, and they left" — she opened the coat with the back of her hand — "a signet ring, gold, on his little finger. You panic-rob a man, you don't sit down and select. You take the ring. It's right there." Pell shifted his weight. "Watch might have been engraved. Traceable." "Then so's the ring." "Harlow." "I'm not arguing, I'm counting." She sat back on her heels. "Keep going. The blow's to the back of the skull. He's on his back, arms at his sides, feet together. If you hit a man from behind and he drops, he goes forward. Face down, arms out, one knee up. He doesn't lie down like he's being measured for a coffin." "So they turned him over." "Why?" "To check he was dead. To go through his pockets." "Then his coat would be twisted. Look at it." She traced the air an inch above the wool. "Hem's straight. Lapels are flat. His collar's not even rucked. Somebody rolled him, straightened his limbs, arranged his coat, and closed his eyes." She paused. "Somebody who was sorry." Pell said nothing for a moment. Then, quieter: "Or somebody performing sorry, for our benefit." She almost smiled. He wasn't stupid, Pell. He was just tired in a way that had gone structural, and tired men prefer explanations that let them go home. "Second thing," she said, standing. "Where's the blood?" The concrete under the man's head was dry. Not scrubbed — Quinn had seen scrubbed, scrubbed leaves a halo, a ghost of clean in the dirt. This was ordinary grey floor with ordinary grime, and a dead man with a broken skull lying on it. "Killed elsewhere," Pell said. "Dumped here." "Down two flights of stairs and a soft third step, carrying a fifteen-stone man, without touching either wall. Look at the dust on the tiles. There's no smear. No drag marks. No shoeprints but ours and the response team's." She turned her torch on the platform floor and swept it in a slow arc, and the two of them looked at the swept concrete and the neat berms of dust and the absolute absence of any indication that a single living person had ever walked there. "That's not possible," Pell said. "No," Quinn agreed. "It isn't." She walked to the platform edge and shone the torch down into the trackbed. No rails; they'd been lifted decades ago, leaving two long grooves of ballast and a rat's nest of cable. And there, in the dust of the trackbed, so faint she had to crouch and change her angle twice: a track. Not footprints. A single line, smooth, about four inches wide, running from beneath the dead man's position out along the tunnel and into the dark, like something had been dragged. Or like something had trailed behind whoever had walked out. "Marcus. Come and look at this." He came, and he looked, and she watched his eyes find the line and slide off it again. "Cable. They pulled cable out." "There's cable right there, still in place." "Then a bag. A holdall." "Sure," she said, and let it go, because there was no percentage in it and because she had already stopped talking to him. She went back to the body and got down on the floor beside it, cheek almost to the concrete, and looked at the man's face from three inches away. His eyes were closed. His mouth was slightly open. And on his tongue, dry and grey as a communion wafer, lay a small flat disc of bone the size of a five-pence piece, scored on one face with a mark like a stitched wound. Quinn's stomach went cold, and not from the floor. She had seen that shape once before, three years ago, in a photograph she had never been permitted to enter into evidence, taken at a scene where DS Michael Morris had gone in through a door and had never come back out of it. She'd been told, at the time, that the door led to a plant room. She'd been shown the plant room. She'd measured it. It was two feet too shallow. "Guv?" Adeyemi, from the stairs. "There's a woman up top asking to speak to you. Says she's not press. Red hair, glasses, got a bag full of books. Says she knows what the token means." Quinn stayed where she was for a count of five, looking at the little bone coin, feeling eighteen years of decorated service tilt under her like the soft third step. Then she stood, brushed the dust from her knees, and touched the worn leather strap of the watch on her left wrist, once, the way she always did. "Marcus," she said. "Nobody touches that man's mouth. Nobody. And get me the sealing records for this station going back to 1916. All of them." "Harlow, it's a mugging." "It's a delivery," she said, and went up into the grey beginnings of the morning to meet the woman with the books.
created_at"2026-07-25T13:19:36.604Z" 7/25/2026, 1:19:36 PM
model"anthropic/claude-opus-5-20260723"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2083
moderation_latency(null)
generation_time53215
tokens_prompt896
tokens_completion2074
native_tokens_prompt1285
native_tokens_completion2829
native_tokens_completion_images(null)
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"end_turn"
service_tier"default"
usage0.07715
router(null)
provider_responses
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endpoint_id"76cb4608-f48c-483d-8da8-9957fb44244e"
id"msg_011CdNqrT9aUpLAHzDwk3ni6"
is_byokfalse
latency2083
model_permaslug"anthropic/claude-opus-5-20260723"
provider_name"Amazon Bedrock"
status200
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request_id"req-1784985576-9UsokYldl3ze445jGABx"
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api_type"completions"
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upstream_id"msg_011CdNqrT9aUpLAHzDwk3ni6"
total_cost0.07715
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upstream_inference_cost0
provider_name"Amazon Bedrock"
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data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags18
adverbTagCount1
adverbTags
0"She sat back [back]"
dialogueSentences51
tagDensity0.353
leniency0.706
rawRatio0.056
effectiveRatio0.039
93.24% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1480
totalAiIsmAdverbs2
found
0
adverb"slightly"
count2
highlights
0"slightly"
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Marcus"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
83.11% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1480
totalAiIsms5
found
0
word"weight"
count1
1
word"measured"
count2
2
word"traced"
count1
3
word"stomach"
count1
highlights
0"weight"
1"measured"
2"traced"
3"stomach"
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
narrationSentences76
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences76
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences107
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen88
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1485
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions16
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions23
wordCount1015
uniqueNames8
maxNameDensity0.79
worstName"Pell"
maxWindowNameDensity2.5
worstWindowName"Pell"
discoveredNames
Quinn7
Camden1
Road1
Adeyemi3
Marcus1
Pell8
Michael1
Morris1
persons
0"Quinn"
1"Adeyemi"
2"Marcus"
3"Pell"
4"Michael"
5"Morris"
places
0"Camden"
1"Road"
globalScore1
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences53
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.673
wordCount1485
matches
0"No shoeprints but"
73.21% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount3
totalSentences107
matches
0"doing that thing"
1"logged that, the"
2"seen that shape"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs55
mean27
std26.83
cv0.994
sampleLengths
056
168
229
36
412
513
64
72
88
923
1094
1116
1232
1310
1410
1581
1645
1758
185
194
2021
212
2291
2310
244
251
2662
275
281
2910
3047
3115
3228
338
3445
356
3686
375
385
3994
406
4123
427
435
4423
4529
4644
479
4873
4935
77.56% Passive voice overuse
Target: ≤2% passive sentences
passiveCount6
totalSentences76
matches
0"was crouched"
1"been lifted"
2"been dragged"
3"been permitted"
4"been told"
5"been shown"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs161
matches
0"was doing"
36.05% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount1
flaggedSentences4
totalSentences107
ratio0.037
matches
0"She came down the service stairs at the old Camden Road platform with her torch low, because the emergency lighting the response team had rigged was doing that thing bad lighting does — it lit the floor and the ceiling and left everything at eye level in a kind of brown fog."
1"Not swept recently — swept a long time ago and kept swept, the dust pushed into neat berms along the tunnel wall the way a man sweeps a shop floor at the end of a shift, over and over, for years."
2"Not scrubbed — Quinn had seen scrubbed, scrubbed leaves a halo, a ghost of clean in the dirt."
3"No rails; they'd been lifted decades ago, leaving two long grooves of ballast and a rat's nest of cable."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1013
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.024679170779861797
lyAdverbCount4
lyAdverbRatio0.003948667324777887
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences107
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences107
mean13.88
std14.16
cv1.02
sampleLengths
015
18
211
322
452
58
68
712
87
910
106
1112
128
135
144
152
162
176
1823
1915
209
2118
225
236
2441
2516
2632
275
285
2910
3032
3149
326
334
3435
3513
3612
3718
3815
395
404
4110
424
434
443
452
4611
4721
4859
494
74.45% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.48598130841121495
totalSentences107
uniqueOpeners52
49.75% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences67
matches
0"Then she stood, brushed the"
ratio0.015
46.87% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences67
matches
0"She came down the service"
1"He looked green under the"
2"She logged that, the way"
3"He didn't get up"
4"She took her time."
5"His shoes were dress shoes,"
6"His face had the settled"
7"She lifted the near hand"
8"She turned the arm slightly"
9"she opened the coat with"
10"She sat back on her"
11"She traced the air an"
12"She almost smiled."
13"He wasn't stupid, Pell."
14"He was just tired in"
15"she said, standing"
16"She turned her torch on"
17"She walked to the platform"
18"He came, and he looked,"
19"she said, and let it"
ratio0.433
49.55% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount55
totalSentences67
matches
0"The call had come in"
1"Anything before three was still"
2"Anything after five belonged to"
3"She came down the service"
4"The air smelled of rust"
5"He looked green under the"
6"Quinn stopped with one hand"
7"She logged that, the way"
8"The platform was longer than"
9"Advertisements from another century, ghosted"
10"Somebody had swept the platform."
11"That was the first wrong"
12"The body lay eleven feet"
13"He didn't get up"
14"Pell straightened, knees cracking"
15"Quinn crouched where he had"
16"She took her time."
17"That was the whole of"
18"The man wore a wool"
19"His shoes were dress shoes,"
ratio0.821
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences67
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences31
technicalSentenceCount1
matches
0"He was just tired in a way that had gone structural, and tired men prefer explanations that let them go home."
97.22% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags18
uselessAdditionCount1
matches
0"Pell straightened, knees cracking"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags9
fancyCount1
fancyTags
0"Quinn agreed (agree)"
dialogueSentences51
tagDensity0.176
leniency0.353
rawRatio0.111
effectiveRatio0.039
84.8117%