Run: 2026-07-01-01KWE9FKRFCFNACFKCVAB95KR8

Run Details

Duration:
36.5s
Cost:
$0.026318
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="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 down in silver sheets, hammering the pavement of Camden High Street until the gutters ran like small rivers, carrying cigarette ends and flyers toward the drains. Detective Harlow Quinn ran through it with her coat plastered to her shoulders, breath tearing at her throat, her eyes fixed on the man sixty feet ahead of her. Tomás Herrera moved like someone who'd spent years running toward emergencies instead of away from them—economical, low to the ground, cutting corners with the precision of a man who'd once had seconds to decide whether someone lived or died. He'd ducked between two stalled buses on Parkway, vaulted a low wall she'd had to scramble over, and now he was making for the old Tube entrance, the one sealed off since '09 with a chain-link gate and a faded TRANSPORT FOR LONDON sign gone the color of rust. "Herrera!" she shouted, though she knew he wouldn't stop. Eighteen years on the force had taught her the sound of a man who wasn't going to stop. He didn't even look back. He hit the gate at a dead run, and instead of climbing it, he did something with his hand at the padlock—she saw the glint of a key, or maybe not a key at all, maybe just his fingers moving too fast to track in the rain and streetlight—and the chain fell away like it had been waiting for him. Quinn's lungs burned. She was forty-one, not built for this kind of night sprint anymore, but she pushed harder anyway, because something about the way that lock had opened made the hair rise on her arms. She'd seen a lot in eighteen years. She'd learned to recognize the particular chill that came before something she wouldn't be able to explain in a report. She reached the gate seconds after him and shoved through, into the dark mouth of the stairwell beyond. The smell hit her first—damp stone, old electrical wiring, and underneath it something sweeter, like copper and crushed flowers, wrong in a way she couldn't name. Water dripped somewhere in the dark, a slow metronome. She could hear Herrera's footsteps below, descending fast, sure of himself in a way that told her he'd done this before. She thumbed on her torch. The beam caught peeling tile, a faded Underground roundel gone green with mold, and then Herrera's shadow slipping around a bend thirty feet down. "This is a police pursuit," she called, knowing how absurd it sounded down here, in the dark, to nobody. "There's nowhere to go, Tomás." His laugh drifted back up to her, short and without much humor in it. "You'd be surprised, Detective." She followed him down two flights of stairs slick with condensation, her shoes squeaking on tile, until the stairwell opened into what had once been a platform. She remembered this station from before it closed—Camden Town's ghost twin, decommissioned when the tunnels beneath it were declared structurally unsound. Except the platform in front of her didn't look unsound. It looked *occupied*. Strings of amber lantern light hung along the curve of the tunnel, threading between shopfronts built out of old ticket kiosks and shipping pallets and what might once have been a newsagent's stall. There were people—if they were people—moving between the stalls, wrapped in long coats and scarves despite the warmth radiating up from somewhere below, an unnatural warmth that had no business existing in an abandoned Underground station. She smelled roasting meat, and beneath that, the same sweet copper smell from the stairwell, stronger now, cloying. Herrera had stopped at the platform's edge, half-turned back to look at her, rain still dripping from his curls onto his shoulders. The Saint Christopher medallion at his throat caught the lantern light. "You shouldn't be here," he said, and for the first time that night there was no anger in his voice, only something that sounded uncomfortably like pity. "Go home, Detective Quinn." "Not until you tell me what happened to Danny Okafor." She kept her torch trained on him, though it felt suddenly like a child's toy against the strangeness pooling around them. "Not until you tell me why his blood work came back with compounds that don't exist. Not until you explain why three of my witnesses have developed selective amnesia in the last two weeks." Herrera's jaw tightened. "There are things you don't want answers to." "Three years ago I lost my partner in an alley off Brick Lane," Quinn said, and her voice cracked despite herself, despite the eighteen years of training that had taught her to keep her composure through worse than this. "Something happened to Morris that night that I have never been able to explain. Not to my superintendent, not to his widow, not to myself. So don't tell me what I don't want to know. Tell me what's real." Something shifted in Herrera's expression—not quite sympathy, but close enough to it that she recognized the shape of it. Then a woman's voice called his name from somewhere among the stalls, low and urgent, and he turned his head toward it before turning back to Quinn. "You have maybe thirty seconds before that gate up there locks itself again until the next full moon," he said. "The Market doesn't like uninvited guests. It has ways of making that clear that are considerably worse than anything the Met trains you for." Quinn stood at the platform's edge, torch beam trembling very slightly in her grip, rain still running off her coat in thin rivulets onto stone that had absorbed a hundred years of London's underground damp. Behind Herrera, deeper in the tunnel, she could see figures with eyes that caught the lantern light wrong, reflecting it back gold and green like something nocturnal. She could see a stall hung with what looked like small bones strung on silver wire, spinning gently though there was no wind down here to move them. Every instinct honed over eighteen years told her to turn around, climb back up into the rain, file a report that would get quietly buried, and go home to a flat that still had Morris's old case files stacked in boxes she'd never had the courage to open. She thought of Morris's face in that alley three years ago, and the thing she'd seen crouched over him that the coroner's report had never mentioned. She switched off her torch, so as not to mark herself so clearly as an outsider, and stepped down onto the platform.
created_at"2026-07-01T07:32:18.844Z" 7/1/2026, 7:32:18 AM
model"anthropic/claude-sonnet-5-20260630"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency4759
moderation_latency(null)
generation_time36437
tokens_prompt914
tokens_completion1738
native_tokens_prompt1264
native_tokens_completion2379
native_tokens_completion_images(null)
native_tokens_reasoning120
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"
usage0.026318
router(null)
provider_responses
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endpoint_id"37b16f45-eeae-45f3-9b85-2137f7c6d61b"
id"msg_01C5wZEAdKotpvjWSuE7H21k"
is_byokfalse
latency2313
model_permaslug"anthropic/claude-sonnet-5-20260630"
provider_name"Amazon Bedrock"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.17.0; linux; x64))"
http_referer(null)
request_id"req-1782891138-Ew50yUgMpvVvwCxHiKwr"
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api_type"completions"
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upstream_id"msg_01C5wZEAdKotpvjWSuE7H21k"
total_cost0.026318
cache_discount(null)
upstream_inference_cost0
provider_name"Amazon Bedrock"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags7
adverbTagCount0
adverbTags(empty)
dialogueSentences13
tagDensity0.538
leniency1
rawRatio0
effectiveRatio0
81.74% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1095
totalAiIsmAdverbs4
found
0
adverb"suddenly"
count1
1
adverb"very"
count1
2
adverb"slightly"
count1
3
adverb"gently"
count1
highlights
0"suddenly"
1"very"
2"slightly"
3"gently"
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)
77.17% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1095
totalAiIsms5
found
0
word"glint"
count1
1
word"chill"
count1
2
word"footsteps"
count1
3
word"warmth"
count2
highlights
0"glint"
1"chill"
2"footsteps"
3"warmth"
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
narrationSentences42
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences42
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences49
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen62
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords1087
ratio0.001
matches
0"occupied"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions13
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions28
wordCount901
uniqueNames15
maxNameDensity0.78
worstName"Herrera"
maxWindowNameDensity2
worstWindowName"Herrera"
discoveredNames
Camden2
High1
Street1
Harlow1
Quinn5
Herrera7
Parkway1
Tube1
Eighteen1
Underground2
Town1
Saint1
Christopher1
London1
Morris2
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Parkway"
4"Town"
5"Saint"
6"Christopher"
7"Morris"
places
0"Camden"
1"High"
2"Street"
3"Eighteen"
4"London"
globalScore1
windowScore1
11.11% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences36
glossingSentenceCount2
matches
0"not quite sympathy, but close enough to it that she recognized the shape of it"
1"looked like small bones strung on silver"
16.01% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords1.84
wordCount1087
matches
0"not built for this kind of night sprint anymore, but she pushed harder anyway, because something about the way"
1"not quite sympathy, but close enough to it"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences49
matches(empty)
96.69% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs22
mean49.41
std24.13
cv0.488
sampleLengths
057
188
227
365
463
574
629
724
818
961
1087
1133
1231
1365
1411
1578
1646
1744
1890
1948
2026
2122
96.91% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences42
matches
0"were declared"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs145
matches
0"was making"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount0
flaggedSentences6
totalSentences49
ratio0.122
matches
0"Tomás Herrera moved like someone who'd spent years running toward emergencies instead of away from them—economical, low to the ground, cutting corners with the precision of a man who'd once had seconds to decide whether someone lived or died."
1"He hit the gate at a dead run, and instead of climbing it, he did something with his hand at the padlock—she saw the glint of a key, or maybe not a key at all, maybe just his fingers moving too fast to track in the rain and streetlight—and the chain fell away like it had been waiting for him."
2"The smell hit her first—damp stone, old electrical wiring, and underneath it something sweeter, like copper and crushed flowers, wrong in a way she couldn't name."
3"She remembered this station from before it closed—Camden Town's ghost twin, decommissioned when the tunnels beneath it were declared structurally unsound."
4"There were people—if they were people—moving between the stalls, wrapped in long coats and scarves despite the warmth radiating up from somewhere below, an unnatural warmth that had no business existing in an abandoned Underground station."
5"Something shifted in Herrera's expression—not quite sympathy, but close enough to it that she recognized the shape of it."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount273
adjectiveStacks0
stackExamples(empty)
adverbCount9
adverbRatio0.03296703296703297
lyAdverbCount1
lyAdverbRatio0.003663003663003663
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences49
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences49
mean22.18
std13.22
cv0.596
sampleLengths
028
129
239
349
49
518
65
760
83
933
107
1120
1218
1326
149
1521
165
1724
1819
195
2014
214
2227
2321
2410
253
2633
2736
2818
2922
3011
3127
324
3331
3434
353
368
3739
3839
3919
4027
4120
4224
4335
4427
4528
4648
4726
4822
63.27% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.4897959183673469
totalSentences49
uniqueOpeners24
81.30% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences41
matches
0"Then a woman's voice called"
ratio0.024
15.12% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount21
totalSentences41
matches
0"He'd ducked between two stalled"
1"she shouted, though she knew"
2"He didn't even look back."
3"He hit the gate at"
4"She was forty-one, not built"
5"She'd seen a lot in"
6"She'd learned to recognize the"
7"She reached the gate seconds"
8"She could hear Herrera's footsteps"
9"She thumbed on her torch."
10"she called, knowing how absurd"
11"His laugh drifted back up"
12"She followed him down two"
13"She remembered this station from"
14"It looked *occupied*."
15"She smelled roasting meat, and"
16"he said, and for the"
17"She kept her torch trained"
18"She could see a stall"
19"She thought of Morris's face"
ratio0.512
20.98% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount36
totalSentences41
matches
0"Rain came down in silver"
1"Detective Harlow Quinn ran through"
2"Tomás Herrera moved like someone"
3"He'd ducked between two stalled"
4"she shouted, though she knew"
5"He didn't even look back."
6"He hit the gate at"
7"Quinn's lungs burned."
8"She was forty-one, not built"
9"She'd seen a lot in"
10"She'd learned to recognize the"
11"She reached the gate seconds"
12"The smell hit her first—damp"
13"Water dripped somewhere in the"
14"She could hear Herrera's footsteps"
15"She thumbed on her torch."
16"The beam caught peeling tile,"
17"she called, knowing how absurd"
18"His laugh drifted back up"
19"She followed him down two"
ratio0.878
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences41
matches(empty)
ratio0
0.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences28
technicalSentenceCount7
matches
0"Tomás Herrera moved like someone who'd spent years running toward emergencies instead of away from them—economical, low to the ground, cutting corners with the …"
1"She'd learned to recognize the particular chill that came before something she wouldn't be able to explain in a report."
2"She could hear Herrera's footsteps below, descending fast, sure of himself in a way that told her he'd done this before."
3"The beam caught peeling tile, a faded Underground roundel gone green with mold, and then Herrera's shadow slipping around a bend thirty feet down."
4"There were people—if they were people—moving between the stalls, wrapped in long coats and scarves despite the warmth radiating up from somewhere below, an unna…"
5"Quinn stood at the platform's edge, torch beam trembling very slightly in her grip, rain still running off her coat in thin rivulets onto stone that had absorbe…"
6"Behind Herrera, deeper in the tunnel, she could see figures with eyes that caught the lantern light wrong, reflecting it back gold and green like something noct…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount0
matches(empty)
73.08% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount1
fancyTags
0"she shouted (shout)"
dialogueSentences13
tagDensity0.385
leniency0.769
rawRatio0.2
effectiveRatio0.154
74.4453%