Run: 2026-02-17-01KHMMD5YSFQ822EX268XJB091

Run Details

Duration:
37.1s
Cost:
$0.041862
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 hammered against Detective Quinn's face as she sprinted down the slick pavement, her boots splashing through puddles that reflected the neon signs above. Her quarry was quick – younger, probably fitter – but Quinn had been chasing suspects through London's streets for nearly two decades. She knew these alleys, knew how to pace herself. The figure ahead darted left into a narrow passage between buildings. Quinn's hand instinctively moved to her weapon as she followed, her breathing measured despite the exertion. The passage opened onto Camden High Street, where late-night revelers scattered as the suspect barreled through them. Quinn caught a glimpse of olive skin, a flash of something metallic around his neck. Tomás Herrera. The unlicensed medic she'd been investigating for months. "Police! Stop!" she shouted, more for the benefit of the startled bystanders than any hope of compliance. Her worn leather watch caught the streetlight as she checked the time – 23:47. Something about that detail nagged at her, but she couldn't spare the mental energy to examine why. Herrera veered suddenly, disappearing down the stairs of a defunct Underground station. Quinn pulled up short at the top of the steps, her training warring with her instincts. The station had been closed for years, supposedly due to structural issues. But over the past three years, since Morris's disappearance, she'd heard whispers about this place. The Veil Market, some called it, though she'd never found anyone willing to elaborate on what that meant. "Damn it," she muttered, drawing her weapon and starting down the stairs. The rain grew distant as she descended, replaced by an odd humming that seemed to emanate from the tiles themselves. Her flashlight beam caught the edges of old advertisements, their colors still somehow vibrant despite years of abandonment. The ticket hall was empty, turnstiles frozen in eternal wait. But there was light coming from somewhere deeper in the station – not the harsh fluorescents of Transport for London, but something softer, more organic. Quinn moved carefully, checking corners, trying to ignore the way the air felt thicker down here, almost syrupy against her skin. A movement caught her eye – Herrera, ducking through a maintenance door. As she approached, she noticed something odd about the lock. Instead of the expected keypad or card reader, there was what appeared to be a small ivory dish mounted beside the handle. Quinn had seen enough evidence photos to recognize bone when she saw it. She reached the door just as it was swinging shut, catching it with her free hand. Beyond lay not a maintenance tunnel, but a wide corridor that should have been physically impossible given the station's layout. The walls were lined with stalls, each illuminated by floating orbs of light that cast everything in an amber glow. The Veil Market. It was real. Vendors called out in languages she both recognized and didn't, selling wares that made her eyes hurt to look at directly. A woman with scales instead of skin offered vials of swirling mist. A man whose shadow moved independently of his body haggled over what appeared to be a living book. Quinn spotted Herrera weaving through the crowd ahead, his Saint Christopher medallion glinting. She pushed forward, trying to keep him in sight while processing the impossible scene around her. This was the missing piece – the thread that could finally explain what had happened to Morris. He'd been investigating a series of mysterious deaths, all connected to unauthorized medical procedures. All connected to Herrera. The market curved in ways that defied euclidean geometry. Quinn's training felt inadequate here – what good was standard procedure in a place that shouldn't exist? But she pressed on, watching as Herrera approached what looked like an ordinary bookshelf wedged between two stalls. It reminded her of the one she'd seen at The Raven's Nest during her surveillance of that bar. Herrera pulled a book, and the shelf swung open like a door. He glanced back, meeting Quinn's eyes for just a moment. There was something like pity in his expression. Quinn raised her weapon. "Stop right there, Herrera!" The crowd parted around them, market-goers pressing against the stalls. Herrera stood in the doorway, one hand still on the book. "Detective Quinn," he said, his Spanish accent more pronounced under stress, "you don't want to follow me through here. Go back up to your world of incident reports and evidence bags. Some mysteries aren't meant to be solved." "Morris followed you through a door like that, didn't he?" Quinn took a step forward. "Three years ago. What happened to him?" Herrera's face softened. "He made a choice. Just like you're about to." He stepped through the doorway. "Sometimes the truth is more dangerous than not knowing." Quinn stood at the threshold, weapon trained on the darkness beyond. The market hummed around her, filled with impossible things and people who weren't quite people. Everything she thought she knew about reality was unraveling, but one thing remained clear: behind that door lay answers she'd spent three years searching for. She thought of Morris, of his empty desk and the questions in his case files that had never been answered. She thought of the way his wife still called the station on the anniversary of his disappearance, hoping for news. Quinn took a deep breath and stepped through the doorway, leaving the last remnants of her familiar world behind.
created_at"2026-02-17T01:46:37.614777+00:00" 2/17/2026, 1:46:37 AM
model"anthropic/claude-3.5-sonnet"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency602
moderation_latency135
generation_time36898
tokens_prompt914
tokens_completion1418
native_tokens_prompt917
native_tokens_completion1212
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)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.041862
router(null)
provider_responses
0
id"006474a1-c2c2-45fb-95c3-1707d99f9afd"
status200
is_byokfalse
latency602
endpoint_id"d4fb79bd-9786-4932-af81-b83040e9f4e4"
provider_name"Amazon Bedrock"
model_permaslug"anthropic/claude-3.5-sonnet"
api_type"completions"
id"gen-1771292760-wfkL4pASovnaGEGsdfgR"
upstream_id"006474a1-c2c2-45fb-95c3-1707d99f9afd"
total_cost0.041862
cache_discount(null)
upstream_inference_cost0
provider_name"Amazon Bedrock"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags5
adverbTagCount0
adverbTags(empty)
dialogueSentences8
tagDensity0.625
leniency1
rawRatio0
effectiveRatio0
88.83% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount895
totalAiIsmAdverbs2
found
0
adverb"suddenly"
count1
1
adverb"carefully"
count1
highlights
0"suddenly"
1"carefully"
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)
72.07% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount895
totalAiIsms5
found
0
word"measured"
count1
1
word"glinting"
count1
2
word"standard"
count1
3
word"unraveling"
count1
4
word"familiar"
count1
highlights
0"measured"
1"glinting"
2"standard"
3"unraveling"
4"familiar"
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
narrationSentences60
matches(empty)
23.81% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount4
narrationSentences60
filterMatches
0"watch"
hedgeMatches
0"seemed to"
1"appeared to"
2"happened to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences63
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen38
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords902
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions7
unquotedAttributions0
matches(empty)
65.66% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions43
wordCount830
uniqueNames17
maxNameDensity1.69
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Herrera"
discoveredNames
Detective1
Quinn14
London2
Camden1
High1
Street1
Herrera9
Underground1
Morris3
Veil2
Market2
Transport1
Saint1
Christopher1
Raven1
Nest1
Spanish1
persons
0"Detective"
1"Quinn"
2"Herrera"
3"Morris"
4"Market"
5"Saint"
6"Christopher"
7"Spanish"
places
0"London"
1"Camden"
2"High"
3"Street"
4"Raven"
globalScore0.657
windowScore0.667
0.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences52
glossingSentenceCount4
matches
0"humming that seemed to emanate from the tiles themselves"
1"looked like an ordinary bookshelf wedged"
2"something like pity in his expression"
3"quite people"
0.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords2.217
wordCount902
matches
0"not the harsh fluorescents of Transport for London, but something softer, more organic"
1"not a maintenance tunnel, but a wide corridor"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences63
matches(empty)
89.07% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs21
mean42.95
std19.83
cv0.462
sampleLengths
055
159
210
348
473
550
656
757
856
96
1051
1164
1262
1330
148
1559
1622
1726
1851
1940
2019
87.72% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences60
matches
0"been closed"
1"were lined"
2"been answered"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs149
matches
0"was swinging"
1"was unraveling"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount7
semicolonCount0
flaggedSentences6
totalSentences63
ratio0.095
matches
0"Her quarry was quick – younger, probably fitter – but Quinn had been chasing suspects through London's streets for nearly two decades."
1"Her worn leather watch caught the streetlight as she checked the time – 23:47."
2"But there was light coming from somewhere deeper in the station – not the harsh fluorescents of Transport for London, but something softer, more organic."
3"A movement caught her eye – Herrera, ducking through a maintenance door."
4"This was the missing piece – the thread that could finally explain what had happened to Morris."
5"Quinn's training felt inadequate here – what good was standard procedure in a place that shouldn't exist?"
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount825
adjectiveStacks0
stackExamples(empty)
adverbCount27
adverbRatio0.03272727272727273
lyAdverbCount10
lyAdverbRatio0.012121212121212121
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences63
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences63
mean14.32
std6.43
cv0.449
sampleLengths
024
122
29
311
416
517
615
72
88
917
1014
1117
1212
1316
1412
1515
1618
1712
1820
1918
2010
2125
2221
2312
2410
2522
2613
2716
2820
2920
303
313
3221
3312
3418
3513
3616
3717
3814
394
409
4117
4218
4318
4412
4510
468
474
484
4910
66.67% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.42857142857142855
totalSentences63
uniqueOpeners27
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences59
matches
0"Instead of the expected keypad"
1"All connected to Herrera."
ratio0.034
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount16
totalSentences59
matches
0"Her quarry was quick –"
1"She knew these alleys, knew"
2"she shouted, more for the"
3"Her worn leather watch caught"
4"she muttered, drawing her weapon"
5"Her flashlight beam caught the"
6"She reached the door just"
7"It was real."
8"She pushed forward, trying to"
9"He'd been investigating a series"
10"It reminded her of the"
11"He glanced back, meeting Quinn's"
12"he said, his Spanish accent"
13"He stepped through the doorway"
14"She thought of Morris, of"
15"She thought of the way"
ratio0.271
36.27% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount50
totalSentences59
matches
0"Her quarry was quick –"
1"She knew these alleys, knew"
2"The figure ahead darted left"
3"Quinn's hand instinctively moved to"
4"The passage opened onto Camden"
5"Quinn caught a glimpse of"
6"The unlicensed medic she'd been"
7"she shouted, more for the"
8"Her worn leather watch caught"
9"Something about that detail nagged"
10"Herrera veered suddenly, disappearing down"
11"Quinn pulled up short at"
12"The station had been closed"
13"The Veil Market, some called"
14"she muttered, drawing her weapon"
15"The rain grew distant as"
16"Her flashlight beam caught the"
17"The ticket hall was empty,"
18"Quinn moved carefully, checking corners,"
19"A movement caught her eye"
ratio0.847
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences59
matches(empty)
ratio0
79.37% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences45
technicalSentenceCount4
matches
0"Rain hammered against Detective Quinn's face as she sprinted down the slick pavement, her boots splashing through puddles that reflected the neon signs above."
1"The rain grew distant as she descended, replaced by an odd humming that seemed to emanate from the tiles themselves."
2"Beyond lay not a maintenance tunnel, but a wide corridor that should have been physically impossible given the station's layout."
3"Quinn's training felt inadequate here – what good was standard procedure in a place that shouldn't exist?"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags5
uselessAdditionCount0
matches(empty)
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount2
fancyTags
0"she shouted (shout)"
1"she muttered (mutter)"
dialogueSentences8
tagDensity0.375
leniency0.75
rawRatio0.667
effectiveRatio0.5
73.6488%