Run: 2026-07-01-01KWEAC9ZTWEBZ05D7ARRJ3CYK

Run Details

Duration:
36.2s
Cost:
$0.024948
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
The rain came down in needles, sharp and cold, needling through Harlow Quinn's coat as she rounded the corner onto Chalk Farm Road at a dead sprint. Ahead of her, a shape in a dark hoodie cut between two parked cars, vaulted a low wall with an ease that struck her as wrong—too fluid, too fast for a man his size—and vanished into the alley behind a shuttered chip shop. "Stop! Police!" Her voice cracked against the wet brick and came back to her, thin and useless. Eighteen years on the force and she still said it, still believed for half a second that the words carried weight enough to stop a man from running. He didn't stop. He never did, the good ones. Quinn's boots hit standing water and she didn't slow, didn't think about the ache already blooming in her knee, just kept her eyes fixed on the retreating blur of him. Marcus Webb. Petty thief, sometimes police informant, a man she'd hauled in twice for receiving stolen goods and once, memorably, for possession of a substance that hadn't shown up on any toxicology database in existence. That last one should have told her something. It had, eventually. It was why she was out here at half past eleven on a Tuesday night instead of home with a glass of wine and the telly, chasing a low-level nobody through the rain like her career depended on it. Maybe it did. Maybe more than her career. She'd pulled his name from a witness statement connected to a break-in at a private members' club in Mayfair—nothing stolen, nothing damaged, but a smell reported by the cleaning staff the next morning like "burnt hair and church candles," and a security guard who swore blind he'd seen the intruder walk through a locked door without opening it. She'd laughed at that in the briefing. She wasn't laughing now. Webb hit the end of the alley and didn't slow for the fence. He went up it like it wasn't there, like gravity was a suggestion he'd decided to ignore, and dropped down the other side into the old railway cutting that ran behind Camden. Quinn swore under her breath and followed, her hands raw against the wet chain-link, her jacket catching and tearing on the top wire. She landed hard, jarred her teeth, kept moving. The rain was worse down here, funneled between the brick embankments, and the streetlight orange had given way to a deeper dark, broken only by the phone in her pocket, which she didn't dare stop to check. Somewhere three years ago, in a night that had looked a great deal like this one, she'd lost sight of Morris for eleven minutes. Eleven minutes was all it had taken. She'd found what was left of him in a stairwell that smelled the same way that Mayfair club had smelled, and the official report had called it an animal attack, and she had signed her name to that report because there had been nothing else true enough to say. She was not going to lose sight of this one. Webb ducked through a gap in the hoarding where the old Tube entrance had been bricked up and then, evidently, un-bricked by someone with more patience than the council. Quinn slowed at the mouth of it, breath ragged, rain running down the back of her collar. There were disused stations all over London, mothballed relics of lines rerouted decades ago, and she knew, in the dim procedural part of her brain that was still functioning, that going in there alone, off the books, with no radio call logged, was the kind of decision that got written up in inquiries. The kind of decision that got detectives killed, or worse, got them found six months later with no explanation anyone could stomach putting in a file. She went in anyway. The tunnel beyond the hoarding sloped down into old brick and older dark, and the sound of the rain fell away behind her, replaced by something stranger: a low murmur of voices, layered and strange, threading up from somewhere beneath her feet. Light bled up the stairwell ahead, not electric light, something warmer and unsteadier, the color of candle flame or worse. She could smell woodsmoke, and beneath it something like copper, and beneath that something floral and rotten she couldn't place at all. Quinn stood at the top of a set of stairs that shouldn't have existed on any Transport for London schematic she'd ever pulled, and looked down into a platform lit by hanging lanterns and strings of bulbs strung between iron pillars, and rows of stalls stretching away into the dark further than the tunnel had any right to go. There were people down there—if they were people—moving between the stalls with unhurried purpose, examining jars and bundled herbs and things that glittered wrong in the lantern light. She heard a bell ring, once, somewhere in the depths, and the murmur of the crowd didn't so much as pause. Webb was already at the bottom of the stairs. He turned, once, and looked up at her, and there was something in his face that wasn't fear anymore. It was almost pity. "You don't want to come down here, Detective," he said, and his voice carried up the stairwell with unnatural clarity. "Not without a token. Not without an invitation. Things down here don't much care about your warrant card." "Webb—" Her hand found the grip of the baton at her belt out of pure reflex, useless as it would likely prove. "I just want to talk to you." "No," he said, almost gently, "you want to know what happened to your partner. I know that face. I've seen it on you since Mayfair." He shook his head, water dripping from his sleeves onto stone floor. "Wrong entrance, wrong night, for that answer." Then he turned and walked into the crowd, unhurried now, and within three seconds she'd lost him completely among the stalls and the shifting lantern light, as though the market itself had folded around him and closed the seam. Quinn stood at the top of the stairs with the rain still falling behind her and the strange warm dark spreading out below, and she thought about eleven minutes, and about a report she'd signed that she hadn't believed even as the pen left the paper, and about how many years she had left before someone else's name went into a file like that because of a door she'd been too careful to walk through. She thought about calling it in. She thought about the words she'd have to use, and how they'd sound over the radio, and how quickly a sympathetic sergeant would have her reassigned to desk duty pending psychological evaluation. Then she put her hand on the cold iron railing, and started down the stairs into the market, alone, unarmed in any way that would matter, and did not look back at the rain.
created_at"2026-07-01T07:47:59.111Z" 7/1/2026, 7:47:59 AM
model"anthropic/claude-sonnet-5-20260630"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency4956
moderation_latency(null)
generation_time36155
tokens_prompt914
tokens_completion1761
native_tokens_prompt1264
native_tokens_completion2242
native_tokens_completion_images(null)
native_tokens_reasoning87
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"
usage0.024948
router(null)
provider_responses
0
endpoint_id"37b16f45-eeae-45f3-9b85-2137f7c6d61b"
id"msg_01KngycaCieJy7TH3rqAjrdj"
is_byokfalse
latency2540
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-1782892079-7u8DGLaOj64eBWWCUbwg"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1782892079-AHgWq31JlDZvC5PrPOWZ"
upstream_id"msg_01KngycaCieJy7TH3rqAjrdj"
total_cost0.024948
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
totalTags5
adverbTagCount0
adverbTags(empty)
dialogueSentences8
tagDensity0.625
leniency1
rawRatio0
effectiveRatio0
87.22% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1174
totalAiIsmAdverbs3
found
0
adverb"gently"
count1
1
adverb"completely"
count1
2
adverb"quickly"
count1
highlights
0"gently"
1"completely"
2"quickly"
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)
78.71% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1174
totalAiIsms5
found
0
word"weight"
count1
1
word"database"
count1
2
word"stomach"
count1
3
word"electric"
count1
4
word"depths"
count1
highlights
0"weight"
1"database"
2"stomach"
3"electric"
4"depths"
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
narrationSentences48
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences48
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences51
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen75
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1169
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions23
wordCount1065
uniqueNames14
maxNameDensity0.56
worstName"Quinn"
maxWindowNameDensity1
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn6
Chalk1
Farm1
Road1
Eighteen1
Webb4
Tuesday1
Camden1
Morris1
Mayfair1
Tube1
London2
Transport1
persons
0"Harlow"
1"Quinn"
2"Webb"
3"Morris"
places
0"Chalk"
1"Farm"
2"Road"
3"London"
globalScore1
windowScore1
25.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences40
glossingSentenceCount2
matches
0"d up and then, evidently, un-bricked by some"
1"something like copper, and beneath that some"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1169
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences51
matches
0"signed that she"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs21
mean55.67
std37.1
cv0.666
sampleLengths
070
145
29
3115
48
569
676
7117
810
9125
104
1184
12108
1332
1438
1529
1644
1739
1875
1938
2034
90.64% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences48
matches
0"been bricked"
1"got written"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs166
matches
0"wasn't laughing"
1"was still functioning"
30.81% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount4
semicolonCount0
flaggedSentences2
totalSentences51
ratio0.039
matches
0"Ahead of her, a shape in a dark hoodie cut between two parked cars, vaulted a low wall with an ease that struck her as wrong—too fluid, too fast for a man his size—and vanished into the alley behind a shuttered chip shop."
1"There were people down there—if they were people—moving between the stalls with unhurried purpose, examining jars and bundled herbs and things that glittered wrong in the lantern light."
88.08% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount317
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.05362776025236593
lyAdverbCount3
lyAdverbRatio0.00946372239747634
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences51
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences51
mean22.92
std16.98
cv0.741
sampleLengths
027
143
217
328
43
56
630
72
833
98
103
1139
123
135
1458
157
164
1713
1832
1923
208
2137
2224
237
2449
2510
2629
2717
2853
2926
304
3142
3220
3322
3459
3528
3621
379
3819
394
4020
4118
4222
437
4437
457
4639
4775
486
4932
61.44% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.45098039215686275
totalSentences51
uniqueOpeners23
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount5
totalSentences47
matches
0"Maybe it did."
1"Maybe more than her career."
2"Somewhere three years ago, in"
3"Then he turned and walked"
4"Then she put her hand"
ratio0.106
32.77% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount22
totalSentences47
matches
0"Her voice cracked against the"
1"He didn't stop."
2"He never did, the good"
3"It had, eventually."
4"It was why she was"
5"She'd pulled his name from"
6"She'd laughed at that in"
7"She wasn't laughing now."
8"He went up it like"
9"She landed hard, jarred her"
10"She'd found what was left"
11"She was not going to"
12"She went in anyway."
13"She could smell woodsmoke, and"
14"She heard a bell ring,"
15"He turned, once, and looked"
16"It was almost pity."
17"he said, and his voice"
18"Her hand found the grip"
19"he said, almost gently, He"
ratio0.468
77.02% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount36
totalSentences47
matches
0"The rain came down in"
1"Her voice cracked against the"
2"He didn't stop."
3"He never did, the good"
4"Quinn's boots hit standing water"
5"That last one should have"
6"It had, eventually."
7"It was why she was"
8"She'd pulled his name from"
9"She'd laughed at that in"
10"She wasn't laughing now."
11"Webb hit the end of"
12"He went up it like"
13"Quinn swore under her breath"
14"She landed hard, jarred her"
15"The rain was worse down"
16"She'd found what was left"
17"She was not going to"
18"Webb ducked through a gap"
19"Quinn slowed at the mouth"
ratio0.766
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences47
matches(empty)
ratio0
0.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences28
technicalSentenceCount9
matches
0"Ahead of her, a shape in a dark hoodie cut between two parked cars, vaulted a low wall with an ease that struck her as wrong—too fluid, too fast for a man his s…"
1"Petty thief, sometimes police informant, a man she'd hauled in twice for receiving stolen goods and once, memorably, for possession of a substance that hadn't s…"
2"Quinn swore under her breath and followed, her hands raw against the wet chain-link, her jacket catching and tearing on the top wire."
3"She'd found what was left of him in a stairwell that smelled the same way that Mayfair club had smelled, and the official report had called it an animal attack,…"
4"There were disused stations all over London, mothballed relics of lines rerouted decades ago, and she knew, in the dim procedural part of her brain that was sti…"
5"The kind of decision that got detectives killed, or worse, got them found six months later with no explanation anyone could stomach putting in a file."
6"Quinn stood at the top of a set of stairs that shouldn't have existed on any Transport for London schematic she'd ever pulled, and looked down into a platform l…"
7"There were people down there—if they were people—moving between the stalls with unhurried purpose, examining jars and bundled herbs and things that glittered wr…"
8"Then he turned and walked into the crowd, unhurried now, and within three seconds she'd lost him completely among the stalls and the shifting lantern light, as …"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags5
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount0
fancyTags(empty)
dialogueSentences8
tagDensity0.25
leniency0.5
rawRatio0
effectiveRatio0
81.7228%