Run: 2026-07-25-01KYCV1GZ7N72H6C17YV22RA3Q

Run Details

Duration:
11.1s
Cost:
$0.007628
Provider:
BaseTen

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
Quinn’s boots hit the pavement with a dull splash that sent rainwater skittering down the curb. The alley mouth yawned black ahead, and she pushed through it hard, lungs burning with the copper taste of exertion. Behind her, Soho’s neon bled into the wet asphalt—pink, green, sick yellow—while her quarry, a thin silhouette in a charcoal coat, vanished around the corner of Berwick Street with the fluid grace of someone who knew these veins by heart. She rounded the corner, shoulder brushing brick, and caught the flick of that coat disappearing into a service stairwell beside a shuttered kebab shop. The stairwell exhaled a stink of rust and old urine. She hesitated for half a second—just long enough for her heart to thunder in her ears—then followed. The stairs plunged downward in a spiral of iron and grime, each step echoing like a gunshot in the enclosed dark. Rain plastered her hair flat against her skull, and she ran a hand over her salt-and-pepper crop, slick with water, cursing herself for leaving her coat in the car. By the time she hit the bottom landing, her shoes were soaked through and her left wrist ached where she’d braced herself against a rail. The leather of her watch—worn soft by eighteen years—digged into her skin. The corridor at the bottom was tiled in white ceramic, yellowed by decades of neglect, and lit by a single flickering tube that hummed like an angry wasp. She moved with her hand near her hip, where her service weapon rested cold and familiar, her bearing precise even as her breath came hard. The charcoal coat was gone, but the air still carried the scent of wet wool and something sharper, chemical, like ozone before a storm. Then the corridor opened up. Quinn stopped dead. She had expected a boiler room, a storage cellar, maybe a dead end where her suspect had hidden in some maintenance closet. Instead, she stood at the threshold of a cavernous space that defied the geometry of the street above. The ceiling arched high, lined with the skeletal ribs of an abandoned Tube station—Camden Town, or what was left of it—where rusted tracks disappeared into darkness and old advertisement posters for cigarettes and musicals peeled from the walls in long, decayed ribbons. But people were here. Dozens of them, maybe more, threading through stalls that had been erected between the platform edges and the abandoned train cars. Torches—actual torches—burned in iron brackets, casting dancing shadows across faces that were not quite right. Some wore masks of polished bone. Others had eyes that reflected the torchlight like cats’. A vendor with gnarled hands sold vials of liquid that glowed violet from a crate stamped with symbols she couldn’t read. The air was thick with incense, rot, and the metallic tang of old electricity. Quinn pressed herself back into the corridor’s shadow, her sharp jaw set hard. This was not Soho. This was not London, not the one she’d policed for nearly two decades. It was the Veil. She’d heard the name in whispers, in files that never made it to the court docket, in the terrified ramblings of witnesses who swore they’d seen things that broke physics. She’d never believed it was real. Or she hadn’t wanted to. The charcoal coat was visible now, weaving through the crowd near a stall that displayed what looked like human teeth strung on copper wire. The suspect—Quinn still didn’t have a name, only the report that linked him to three disappearances—moved with purpose, not panic. He knew this place. He belonged here. Quinn’s hand tightened on her weapon, then released. Drawing steel in a room full of unknown entities was the kind of mistake that got you killed, or worse, disappeared without a trace. Like Morris. The thought came unbidden, sharp as a needle. Three years since she’d watched her partner, DS Morris, walk into a warehouse in Whitechapel and never come back. The official report cited structural collapse, accidental death, case closed. But Quinn had seen the security footage—what little survived—of Morris stepping into darkness and then nothing, a flicker, like someone had turned off the lights inside his body. She’d spent three years digging, and every thread led back to spaces like this, hidden beneath the skin of the city she thought she knew. Her watch ticked loud in the silence of the corridor. She glanced down—7:44 PM, the leather strap dark with rain. She needed to follow him. Needed to see where he went, who he spoke to, whether this was the hub that had swallowed Morris whole. But she needed entry first. At the far end of the market, near a collapsed escalator that led back to the surface, she spotted the gatekeeper. A broad-shouldered figure in a leather duster, examining something in the palm of each entrant with the patience of a toll collector. She moved closer, staying to the shadow of a broken pillar, and watched. Bone. They were handing over chips of bone, yellowed with age, each one unique like a fingerprint. Tokens. The price of admission. Quinn checked her pockets. Phone—useless down here, the signal dead as stone. Wallet—thin, carrying her warrant card and twenty quid. Nothing that looked like a fragment of skeleton. She scanned the perimeter, her eyes adjusting to the dim. Near a stall selling bottled smoke, she spotted a dead rat, its body desiccated, ribs visible through papery skin. Not ideal. Not human. But bone was bone, and she only needed to pass one check. She waited for the gatekeeper to turn, then darted across the open space with her head down, her boots silent on the dirty tile. The rat was lighter than she expected, brittle, and she snapped free a ribcage with her gloved fingers, pocketing the fragment with a grimace. Then she was in line, sandwiched between a woman with antlers hidden beneath a hood and a tall man whose face was hidden behind a respirator mask. The gatekeeper barely looked at her. His eyes—too large, too black—scanned the bone token she pressed into his palm, then nodded toward the market’s heart. Quinn stepped through. The noise hit her first, a low murmur of bargaining in languages she half-recognized and others that sounded like wind through hollow trees. The smells intensified—sulfur, sweat, sweet rot. She pulled her collar up and moved into the flow, letting the crowd carry her forward, her eyes locked on the charcoal coat that had paused near a cluster of hanging lanterns. She was in now. No cover. No backup. No one even knew she was down here except the dead rat she’d robbed and the gatekeeper whose gaze she still felt on her back. The coat moved again, heading toward a narrow passage between two train cars that had been converted into some kind of archive—books with leather bindings that squirmed when she passed, pages turning of their own accord. Quinn followed, her heart steady now, the fear transmuted into the cold precision that had kept her alive through eighteen years of service. She was good at following. Good at waiting. Good at seeing patterns in darkness. At the mouth of the passage, she paused and looked back. The market stretched behind her, a galaxy of torchlight and shadow, dangerous and alive. She had crossed a threshold, not just physical but existential. The rules up top—law, order, the rational world of evidence and warrants—did not apply here. She was in the marrow of the city now, where the bones of old things were currency and people vanished not into death but into something older. Quinn took a breath, held it, and stepped into the passage after her suspect. She was not leaving. Not without answers. Not without knowing if Morris was still down here somewhere, lost in these tunnels, waiting for someone with the courage to come find him. The charcoal coat disappeared into darkness. Quinn followed.
created_at"2026-07-25T14:32:06.383Z" 7/25/2026, 2:32:06 PM
model"thinkingmachines/inkling-20260715"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency262
moderation_latency(null)
generation_time10445
tokens_prompt888
tokens_completion1994
native_tokens_prompt816
native_tokens_completion1682
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"stop"
service_tier(null)
usage0.0076281
router(null)
provider_responses
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endpoint_id"ba2df08c-c0a0-4e0e-9f31-d79a9c475b70"
id"chatcmpl-3f2585f3c7894515aed4abeaef106d0d"
is_byokfalse
latency262
model_permaslug"thinkingmachines/inkling-20260715"
provider_name"BaseTen"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1784989926-PV955lZDEs16HP40VIVO"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784989926-Hk5Mww4dADSCf0wVo3u5"
upstream_id"chatcmpl-3f2585f3c7894515aed4abeaef106d0d"
total_cost0.0076281
cache_discount(null)
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provider_name"BaseTen"
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
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences0
tagDensity1
leniency1
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1345
totalAiIsmAdverbs0
found(empty)
highlights(empty)
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)
73.98% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1345
totalAiIsms7
found
0
word"echoing"
count1
1
word"familiar"
count1
2
word"dancing"
count1
3
word"flicker"
count1
4
word"silence"
count1
5
word"scanned"
count2
highlights
0"echoing"
1"familiar"
2"dancing"
3"flicker"
4"silence"
5"scanned"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"air was thick with"
count1
highlights
0"The air was thick with"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences94
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences94
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences94
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen44
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1322
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions26
wordCount1321
uniqueNames11
maxNameDensity0.83
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Soho2
Berwick1
Street1
Tube1
Camden1
Town1
London1
Veil1
Quinn11
Morris5
Whitechapel1
persons
0"Quinn"
1"Morris"
places
0"Soho"
1"Berwick"
2"Street"
3"Camden"
4"Town"
5"London"
6"Whitechapel"
globalScore1
windowScore1
39.71% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences68
glossingSentenceCount3
matches
0"looked like human teeth strung on copper"
1"looked like a fragment of skeleton"
2"sounded like wind through hollow trees"
48.71% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords1.513
wordCount1322
matches
0"not just physical but existential"
1"not into death but into something older"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences94
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs32
mean41.31
std28.51
cv0.69
sampleLengths
076
151
287
377
45
53
682
74
886
930
104
1141
1251
1334
1490
1520
1625
1761
1822
1928
2045
2175
2225
233
2461
2533
2673
2711
2866
2914
3031
318
86.60% Passive voice overuse
Target: ≤2% passive sentences
passiveCount5
totalSentences94
matches
0"was tiled"
1"was gone"
2"been erected"
3"was hidden"
4"been converted"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs219
matches
0"were handing"
1"was not leaving"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount23
semicolonCount0
flaggedSentences14
totalSentences94
ratio0.149
matches
0"Behind her, Soho’s neon bled into the wet asphalt—pink, green, sick yellow—while her quarry, a thin silhouette in a charcoal coat, vanished around the corner of Berwick Street with the fluid grace of someone who knew these veins by heart."
1"She hesitated for half a second—just long enough for her heart to thunder in her ears—then followed."
2"The leather of her watch—worn soft by eighteen years—digged into her skin."
3"The ceiling arched high, lined with the skeletal ribs of an abandoned Tube station—Camden Town, or what was left of it—where rusted tracks disappeared into darkness and old advertisement posters for cigarettes and musicals peeled from the walls in long, decayed ribbons."
4"Torches—actual torches—burned in iron brackets, casting dancing shadows across faces that were not quite right."
5"The suspect—Quinn still didn’t have a name, only the report that linked him to three disappearances—moved with purpose, not panic."
6"But Quinn had seen the security footage—what little survived—of Morris stepping into darkness and then nothing, a flicker, like someone had turned off the lights inside his body."
7"She glanced down—7:44 PM, the leather strap dark with rain."
8"Phone—useless down here, the signal dead as stone."
9"Wallet—thin, carrying her warrant card and twenty quid."
10"His eyes—too large, too black—scanned the bone token she pressed into his palm, then nodded toward the market’s heart."
11"The smells intensified—sulfur, sweat, sweet rot."
12"The coat moved again, heading toward a narrow passage between two train cars that had been converted into some kind of archive—books with leather bindings that squirmed when she passed, pages turning of their own accord."
13"The rules up top—law, order, the rational world of evidence and warrants—did not apply here."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount447
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.03803131991051454
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences94
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences94
mean14.06
std9.83
cv0.699
sampleLengths
016
120
240
324
410
517
621
729
825
912
1028
1125
1224
135
143
1522
1618
1742
184
1921
2015
216
229
2321
2414
2513
264
2713
284
2930
306
315
3224
3320
344
353
368
3724
382
398
4019
4110
4228
4325
4410
4510
465
4720
485
4921
48.23% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.3723404255319149
totalSentences94
uniqueOpeners35
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences86
matches
0"Then the corridor opened up."
1"Instead, she stood at the"
2"Then she was in line,"
ratio0.035
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount24
totalSentences86
matches
0"She rounded the corner, shoulder"
1"She hesitated for half a"
2"She moved with her hand"
3"She had expected a boiler"
4"It was the Veil."
5"She’d heard the name in"
6"She’d never believed it was"
7"He knew this place."
8"He belonged here."
9"She’d spent three years digging,"
10"Her watch ticked loud in"
11"She glanced down—7:44 PM, the"
12"She needed to follow him."
13"She moved closer, staying to"
14"They were handing over chips"
15"She scanned the perimeter, her"
16"She waited for the gatekeeper"
17"His eyes—too large, too black—scanned"
18"She pulled her collar up"
19"She was in now."
ratio0.279
87.91% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount64
totalSentences86
matches
0"Quinn’s boots hit the pavement"
1"The alley mouth yawned black"
2"She rounded the corner, shoulder"
3"The stairwell exhaled a stink"
4"She hesitated for half a"
5"The stairs plunged downward in"
6"Rain plastered her hair flat"
7"The leather of her watch—worn"
8"The corridor at the bottom"
9"She moved with her hand"
10"The charcoal coat was gone,"
11"Quinn stopped dead."
12"She had expected a boiler"
13"The ceiling arched high, lined"
14"Dozens of them, maybe more,"
15"Torches—actual torches—burned in iron brackets,"
16"Some wore masks of polished"
17"Others had eyes that reflected"
18"A vendor with gnarled hands"
19"The air was thick with"
ratio0.744
58.14% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences86
matches
0"By the time she hit"
ratio0.012
28.06% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences56
technicalSentenceCount9
matches
0"Quinn’s boots hit the pavement with a dull splash that sent rainwater skittering down the curb."
1"Behind her, Soho’s neon bled into the wet asphalt—pink, green, sick yellow—while her quarry, a thin silhouette in a charcoal coat, vanished around the corner of…"
2"The corridor at the bottom was tiled in white ceramic, yellowed by decades of neglect, and lit by a single flickering tube that hummed like an angry wasp."
3"Instead, she stood at the threshold of a cavernous space that defied the geometry of the street above."
4"The charcoal coat was visible now, weaving through the crowd near a stall that displayed what looked like human teeth strung on copper wire."
5"Drawing steel in a room full of unknown entities was the kind of mistake that got you killed, or worse, disappeared without a trace."
6"At the far end of the market, near a collapsed escalator that led back to the surface, she spotted the gatekeeper."
7"The coat moved again, heading toward a narrow passage between two train cars that had been converted into some kind of archive—books with leather bindings that …"
8"Quinn followed, her heart steady now, the fear transmuted into the cold precision that had kept her alive through eighteen years of service."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags1
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
85.7111%