Run: 2026-07-25-01KYD5KFFEHKYWD2EPYZWFPERV

Run Details

Duration:
1m 12s
Cost:
$0.027311
Provider:
Moonshot AI

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 sheets over Soho, turning the neon into smears of green and red across the wet pavement, and Harlow Quinn was already soaked through to the skin. She'd been sitting in her car outside the Raven's Nest for three hours when the man she knew only as the fixer came out the side door. Tomás Herrera — she had his file memorized. Twenty-nine, former NHS paramedic, license stripped two years ago for reasons the official record kept suspiciously vague. She'd watched him go into that bar a dozen times over the past month. Watched him come out carrying a black medical bag. Watched him meet with people who didn't appear on any database she'd ever searched. Tonight, he'd made her. She hadn't even done anything wrong. Just a glance held a half-second too long as he passed her car, his warm brown eyes finding hers through the rain-streaked windshield, and then he was moving — fast, bag clutched to his chest, cutting left down an alley off Brewer Street. Quinn was out of the car before she made a conscious decision, her boots hitting the pavement, eighteen years of training overriding everything else. "Herrera! Met Police — stop!" He didn't stop. Of course he didn't. The alley was narrow, stinking of grease and old rain, and her shoulder slammed a drainpipe as she rounded a stack of pallets he'd shoved behind him. She scrambled over them, kept her footing, and caught a flash of his olive skin under a streetlight as he burst out onto Berwick Street. The market stalls were shuttered, awnings dripping, the whole street a river of reflected light. He was fast. She'd give him that. Eighteen years of service, three of them spent chasing ghosts that no report could explain, and she was gaining on a man twelve years younger. Her lungs burned. Her worn leather watch — Morris's watch, the one she'd never taken off — ticked against her wrist like a second heartbeat. "Herrera, stop!" she shouted again. "I just want to talk!" A lie, mostly. She wanted answers. She wanted to know what was in the bag. She wanted to know why half the people he treated had no records, no NHS numbers, no existence. She wanted to know what her dead partner had stumbled into three years ago, because the closer she looked at Herrera's circle, the more it smelled like the same thing. He veered north, toward Camden, and she lost him for thirty seconds at the junction — long enough for her pulse to spike, her hand going to her radio before she thought better of it. Call it in and what? Explain she was off-shift, running surveillance on a case that wasn't hers, chasing a man into the rain on a hunch her superintendent had already told her to drop twice? She caught sight of him again at the entrance to the old Tube station. She'd walked past it a hundred times. Boarded up since the sixties, according to the city. A dead station, fenced off, marked for redevelopment that never came. Except the fence had a gap in it tonight — a gap she was suddenly certain had been opened from the inside — and Herrera slipped through it like water through a crack. Quinn slowed at the fence line, rain streaming off her closely cropped hair, her chest heaving. This was where a smart detective stopped. This was where she noted the location, called for backup, did it by the book. The book had kept her alive for eighteen years. Mostly. Morris had followed the book too. Morris was dead, and the file on his death had so many redactions it read like a crossword puzzle, and nobody — nobody — would tell her why. She went through the fence. The stairs went down farther than they should have. She knew that immediately, with the cold animal certainty that lived at the base of her spine. The old station shouldn't have descended this far. The tiled walls were sweating, ancient adverts peeling away in damp curls, and somewhere below she could hear Herrera's footsteps echoing — and something else. Music. Voices. The murmur of a crowd, rising up from the earth like heat from a vent. She drew her sidearm — off the books, like everything else tonight — and kept going. The stairs opened onto a platform, and Quinn stopped dead. The station was alive. String lights hung in swags from the vaulted ceiling, hundreds of them, casting amber pools across a market that sprawled the length of the platform and spilled onto the tracks themselves. Stalls crowded shoulder to shoulder: glass jars full of things that pulsed faintly in the dark, bundles of dried herbs she couldn't name, knives laid out on black velvet that seemed to drink the light. A woman with no irises — white from lid to lid — turned her head as Quinn passed, and smiled. Somewhere a man was haggling in a language that made Quinn's back teeth ache. Her hand tightened on the pistol. She kept it low, close to her thigh, and forced her breathing to slow. Sharp jaw set. Military precision. Assess, don't panic. The people here — if they were people — hadn't reacted to her. Not yet. A few glances, quickly averted. Like they knew what she was and didn't care, or worse, knew what she was and found it uninteresting. She scanned the crowd for Herrera and found him halfway down the platform, stopped at a stall, his medical bag open. He was talking urgently to a figure in a gray coat, gesturing back toward the stairs. Toward her. Then the figure in gray looked up, and though Quinn couldn't see its face beneath the hood, she felt its attention land on her like a hand on the back of her neck. Every instinct she had screamed at her to run. She was out of her jurisdiction in every sense — geographic, procedural, and something deeper she didn't have a word for. She had no backup. No one knew where she was. If she vanished down here, her file would end up exactly like Morris's: black bars and unanswered questions. Herrera saw her then. His face went pale under the string lights, and he did something she didn't expect. He didn't run. He closed his bag, said something to the gray figure, and started walking toward her — hands raised slightly, palms open, the way a man approaches a frightened animal. "Detective," he called over the market noise, close enough now that she could see the gold glint of a medallion at his throat. Saint Christopher. Patron saint of travelers. "You should not have followed me down here." "Tomás Herrera." She kept the pistol low but let him see it. "You're going to tell me what this place is." "This place is the least of your problems." His eyes flicked past her, toward the stairs, and something in his expression shifted — the particular stillness of a paramedic reading a scene. "You walked in through the front, which means the door was open for you. Do you understand what that means? They let you in. This market doesn't open for people like you unless it wants something." Behind him, the crowd had gone quiet. Stall by stall, like a wave moving along the platform, the murmur died. The white-eyed woman was watching. The figure in gray was watching. Quinn felt hundreds of gazes settling on her skin like rain. Herrera stepped closer, lowering his voice. "You have maybe a minute before someone decides you're interesting. Come with me through the back, right now, and I will answer one question — any question you want, honestly, I swear it on the medal. Or stay here with your gun and your warrant card and find out what they're worth underground." She looked at him. She looked past him at the impossible market, the pulsing jars, the stalls that shouldn't exist beneath a city she'd policed her entire adult life. She thought of Morris's file. She thought of the one question she'd been asking for three years to empty rooms. "Any question," she said. "One." "Then take me through the back," Quinn said, and holstered her weapon, and followed Tomás Herrera into the dark beneath London.
created_at"2026-07-25T17:36:40.437Z" 7/25/2026, 5:36:40 PM
model"moonshotai/kimi-k3-20260715"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3758
moderation_latency(null)
generation_time71805
tokens_prompt888
tokens_completion2050
native_tokens_prompt910
native_tokens_completion1777
native_tokens_completion_images(null)
native_tokens_reasoning55
native_tokens_cached768
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)
usage0.0273114
router(null)
provider_responses
0
endpoint_id"650c9b12-7b6d-444d-8d92-df8daef84d7a"
id"chatcmpl-6a64f429afdc8cdbbb9b5b14"
is_byokfalse
latency3758
model_permaslug"moonshotai/kimi-k3-20260715"
provider_name"Moonshot AI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1785001000-0iY3qpPXMNPnQQLLKBkj"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1785001000-hm7qqMdBVK4U9VKBiFxz"
upstream_id"chatcmpl-6a64f429afdc8cdbbb9b5b14"
total_cost0.0273114
cache_discount0.0020736
upstream_inference_cost0
provider_name"Moonshot AI"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
46.15% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags6
adverbTagCount1
adverbTags
0"she shouted again [again]"
dialogueSentences13
tagDensity0.462
leniency0.923
rawRatio0.167
effectiveRatio0.154
89.07% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1372
totalAiIsmAdverbs3
found
0
adverb"suddenly"
count1
1
adverb"quickly"
count1
2
adverb"slightly"
count1
highlights
0"suddenly"
1"quickly"
2"slightly"
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)
63.56% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1372
totalAiIsms10
found
0
word"database"
count1
1
word"pulse"
count1
2
word"streaming"
count1
3
word"footsteps"
count1
4
word"echoing"
count1
5
word"pulsed"
count1
6
word"velvet"
count1
7
word"scanned"
count1
8
word"glint"
count1
9
word"flicked"
count1
highlights
0"database"
1"pulse"
2"streaming"
3"footsteps"
4"echoing"
5"pulsed"
6"velvet"
7"scanned"
8"glint"
9"flicked"
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
narrationSentences96
matches(empty)
83.33% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount1
narrationSentences96
filterMatches
0"watch — watch"
1"see"
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences103
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen52
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1393
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions37
wordCount1255
uniqueNames16
maxNameDensity0.72
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Soho1
Harlow1
Quinn9
Raven1
Nest1
Herrera8
Brewer1
Street2
Berwick1
Morris5
Camden1
Tube1
Saint1
Christopher1
Tomás2
London1
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Morris"
4"Saint"
5"Christopher"
6"Tomás"
places
0"Soho"
1"Raven"
2"Brewer"
3"Street"
4"Berwick"
5"Camden"
6"London"
globalScore1
windowScore1
74.24% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences66
glossingSentenceCount2
matches
0"smelled like the same thing"
1"velvet that seemed to drink the light"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1393
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences103
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs37
mean37.65
std25.39
cv0.674
sampleLengths
031
189
24
349
429
57
667
757
810
963
1070
1114
1260
1316
1432
1534
165
1776
1816
1910
20104
2128
2239
2339
2433
2558
2619
2732
2837
2921
3068
3142
3259
3349
344
351
3621
97.95% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences96
matches
0"were shuttered"
1"been opened"
17.35% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount6
totalVerbs219
matches
0"was gaining"
1"were sweating"
2"was haggling"
3"was talking"
4"was watching"
5"was watching"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount19
semicolonCount0
flaggedSentences13
totalSentences103
ratio0.126
matches
0"Tomás Herrera — she had his file memorized."
1"Just a glance held a half-second too long as he passed her car, his warm brown eyes finding hers through the rain-streaked windshield, and then he was moving — fast, bag clutched to his chest, cutting left down an alley off Brewer Street."
2"Her worn leather watch — Morris's watch, the one she'd never taken off — ticked against her wrist like a second heartbeat."
3"He veered north, toward Camden, and she lost him for thirty seconds at the junction — long enough for her pulse to spike, her hand going to her radio before she thought better of it."
4"Except the fence had a gap in it tonight — a gap she was suddenly certain had been opened from the inside — and Herrera slipped through it like water through a crack."
5"Morris was dead, and the file on his death had so many redactions it read like a crossword puzzle, and nobody — nobody — would tell her why."
6"The tiled walls were sweating, ancient adverts peeling away in damp curls, and somewhere below she could hear Herrera's footsteps echoing — and something else."
7"She drew her sidearm — off the books, like everything else tonight — and kept going."
8"A woman with no irises — white from lid to lid — turned her head as Quinn passed, and smiled."
9"The people here — if they were people — hadn't reacted to her."
10"She was out of her jurisdiction in every sense — geographic, procedural, and something deeper she didn't have a word for."
11"He closed his bag, said something to the gray figure, and started walking toward her — hands raised slightly, palms open, the way a man approaches a frightened animal."
12"\"This place is the least of your problems.\" His eyes flicked past her, toward the stairs, and something in his expression shifted — the particular stillness of a paramedic reading a scene."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1241
adjectiveStacks0
stackExamples(empty)
adverbCount37
adverbRatio0.029814665592264304
lyAdverbCount12
lyAdverbRatio0.009669621273166801
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences103
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences103
mean13.52
std10.89
cv0.806
sampleLengths
031
127
28
317
414
59
614
74
86
943
1024
115
123
134
1427
1525
1615
173
184
1925
203
2122
225
235
243
253
269
2718
2830
2935
305
3130
3214
337
349
3511
3633
3716
387
3915
409
411
426
4328
445
459
4617
478
4825
491
58.90% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats16
diversityRatio0.44660194174757284
totalSentences103
uniqueOpeners46
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount4
totalSentences88
matches
0"Just a glance held a"
1"Of course he didn't."
2"Somewhere a man was haggling"
3"Then the figure in gray"
ratio0.045
56.36% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount36
totalSentences88
matches
0"She'd been sitting in her"
1"She'd watched him go into"
2"She hadn't even done anything"
3"He didn't stop."
4"She scrambled over them, kept"
5"He was fast."
6"She'd give him that."
7"Her lungs burned."
8"Her worn leather watch —"
9"she shouted again"
10"She wanted answers."
11"She wanted to know what"
12"She wanted to know why"
13"She wanted to know what"
14"He veered north, toward Camden,"
15"She caught sight of him"
16"She'd walked past it a"
17"She went through the fence."
18"She knew that immediately, with"
19"She drew her sidearm —"
ratio0.409
73.64% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount68
totalSentences88
matches
0"The rain came down in"
1"She'd been sitting in her"
2"Tomás Herrera — she had"
3"She'd watched him go into"
4"Tonight, he'd made her."
5"She hadn't even done anything"
6"Quinn was out of the"
7"He didn't stop."
8"The alley was narrow, stinking"
9"She scrambled over them, kept"
10"The market stalls were shuttered,"
11"He was fast."
12"She'd give him that."
13"Her lungs burned."
14"Her worn leather watch —"
15"she shouted again"
16"A lie, mostly."
17"She wanted answers."
18"She wanted to know what"
19"She wanted to know why"
ratio0.773
56.82% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences88
matches
0"If she vanished down here,"
ratio0.011
47.62% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences45
technicalSentenceCount6
matches
0"Quinn was out of the car before she made a conscious decision, her boots hitting the pavement, eighteen years of training overriding everything else."
1"Explain she was off-shift, running surveillance on a case that wasn't hers, chasing a man into the rain on a hunch her superintendent had already told her to dr…"
2"Quinn slowed at the fence line, rain streaming off her closely cropped hair, her chest heaving."
3"She knew that immediately, with the cold animal certainty that lived at the base of her spine."
4"The tiled walls were sweating, ancient adverts peeling away in damp curls, and somewhere below she could hear Herrera's footsteps echoing — and something else."
5"She looked past him at the impossible market, the pulsing jars, the stalls that shouldn't exist beneath a city she'd policed her entire adult life."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount0
matches(empty)
73.08% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount1
fancyTags
0"she shouted again (shout)"
dialogueSentences13
tagDensity0.308
leniency0.615
rawRatio0.25
effectiveRatio0.154
81.2691%