Run: 2026-07-25-01KYD5GMM1MR16SNN2X38PSCH4

Run Details

Duration:
1m 11s
Cost:
$0.026435
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="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <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> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. 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 stairs down to the old Camden passage smelled of wet concrete and something sweeter underneath, something that put Harlow Quinn in mind of a church her grandmother used to drag her to in Birmingham. Incense and old stone. She ducked the crime scene tape at the bottom of the steps and held her warrant card up to the uniform posted there, a boy who couldn't have been more than twenty-three and who looked at the abandoned platform beyond with the particular blankness of someone trying very hard not to think. "Detective Quinn," she said. "Who called it in?" "British Transport Police found him at oh-five-hundred, ma'am. Routine trespass sweep. They took one look and kicked it up to us." "Wise of them." She pulled on gloves and stepped past him onto the platform. The station had been closed since before she was born — one of those wartime casualties the city had simply bricked over and forgotten, though forgotten places had a way of being remembered by the wrong people. The tiles along the curved wall were that oxblood red you only saw in the oldest stations, crazed with grime, and somebody had spray-painted sigils along them at intervals. Not gang tags. Quinn had seen enough gang tags to know. These were careful, symmetrical, almost calligraphic, rendered in a paint that seemed to swallow the scene lamps rather than reflect them. The body sat propped against the far wall as if waiting for a train that would never come. Male, late thirties, well dressed — good coat, good shoes, a wedding band. No wallet. No phone. His hands rested in his lap, palms up, and his eyes were open, fixed on the black tunnel mouth across the tracks with an expression that Quinn could only describe as attentive. Like he'd heard an announcement and was listening for it to repeat. DS Ferris was waiting for her, crouched beside the forensic tent with a coffee going cold in one hand. He was a solid man, methodical, the kind of detective who wrote everything down and trusted the paperwork more than his own eyes. Three years ago she'd have called that a virtue. "Quinn. Glad they sent someone with seniority." He straightened up, wincing at his knees. "Nasty one. No visible wounds, no blood, nothing. Doc's guess is cardiac arrest. Rough sleeper wandered down here, ticker gave out." "He's not a rough sleeper." "Clothes, yes, I clocked the coat. Could've nicked it." "His shoes are broken in, Ferris. Heels worn on the outside edge, right more than left. You don't nick shoes that fit your gait." She crouched beside the body without touching it, angling her head to catch the light. "Fingernails are clean. Hands are soft. And look at his collar." Ferris leaned in. "What am I looking at?" "Nothing. That's the point. No grime. A man sleeps rough for a week, his collar tells you. This man showered yesterday morning and shaved." She lifted her gaze along the platform. "So what was a man with a good coat and a clean collar doing in a station that's been sealed for eighty years?" "Same thing they all do down here. Drugs, or a party. You know what these places get used for. We've had three raves in disused stations this year alone." "A rave." Quinn stood slowly, looking at the empty platform, the swept-clean tiles, the sigils. "With no bottles, no needles, no cigarette ends. No footprints in the dust except his and the BTP lads'. No graffiti except the pretty writing on the walls, which — has anyone tested that paint? Because it isn't reflecting the lamps." Ferris rubbed the back of his neck. "It's matte paint." "It's not matte. Shine your torch at it." He did, reluctantly. The beam struck the nearest sigil and died there, swallowed, a dim grey smudge where a bright circle should have been. Ferris stared at it for a moment. "That's — odd." "Yes." "Could be a coating. Some kind of light-absorbent coating, you can buy them—" "For a party." She kept her voice level. "Ferris, walk me through it. He comes down here — how? The access stairs were chained. BTP had to cut the chain, and the chain was rusted through at the links. Nobody's cut that chain in years." "There's another way in. There's always another way in with these places." "Then show me where his prints lead." Ferris didn't answer that, which was an answer in itself. She turned back to the body, to those upturned palms, and crouched again. Something glinted against the dead man's left hand, half tucked beneath his thigh as though he'd tried to hide it or tried to hold onto it at the last. She lifted it carefully with a gloved finger and the scene photographer moved in, flash cracking like a whip. A compass. Small, brass, green with verdigris, the face etched with tiny marks that made Quinn's eyes water when she tried to focus on them. The needle wasn't pointing north. It was pointing down the platform, dead steady, toward the tunnel mouth. "Give that here," Ferris said, holding out an evidence bag. She dropped it in. Through the plastic, the needle swung — she watched it swing — and settled again, pointing the same direction. She turned the bag a quarter circle in her hand. The needle corrected. Pointing at the tunnel. "Broken," Ferris said. "Compasses don't break toward things." "So it's magnetised. There's iron in the tunnel, rails, old cabling—" "Then it would point at the rails under our feet." She sealed the bag and initialled it, her leather watch strap creaking against her wrist, and kept her face empty of everything she was feeling, which was a cold and patient recognition. Three years since Morris. Three years since a warehouse in Deptford and a report she'd written with holes in it shaped like the truth, and the unexplained had a smell, she had decided long ago. It smelled like this. Incense and old stone. "Here's what happened," Ferris said, gently, the way you'd talk someone off a ledge. "Bloke with money has a hobby. Urban explorer, collector, whatever. He found an access we haven't. He came down here at night with his little antique, his heart gave out — middle-aged men, it happens every day — and he sat down against the wall and died. The strange stuff is strange because places like this are strange. That's all of it." Quinn looked at the dead man's attentive eyes. "Then why is there wax on his sleeves?" "What?" She pointed. Two small dark drips on the right cuff of the good coat, and a smear of it on the left. "He was carrying candles. Two of them, one in each hand, held out to the sides as he walked — that's how you get wax on both cuffs. He walked down that tunnel in the dark carrying candles, Ferris, toward this platform, and then he sat down and put his palms up, and he waited." She looked at the sigils again, spaced at intervals along the wall like markers. Like a route. "He wasn't exploring. He was arriving. This is a doorway dressed up as a crime scene, and whatever he was waiting for, I think it came." Ferris opened his mouth and closed it again. Behind him, one of the scene lamps flickered, and Quinn could have sworn — she would never put it in a report, never say it aloud — that the darkness at the tunnel mouth breathed in. "Bag the wax," she said. "Swab his palms. And I want to know what he was listening for."
created_at"2026-07-25T17:35:07.402Z" 7/25/2026, 5:35:07 PM
model"moonshotai/kimi-k3-20260715"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3959
moderation_latency(null)
generation_time70834
tokens_prompt896
tokens_completion1900
native_tokens_prompt933
native_tokens_completion1714
native_tokens_completion_images(null)
native_tokens_reasoning54
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)
usage0.0264354
router(null)
provider_responses
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endpoint_id"650c9b12-7b6d-444d-8d92-df8daef84d7a"
id"chatcmpl-6a64f3ba967b8ab62c55dc74"
is_byokfalse
latency3959
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-1785000907-sO8duI8G4IARUvwWNeww"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1785000907-WDtL67M5e5Q0K0Xn4Mm0"
upstream_id"chatcmpl-6a64f3ba967b8ab62c55dc74"
total_cost0.0264354
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
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags12
adverbTagCount1
adverbTags
0"Quinn stood slowly [slowly]"
dialogueSentences38
tagDensity0.316
leniency0.632
rawRatio0.083
effectiveRatio0.053
80.28% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1268
totalAiIsmAdverbs5
found
0
adverb"very"
count1
1
adverb"slowly"
count1
2
adverb"reluctantly"
count1
3
adverb"carefully"
count1
4
adverb"gently"
count1
highlights
0"very"
1"slowly"
2"reluctantly"
3"carefully"
4"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)
88.17% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1268
totalAiIsms3
found
0
word"methodical"
count1
1
word"etched"
count1
2
word"flickered"
count1
highlights
0"methodical"
1"etched"
2"flickered"
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
narrationSentences58
matches(empty)
44.33% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount3
narrationSentences58
filterMatches
0"watch"
hedgeMatches
0"seemed to"
1"tried to"
95.24% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences84
gibberishSentences1
adjustedGibberishSentences1
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount1
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen68
ratio0.012
matches
0"\"Nasty one. No visible wounds, no blood, nothing. Doc's guess is cardiac arrest. Rough sleeper wandered down here, ticker gave out.\""
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1280
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions10
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions26
wordCount761
uniqueNames9
maxNameDensity1.18
worstName"Ferris"
maxWindowNameDensity2.5
worstWindowName"Ferris"
discoveredNames
Camden1
Harlow1
Quinn7
Birmingham1
Ferris9
Three3
Morris1
Deptford1
Like2
persons
0"Harlow"
1"Quinn"
2"Ferris"
3"Morris"
places
0"Birmingham"
1"Deptford"
globalScore0.909
windowScore0.833
18.42% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences38
glossingSentenceCount2
matches
0"paint that seemed to swallow the scene lamps rather than reflect them"
1"as if waiting for a train that would never come"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1280
matches(empty)
87.30% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount2
totalSentences84
matches
0"were that oxblood"
1"called that a"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs38
mean33.68
std31.32
cv0.93
sampleLengths
091
18
221
33
4109
518
661
751
835
95
109
1150
128
1354
1429
1556
1610
178
1834
191
2013
2145
2212
237
2471
2542
2610
2740
283
295
3011
3185
3276
3316
341
35120
3644
3718
99.21% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences58
matches
0"been closed"
1"being remembered"
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs132
matches
0"was listening"
1"was waiting"
2"wasn't pointing"
3"was pointing"
4"was feeling"
6.80% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount6
semicolonCount0
flaggedSentences4
totalSentences84
ratio0.048
matches
0"The station had been closed since before she was born — one of those wartime casualties the city had simply bricked over and forgotten, though forgotten places had a way of being remembered by the wrong people."
1"Male, late thirties, well dressed — good coat, good shoes, a wedding band."
2"Through the plastic, the needle swung — she watched it swing — and settled again, pointing the same direction."
3"Behind him, one of the scene lamps flickered, and Quinn could have sworn — she would never put it in a report, never say it aloud — that the darkness at the tunnel mouth breathed in."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount758
adjectiveStacks0
stackExamples(empty)
adverbCount26
adverbRatio0.03430079155672823
lyAdverbCount7
lyAdverbRatio0.009234828496042216
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences84
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences84
mean15.24
std14.13
cv0.927
sampleLengths
035
14
252
34
44
521
63
711
837
929
103
118
1221
1318
1413
152
162
1732
1812
1919
2023
219
2214
2321
245
259
2639
2711
283
295
3031
3123
3229
3315
3441
357
363
378
383
3921
407
413
421
4313
448
4537
4612
477
4810
4913
88.49% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.5595238095238095
totalSentences84
uniqueOpeners47
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences51
matches(empty)
ratio0
86.67% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount17
totalSentences51
matches
0"She ducked the crime scene"
1"She pulled on gloves and"
2"His hands rested in his"
3"He was a solid man,"
4"He straightened up, wincing at"
5"She crouched beside the body"
6"She lifted her gaze along"
7"He did, reluctantly."
8"She kept her voice level"
9"She turned back to the"
10"She lifted it carefully with"
11"It was pointing down the"
12"She dropped it in."
13"She turned the bag a"
14"She sealed the bag and"
15"It smelled like this."
16"She looked at the sigils"
ratio0.333
77.65% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount39
totalSentences51
matches
0"The stairs down to the"
1"Incense and old stone."
2"She ducked the crime scene"
3"She pulled on gloves and"
4"The station had been closed"
5"The tiles along the curved"
6"Quinn had seen enough gang"
7"These were careful, symmetrical, almost"
8"The body sat propped against"
9"His hands rested in his"
10"DS Ferris was waiting for"
11"He was a solid man,"
12"He straightened up, wincing at"
13"She crouched beside the body"
14"Ferris leaned in."
15"She lifted her gaze along"
16"Quinn stood slowly, looking at"
17"Ferris rubbed the back of"
18"He did, reluctantly."
19"The beam struck the nearest"
ratio0.765
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences51
matches(empty)
ratio0
0.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences24
technicalSentenceCount5
matches
0"The stairs down to the old Camden passage smelled of wet concrete and something sweeter underneath, something that put Harlow Quinn in mind of a church her gran…"
1"She ducked the crime scene tape at the bottom of the steps and held her warrant card up to the uniform posted there, a boy who couldn't have been more than twen…"
2"These were careful, symmetrical, almost calligraphic, rendered in a paint that seemed to swallow the scene lamps rather than reflect them."
3"He was a solid man, methodical, the kind of detective who wrote everything down and trusted the paperwork more than his own eyes."
4"Something glinted against the dead man's left hand, half tucked beneath his thigh as though he'd tried to hide it or tried to hold onto it at the last."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences38
tagDensity0.132
leniency0.263
rawRatio0
effectiveRatio0
75.1968%