Run: 2026-09-23-01M37HNBE40F417CB5NWQP8NTV

Run Details

Duration:
1m 5s
Cost:
$0.031420
Provider:
OpenAI

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 last train through the station had run twenty-three years ago. Someone had swept the platform that morning. Harlow Quinn stopped at the foot of the service stairs and looked down the long curve of pale tiles. Beyond the police lamps, darkness swallowed the rails. The air smelled of wet stone, old electricity, and something sweeter she couldn’t place. “Council crew?” she asked. DS Patel followed her gaze. “No scheduled works. We checked.” The clean strip ran from the bottom of the stairs to a yellow line painted at the platform edge. Dust lay thick everywhere else, especially beneath the benches and along the tracks. Whoever had swept had done it carefully, and only where people would walk. A man lay on his side six feet from the edge, one arm folded under him. His coat was open. Blood had dried in his close-cropped hair. “Arthur Bell,” Patel said. “Forty-eight. Dealer in antiquities, according to the business cards. No phone, no wallet. We’ve got a possible fall from the old signal gantry. Dr Shah says the head wound could be consistent.” Quinn looked up. The gantry crossed the tracks twelve feet above them, its ironwork furred with rust. “Who found him?” “A woman from the British Museum. Eva Kowalski. Says Bell called her last night, asked her to meet him here. She came at six, found the body, called us.” “Here?” “Apparently they had business.” That covered very little. Quinn stepped around the body, keeping clear of the numbered markers set by the scene examiner. Bell wore an expensive wool coat, cheap black shoes, and trousers with a wet patch at one knee. His shoes were clean. Not polished—clean in the particular way shoes looked after a walk on dry pavement. She crouched. Patel’s interpretation had the virtue of being ordinary. Bell had climbed the gantry, fallen, and someone had taken his valuables. An abandoned station offered privacy for either a deal or a killing. But there was rust on the gantry and none on Bell’s hands. “Has Shah moved him?” “Only to confirm death.” Quinn leaned closer. A small brass compass rested inside Bell’s open palm. Green corrosion marked its casing; protective symbols, or what looked like them, had been scratched around its face. The needle pointed across the platform toward a wall tiled in cream and brown. “Robber missed that,” she said. “Could be worthless.” “Bell didn’t think so.” His fingers had curled around the compass hard enough to leave their shape impressed in his palm. “What’s behind that wall?” “An old staff passage. Bricked up when they closed the station.” Quinn stood and checked her worn leather watch. Seven eighteen. Forensics would want Bell moved soon. She wanted the platform as it was for another five minutes. “Show me where Kowalski is.” They had put her in the former ticket office. Eva Kowalski sat on a folding chair beneath a cracked route map, a worn leather satchel at her feet. Books strained its seams. She had round glasses, curly red hair, and the watchful expression of someone trying not to look at the platform through the open door. She rose when Quinn entered. “Detective Quinn. DS Patel says you work in the museum’s restricted archives.” “I’m a research assistant.” Eva tucked a curl behind her left ear. “Arthur asked me to identify something.” “The compass?” Eva’s green eyes moved past Quinn to Patel. “Did he have it?” “Yes.” “He showed me a photograph. I hadn’t seen the object itself.” “What did you tell him about the photograph?” “That I couldn’t identify it from one picture.” Quinn waited. Eva took off her glasses and wiped them on the hem of her cardigan, though the lenses were clean. “Mr Bell said it came from a private collection,” she added. “Did he say why he wanted to meet in an abandoned Tube station?” “He said no one would bother us.” “That part he got wrong.” Eva put her glasses back on. Her freckles stood out against pale skin. “I know how it sounds.” “You’re not the first person to meet a dealer somewhere peculiar. What time did you arrive?” “About six. Just after.” “And you found him where he is now?” “Yes.” “Did you touch him?” “I checked for a pulse.” “Did you touch the compass?” “No.” Quinn nodded, then looked at the satchel. “Mind if I see the books?” Eva’s hand closed around the strap. “They’re mine.” “I’m asking.” After a moment, she opened it. Two academic hardbacks, a notebook, a pencil case. No obvious blood. No dust from the platform on the satchel’s bottom, either; she had kept it on her shoulder or held it off the floor. Patel’s radio hissed at his hip. He stepped into the corridor to answer it. Quinn said, “You expected him to be alive.” “Of course.” “You brought your research with you.” Eva glanced down at the books. “He wouldn’t say what else he had.” “What else?” Her mouth tightened. For a second Quinn thought she might answer. Then Patel returned. “Doc wants the body released as soon as we’re done with the scene.” “We’re not done,” Quinn said. Back on the platform, the examiner was photographing Bell’s hands. Quinn asked him for a close shot of the left cuff and waited while he took it. The wet patch on Bell’s trouser knee had begun to dry at the edges, leaving a faint tide mark. Beneath it clung a grain of yellow grit. There was no yellow grit on the platform. Its concrete was grey and smooth. She walked toward the tiled wall, following the direction of the compass needle. The swept path narrowed there, ending at what appeared to be a strip of shadow between a tiled pillar and an advertisement board. The poster advertised a theatre production that had closed decades earlier. Its paper was brittle, but one lower corner had been pressed flat by a fresh thumb. Quinn put her light against the gap. Behind the board stood an iron door, painted the same brown as the tile border. No handle on this side. “Patel.” He came over. “I saw the board. Old maintenance access. Sealed.” “Why sweep up to a sealed door?” He looked from the clean floor to the poster. “Someone using it as a shelter?” “Possibly.” She bent. At the foot of the door was a shallow recess where the floor met the frame. Fresh blood had collected in it, dark and tacky. The smear was no wider than the edge of a coat hem. Patel crouched beside her. “Bell was moved.” “From this side or the other?” “If there’s an other side.” Quinn straightened and swept her light over the wall. Scratches ringed a small circular hollow in the iron, almost hidden beneath a flake of paint. A coin slot, perhaps, though too wide and shallow for any coin she knew. More yellow grit was caught in its lower lip. She remembered Bell’s clean shoes and his damp knee. He had knelt somewhere wet and gritty, then walked—or been brought—through the door. The blow to his head might still have come from a fall, but not from the gantry. “Get this photographed,” she said. “And find out who sealed it.” Behind them, Eva said, “They won’t have a record.” Quinn turned. Eva stood several yards away, on the clean strip, with a uniformed constable just behind her. She must have asked to come out. She stared at the door as if it might open. “You know the station?” Quinn asked. “No.” Eva swallowed. “I mean, records from before the closure are incomplete.” “Of this particular door?” “I didn’t say that.” Quinn looked down at Eva’s shoes. Their soles were edged with yellow grit. Patel saw it too. “Miss Kowalski, did you go through here?” “No.” “Then where did you pick that up?” Eva looked at her feet. Her left hand rose toward her ear and stopped halfway. “There’s grit on the stairs.” “There isn’t,” Quinn said. She had watched every step on her way down. “You found Bell at six, called the police, and told them he was on the platform. When were you going to tell us where you’d been before that?” Eva said nothing. The examiner called from beside the body. “Detective? There’s something else in his coat.” Quinn walked back. He had opened the inner pocket for the photographs. Inside lay a small disc of bone, pierced near one edge, its surface worn smooth by handling. A dark thread ran through the hole. “Not his wallet, then,” Patel said. Quinn studied the disc without touching it. Its rim was stained the same yellow as the grit in the door’s recess. Behind her, Eva made a sound—no more than a breath drawn too sharply. “What is it?” Quinn asked. “I don’t know.” For a moment Quinn heard another voice in another tunnel. Morris, three years ago, telling her over the radio that he’d found a way in. By the time she reached him, there had been no doorway where he said there was one. Only a wall, his dropped radio, and a line of wet footprints that ended against the tiles. She pushed the memory aside. Morris was gone. Bell was in front of her. “Photograph the disc in place,” she told the examiner. “Then bag it separately.” A dull click came from behind the advertisement board. Everyone turned. The iron door had shifted inward a fraction, enough for a thread of warm air to reach the platform. With it came that sweet smell again, sharper now: hot sugar over something bitter and metallic. Patel put a hand on his radio. Eva had gone very still. Quinn kept her eyes on the gap. She could hear footsteps beyond it, more than one set, moving away across a floor that sounded tiled. Then a voice called something she couldn’t make out, and the door began to close. “Hold it,” Quinn said. Patel lunged for the edge. Quinn reached it first and drove her shoulder into the iron. It gave an inch. Light showed through—amber light, shifting with the movement of people on the other side. Then the door slammed against her. Quinn staggered back. The painted edge settled flush with the frame, and the platform went quiet. Patel stared at the wall. “That passage isn’t sealed.” “No,” Quinn said. She looked at the compass in Bell’s palm. Its needle still pointed straight at the door.
created_at"2026-09-23T16:30:27.279Z" 9/23/2026, 4:30:27 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency11458
moderation_latency(null)
generation_time64715
tokens_prompt896
tokens_completion2972
native_tokens_prompt835
native_tokens_completion2975
native_tokens_completion_images0
native_tokens_reasoning752
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"completed"
service_tier"default"
usage0.03142
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790181027-iG3X4MQ1u7Dxtgw2gOwx"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790181027-OqphIMiw3t6hd60qPeA8"
upstream_id"resp_0c6ecc95122e2bba016ab3fea362a087d186ad6344716d51f3"
provider_responses
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endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_0c6ecc95122e2bba016ab3fea362a087d186ad6344716d51f3"
is_byokfalse
latency1835
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.03142
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags18
adverbTagCount0
adverbTags(empty)
dialogueSentences79
tagDensity0.228
leniency0.456
rawRatio0
effectiveRatio0
88.55% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1746
totalAiIsmAdverbs4
found
0
adverb"carefully"
count1
1
adverb"very"
count2
2
adverb"sharply"
count1
highlights
0"carefully"
1"very"
2"sharply"
80.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found
0"Patel"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
94.27% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1746
totalAiIsms2
found
0
word"pulse"
count1
1
word"footsteps"
count1
highlights
0"pulse"
1"footsteps"
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
narrationSentences144
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences144
filterMatches
0"watch"
hedgeMatches
0"appeared to"
1"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences205
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen32
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1741
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions28
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions66
wordCount1281
uniqueNames5
maxNameDensity2.19
worstName"Quinn"
maxWindowNameDensity4
worstWindowName"Quinn"
discoveredNames
Quinn28
Patel12
Bell10
Kowalski1
Eva15
persons
0"Quinn"
1"Patel"
2"Bell"
3"Kowalski"
4"Eva"
places(empty)
globalScore0.407
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences97
glossingSentenceCount1
matches
0"looked like them, had been scratched arou"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1741
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences205
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs110
mean15.83
std15.05
cv0.951
sampleLengths
018
141
24
310
445
527
636
717
83
929
101
114
1256
1334
1412
154
164
1744
185
193
2025
2111
2227
235
2456
255
2612
2718
282
2912
301
3111
328
338
3421
3511
3613
377
385
3918
4016
414
428
431
444
455
465
471
4813
498
88.21% Passive voice overuse
Target: ≤2% passive sentences
passiveCount7
totalSentences144
matches
0"been scratched"
1"been pressed"
2"was caught"
3"been brought"
4"were edged"
5"was stained"
6"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs215
matches
0"was photographing"
59.23% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount5
semicolonCount2
flaggedSentences6
totalSentences205
ratio0.029
matches
0"Not polished—clean in the particular way shoes looked after a walk on dry pavement."
1"Green corrosion marked its casing; protective symbols, or what looked like them, had been scratched around its face."
2"No dust from the platform on the satchel’s bottom, either; she had kept it on her shoulder or held it off the floor."
3"He had knelt somewhere wet and gritty, then walked—or been brought—through the door."
4"Behind her, Eva made a sound—no more than a breath drawn too sharply."
5"Light showed through—amber light, shifting with the movement of people on the other side."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1288
adjectiveStacks0
stackExamples(empty)
adverbCount37
adverbRatio0.02872670807453416
lyAdverbCount6
lyAdverbRatio0.004658385093167702
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences205
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences205
mean8.49
std5.73
cv0.675
sampleLengths
011
17
219
38
414
54
65
75
819
913
1013
1116
124
137
144
1532
163
1714
183
1929
201
214
224
2316
2418
254
2614
272
288
2912
3012
3112
324
334
343
359
3618
3714
385
393
4021
414
4211
438
442
456
4611
475
489
4919
62.60% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.3902439024390244
totalSentences205
uniqueOpeners80
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount5
totalSentences124
matches
0"Then Patel returned."
1"More yellow grit was caught"
2"Only a wall, his dropped"
3"Then a voice called something"
4"Then the door slammed against"
ratio0.04
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount30
totalSentences124
matches
0"His coat was open."
1"His shoes were clean."
2"His fingers had curled around"
3"She wanted the platform as"
4"They had put her in"
5"She had round glasses, curly"
6"She rose when Quinn entered."
7"Her freckles stood out against"
8"He stepped into the corridor"
9"Her mouth tightened."
10"Its concrete was grey and"
11"She walked toward the tiled"
12"Its paper was brittle, but"
13"He came over."
14"He looked from the clean"
15"She remembered Bell’s clean shoes"
16"He had knelt somewhere wet"
17"She must have asked to"
18"She stared at the door"
19"Their soles were edged with"
ratio0.242
72.90% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount96
totalSentences124
matches
0"The last train through the"
1"Someone had swept the platform"
2"Harlow Quinn stopped at the"
3"The air smelled of wet"
4"DS Patel followed her gaze."
5"The clean strip ran from"
6"Dust lay thick everywhere else,"
7"A man lay on his"
8"His coat was open."
9"Blood had dried in his"
10"Quinn looked up."
11"The gantry crossed the tracks"
12"That covered very little."
13"Quinn stepped around the body,"
14"Bell wore an expensive wool"
15"His shoes were clean."
16"Patel’s interpretation had the virtue"
17"Bell had climbed the gantry,"
18"An abandoned station offered privacy"
19"Quinn leaned closer."
ratio0.774
80.65% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences124
matches
0"Whoever had swept had done"
1"By the time she reached"
ratio0.016
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences52
technicalSentenceCount2
matches
0"Only a wall, his dropped radio, and a line of wet footprints that ended against the tiles."
1"She could hear footsteps beyond it, more than one set, moving away across a floor that sounded tiled."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags18
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags15
fancyCount1
fancyTags
0"she added (add)"
dialogueSentences79
tagDensity0.19
leniency0.38
rawRatio0.067
effectiveRatio0.025
91.9914%