Run: 2026-07-09-01KX40JY1KMXTN06GYPENT8PYV

Run Details

Duration:
10.9s
Cost:
$0.011455
Provider:
OpenAI

Model input

System
You are an expert fiction writer. Always keep the following rules in mind: - Write in past tense and use General English spelling, grammar, and colloquialisms/slang. - Write in active voice - Always follow the "show, don't tell" principle. - Avoid adverbs and cliches and overused/commonly used phrases. Aim for fresh and original descriptions. - Convey events and story through dialogue. - Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. - Skip "he/she said said" dialogue tags and convey people's actions or face expressions through their speech - Avoid mushy dialog and descriptions, have dialogue always continue the action, never stall or add unnecessary fluff. Vary the descriptions to not repeat yourself. - Put dialogue on its own paragraph to separate scene and action. - Reduce indicators of uncertainty like "trying" or "maybe" When writing text: - NEVER conclude the scene on your own, follow the beat instructions very closely. - NEVER end with foreshadowing. - NEVER write further than what I prompt you with. - AVOID imagining possible endings, NEVER deviate from the instructions. - STOP EARLY if the continuation contains what was required in the instructions. You do not need to fill out the full amount of words possible.
User/Human
Take into account the following glossary of characters/locations/items/lore... when writing your response: <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> Continue the story using the following instructions: <instructions> 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. </instructions>

Model response

AI
Detective Harlow Quinn ducked beneath the yellow tape and entered the abandoned Tube station. The air tasted of rust, wet stone and something sweet that had spoiled beneath the ground. A single work lamp burned beside the old ticket booth, throwing hard shadows across cracked tiles. Beyond it, the platform stretched into darkness. The tracks had vanished beneath a skin of black water. Uniformed officers stood in a loose ring around the body. Quinn counted them before she looked at the corpse. Four constables. One forensic photographer. Sergeant Vale, who had arrived before her and now held a paper cup in both hands. No civilians. No obvious witnesses. Her leather watch showed 2:17 a.m. “Who found him?” Vale lifted his chin towards the tracks. “Patrol heard shouting from the access tunnel. Came down and found the victim on the platform. We secured the station and called you.” “You heard shouting?” “Three voices. A man, two women.” Quinn’s brown eyes moved over the platform. “And you found one man.” “People ran before the patrol reached the stairs.” “Through the sealed station?” Vale glanced at the tiled wall behind him. “There’s an old service passage. We found footprints.” Quinn stepped closer to the body. The dead man lay on his back beside the ticket machine, one arm flung above his head. He wore a dark overcoat, polished shoes and a silver signet ring. Blood had spread beneath his skull, but none had reached the collar of his coat. His eyes stared at the ceiling. His mouth hung open. A brass compass rested on his chest. Quinn crouched. The little instrument bore a crust of green verdigris along its casing. Protective sigils covered the face in tight, unfamiliar strokes. Its needle trembled, swung east, then settled towards the dark tunnel. Vale shifted beside her. “Robbery,” he said. “The ring’s still there, but the wallet’s gone. Whoever did it struck him from behind, took the cash and ran.” Quinn touched the edge of the blood pool with a gloved finger. It had dried in a narrow fan beneath the victim’s head. “From behind?” “The wound’s at the back of the skull.” “Then why did he fall facing the ticket booth?” Vale frowned. “He fell where he fell.” Quinn pointed to the victim’s shoes. Both soles carried a thin glaze of pale mud. The platform around him held only dust and flaking paint. None of that mud appeared beneath his heels. “He was dragged,” she said. “Dragged from the tunnel.” “No.” She studied the body. “Dragged towards it.” Vale’s cup creaked in his grip. “The feet point towards the tunnel.” “His shoulders don’t. Someone pulled him by the ankles, then turned him over.” “Why?” Quinn looked at the compass. The needle quivered again. It did not point towards the tunnel now. It pointed straight down. “Where’s the wallet?” she asked. “One of the officers bagged it.” “Show me.” A constable crossed the platform and handed over a clear evidence pouch. Inside lay a black leather wallet, empty except for a library card and two train tickets. Quinn held it beneath the lamp. The leather had swollen from damp, but the inner folds remained dry. “Where did you find this?” “Under the victim’s left hand.” “His hand was closed?” “No, Detective.” Quinn looked back at the corpse. The fingers rested open against the tile, palm upward. Vale raised both hands. “He could’ve dropped it.” “Then why did the thief leave the ring?” “Panic.” “Why take cash and leave identification?” “Panic.” “Why drag the body towards the tunnel, turn it over, place the wallet beneath his hand and set a compass on his chest?” Vale stared at her. “You think the compass means something?” “I think someone wanted us to find it.” She reached for the instrument. The forensic photographer took one last picture, then nodded. The brass felt warm through her glove. Quinn withdrew her hand. Behind the ticket booth, a line of water slipped along the wall and disappeared beneath the tiles. She followed it with her gaze. It ran uphill. “Sergeant,” she said, “how long has this platform been closed?” “Since the fire in ’89.” “No power?” “Not for decades.” “Yet the work lamp runs.” Vale looked towards the lamp. “Portable generator.” “Where is it?” He turned. The officers turned with him. The generator stood beside the stairs, its fuel tank sealed, its cable trailing towards the lamp. The plug did not connect to anything. One of the constables swore under his breath. Quinn rose. Her sharp jaw tightened as she examined the lamp. Its bulb glowed without heat. Frost coated the metal cage. “Everyone out,” she ordered. Vale blinked. “The scene isn’t finished.” “Out of the station.” “We’ve got a dead man.” “We’ve got a dead man in a station that has no electricity, footprints that lead in the wrong direction and a compass pointing through solid ground.” Vale’s mouth tightened. “You’re making this theatrical.” Quinn faced him. “Your men heard three voices. Did any of them hear footsteps?” He looked towards the constables. None answered. Quinn walked to the sealed service passage. Bricks filled the arch from floor to ceiling, their mortar black with age. A strip of yellow tape fluttered across it, though no air moved in the station. She crouched near the floor. The footprints began two metres from the wall. They crossed the dust in a neat line: one set of boot marks, narrow and deep, leading towards the body. Then a second set appeared beside them, smaller, the soles shaped like old-fashioned women’s shoes. Both trails stopped at the bricks. Neither returned. Vale came up behind her. “There’s a gap somewhere.” “Search it.” “We already did.” “Search it again.” The nearest constable pulled a torch from his belt and swept the beam across the wall. Quinn watched the dust. A faint shimmer ran between two bricks, a vertical seam too straight for ordinary settling. She reached out and pressed her palm against the masonry. The temperature dropped. For one instant, she smelled smoke and heard a man shouting her name. Morris. Quinn snatched her hand back. Her watch stopped at 2:17. Vale noticed. “Problem?” She forced her wrist down. “Your torch.” The constable raised it. “Not that one. Give me the light from the ticket booth.” “It’s battery-powered,” Vale said. “Give it to me.” He fetched the lamp. Its cold glow spilled across the wall, and the hidden seam sharpened. Symbols appeared in the mortar, scratched beneath layers of soot. They matched the markings on the compass. The needle began to spin. Quinn lifted the instrument from the body with a pair of forceps. The lid snapped open by itself. Inside, beneath the needle, a dark liquid moved like ink in water. Vale stepped back. “What is that?” “Evidence.” “That’s not an answer.” “No. It’s the only one you’re getting until I know what we’re looking at.” The wall clicked. A brick slid inward. Behind it waited a narrow passage, though no space could have existed beyond the solid foundation. Pale blue light pulsed in the darkness. The air carried the scent of rain on hot pavement, though the station lay beneath Camden and the night above remained dry. Quinn held the compass out. The needle pointed into the passage. Then she looked at the dead man. A faint line of black grit marked his throat. Not bruising. Not dirt. A pattern of tiny crescent shapes, pressed into the skin as though something with hooked fingers had gripped him. The victim’s silver ring bore a crest: a crowned eye surrounded by flames. Quinn had seen it before. Three years earlier, beside the body of DS Morris. Vale touched her elbow. “Detective?” Quinn pulled free. “Get the officers upstairs. Seal every entrance. No one enters this station until I return.” “Return from where?” She stepped towards the impossible passage, compass clenched in her hand. “From finding out who killed him.” The blue light flickered across her face. The wall behind her began to close.
created_at"2026-07-09T18:00:08.008Z" 7/9/2026, 6:00:08 PM
model"openai/gpt-5.6-luna-20260709"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency536
moderation_latency(null)
generation_time10145
tokens_prompt1149
tokens_completion2302
native_tokens_prompt1009
native_tokens_completion1741
native_tokens_completion_images0
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"completed"
service_tier"default"
usage0.011455
router(null)
provider_responses
0
endpoint_id"eebea444-34a5-4642-a766-cb319471d33a"
id"resp_0400278fcecc55ea016a4fe1a81d048194afdbc690a7e16059"
is_byokfalse
latency263
model_permaslug"openai/gpt-5.6-luna-20260709"
provider_name"OpenAI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1783620008-YLfL84ICZzC25CFvzhAp"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1783620008-zzcpbm6MKkLkjhYWomAq"
upstream_id"resp_0400278fcecc55ea016a4fe1a81d048194afdbc690a7e16059"
total_cost0.011455
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"
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
totalTags7
adverbTagCount0
adverbTags(empty)
dialogueSentences67
tagDensity0.104
leniency0.209
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1335
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)
77.53% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1335
totalAiIsms6
found
0
word"trembled"
count1
1
word"quivered"
count1
2
word"footsteps"
count1
3
word"fluttered"
count1
4
word"pulsed"
count1
5
word"flickered"
count1
highlights
0"trembled"
1"quivered"
2"footsteps"
3"fluttered"
4"pulsed"
5"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
narrationSentences128
matches(empty)
98.21% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount2
narrationSentences128
filterMatches
0"watch"
hedgeMatches
0"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences188
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen26
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1335
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
44.96% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions41
wordCount952
uniqueNames6
maxNameDensity2.1
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn20
Tube1
Vale16
Camden1
Morris2
persons
0"Harlow"
1"Quinn"
2"Vale"
3"Morris"
places(empty)
globalScore0.45
windowScore0.667
80.56% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences72
glossingSentenceCount2
matches
0"appeared beneath his heels"
1"appeared beside them, smaller, the soles shaped like old-fashioned women’s shoes"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1335
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences188
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs125
mean10.68
std10.64
cv0.996
sampleLengths
014
149
210
39
426
56
63
730
83
96
1012
118
124
1316
146
1554
167
172
1832
194
2023
2123
222
238
249
257
2633
275
284
298
3012
3113
321
335
3416
355
366
372
3828
3918
405
415
424
432
4415
458
468
471
486
491
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences128
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs163
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences188
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount953
adjectiveStacks0
stackExamples(empty)
adverbCount13
adverbRatio0.013641133263378805
lyAdverbCount1
lyAdverbRatio0.001049317943336831
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences188
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences188
mean7.1
std4.97
cv0.7
sampleLengths
014
116
216
37
410
510
69
72
83
916
102
113
126
133
147
1523
163
176
187
195
208
214
228
238
246
2517
2612
2715
286
294
307
312
3212
339
3411
354
363
3720
3812
3911
402
418
429
432
445
456
469
4710
488
495
52.84% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.34574468085106386
totalSentences188
uniqueOpeners65
91.74% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences109
matches
0"Then a second set appeared"
1"Pale blue light pulsed in"
2"Then she looked at the"
ratio0.028
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount24
totalSentences109
matches
0"Her leather watch showed 2:17"
1"He wore a dark overcoat,"
2"His eyes stared at the"
3"His mouth hung open."
4"Its needle trembled, swung east,"
5"It had dried in a"
6"She studied the body"
7"It did not point towards"
8"It pointed straight down."
9"She reached for the instrument."
10"She followed it with her"
11"It ran uphill."
12"Her sharp jaw tightened as"
13"Its bulb glowed without heat."
14"He looked towards the constables."
15"She crouched near the floor."
16"They crossed the dust in"
17"She reached out and pressed"
18"Her watch stopped at 2:17."
19"She forced her wrist down."
ratio0.22
28.81% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount94
totalSentences109
matches
0"Detective Harlow Quinn ducked beneath"
1"The air tasted of rust,"
2"A single work lamp burned"
3"The tracks had vanished beneath"
4"Quinn counted them before she"
5"Sergeant Vale, who had arrived"
6"Her leather watch showed 2:17"
7"Vale lifted his chin towards"
8"Quinn’s brown eyes moved over"
9"Vale glanced at the tiled"
10"Quinn stepped closer to the"
11"The dead man lay on"
12"He wore a dark overcoat,"
13"Blood had spread beneath his"
14"His eyes stared at the"
15"His mouth hung open."
16"A brass compass rested on"
17"The little instrument bore a"
18"Its needle trembled, swung east,"
19"Vale shifted beside her."
ratio0.862
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences109
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences36
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount1
fancyTags
0"she ordered (order)"
dialogueSentences67
tagDensity0.09
leniency0.179
rawRatio0.167
effectiveRatio0.03
89.1548%