Run: 2026-07-09-01KX40668R90SHJZ9AV7TMF3AS

Run Details

Duration:
33.9s
Cost:
$0.043068
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
The dead man sat in the driver’s seat of a Circle Line train, hands folded over his stomach as if someone had posed him for a photograph. Detective Harlow Quinn stood on the platform beneath Camden, one boot planted beside a puddle that reflected the cracked station clock. It had stopped at 2:17. The second hand shivered once, then dragged itself back three marks. The abandoned station smelled of wet brick, coal dust, and something sweet that caught at the back of her throat. Stalls crowded the old platform under strings of green glass lamps. A woman with antlers sold stoppered jars from an old luggage trolley. A boy with no shadow stacked rows of silver teeth onto black velvet. Beyond them, the train waited with its doors open, its interior lights bleeding a weak yellow onto the rails. Quinn glanced at the constable blocking the stairwell. “No press. No curious patrols. Nobody touches a thing.” The constable swallowed. “Already had a few traders asking when they can get back inside.” “Tell them the station stays shut until I’m done.” “They don’t appear to accept instructions much, ma’am.” Quinn looked past him. A tall man in a mourning coat leaned behind a stall of bottled smoke. His pale eyes tracked her without blinking. A woman with a snake coiled around her throat held a bone token between two fingers and watched it darken. “They will.” She crossed the platform. Her leather watch sat warm against her wrist, though the station air had a winter bite. 3:42. The hands moved properly on her watch. Unlike the station clock. Unlike half the clocks she had found in rooms where the impossible had left its fingerprints. DS Morris had joked about that once. Called it a ghost’s bad habit. Three days later, they had pulled his body from the Thames without a drop of water in his lungs. Quinn stepped into the train carriage. A uniformed officer stood near the door, pale beneath the fluorescent lights. He had put blue shoe covers over his boots. The dead man had not received the same courtesy. Mud streaked the soles of his polished shoes. Fine red grit dusted the hem of his trousers. “Name?” “Lucas Bell, ma’am. Forty-eight. No fixed address on the system, though the wallet says he rented a flat in Kentish Town.” The officer pointed with a gloved hand. “Wallet, keys, phone, all present. No obvious weapon. We found him at six thirty when the Market opened.” “Market opened at six thirty?” The officer shifted. “That’s what they call it.” “They sell cursed objects and bottled nightmares under a railway platform. I’m familiar with the word.” A throat cleared behind her. Eva Kowalski stood at the carriage entrance, hugging a worn leather satchel against her ribs. Her curly red hair had escaped its clip in all directions, and rain had darkened the shoulders of her wool coat. Round glasses magnified her green eyes. “You didn’t call me,” Eva said. “I called the Metropolitan Police.” “And they called a unit that didn’t know a curse from a kettle. So someone called me.” Quinn looked towards the platform. The officer had found sudden interest in a patch of peeling station paint. Eva reached into her satchel, produced a handkerchief, and held it over her nose. “That smell is grave sugar.” “Useful?” “Used in binding rites. Sometimes to preserve a body. Sometimes to make a body look preserved.” Quinn turned back to Lucas Bell. His skin held the waxy, blue-grey cast of someone who had been dead for hours. Yet his shirt collar remained crisp. No blood marked the white cotton. No bruises shadowed his jaw. His eyes had been closed. “Cause of death?” “Pathologist’s on the way.” “You’ve had a look.” Eva gave the body a hard stare. “I’ve read books. That is not the same thing.” “Books keep finding themselves near scenes like this.” “They’re more reliable than people.” Quinn crouched beside the driver’s seat. Bell’s hands rested one over the other. His nails were clean. His left cuff had torn loose from its button, and a faint black stain marked the skin beneath his wrist. Not ink. Not dirt. It had the sheen of scorched oil. She leaned closer. The dead man’s watch had stopped at 2:17. Quinn’s jaw tightened. “What?” Eva moved nearer, then caught herself at the edge of the carriage. “You found something.” “His watch stopped at the same time as the station clock.” “That might mean he died at two seventeen.” “It might.” Eva adjusted her glasses. “You don’t believe it.” “I don’t believe in convenient facts.” Quinn examined the dashboard. The train had no keys in the ignition. A red emergency brake handle sat under a cracked plastic cover. The panel lights glowed despite the train’s age and the fact that the line had been closed beneath this part of Camden for more than thirty years. The speedometer needle rested at zero. The odometer had rolled one mile since its last recorded service inspection, according to a yellowed sticker on the panel. One mile. There was no track ahead. The tunnel beyond the station ended in a wall of bricked-up darkness. “Who found him?” “A trader named Mr. Sallow.” The officer pointed down the platform. “Runs the stall with the bottled stuff.” “Bring him over.” Mr. Sallow approached without hurry. His mourning coat skimmed his boots, and the buttons down its front looked like tiny black eyes. He removed his hat, revealing a scalp so white it seemed powdered. “Detective.” “You found Bell?” “I opened my stall. I heard the train arrive.” Quinn glanced at the tracks. “You heard it.” “I heard wheels. Metal. The brakes.” Mr. Sallow’s mouth tightened. “Then the doors opened.” “Did anyone get off?” “No.” “Did anyone get on?” “No.” “Did you see the train enter the station?” “I was arranging inventory.” “So you heard something in a tunnel where trains haven’t run in three decades, and when you looked up, a train stood here with a dead man in it.” Mr. Sallow’s eyes narrowed. “You left out the part where that sort of thing happens in this place.” “Does it?” “Not often enough for me to sleep through it.” Eva pulled a notebook from her satchel. “Mr. Sallow, did you notice whether the lamps dimmed?” He looked at her as if he had found lint on his sleeve. “They went out.” “For how long?” “A breath.” “Did the air change?” “It tasted of pennies.” Eva wrote something down. Quinn kept her eyes on him. “Did Bell come to the Market often?” Mr. Sallow’s fingers flexed around his hat brim. “He came once before.” “When?” “Two nights ago.” “What did he buy?” “Information.” “From whom?” “From a woman who sells information.” “Her name.” “Names cost extra.” Quinn stepped closer. Mr. Sallow stood a head taller than her, but he gave ground when he saw her face. “Her name.” “Madam Vey.” “Where do I find her?” “Not here. The Market moves on the full moon. You know that.” “Then tell me where she was two nights ago.” Mr. Sallow smiled without warmth. “Detective, if I knew where Madam Vey lived, I would have died years ago.” Quinn held the silence until his smile died. “What did Bell ask for?” Mr. Sallow looked at the dead man through the open carriage door. “He asked about a door.” “What kind of door?” “The kind that should stay closed.” Eva’s pencil stopped. Quinn’s left wrist prickled beneath her watch strap. “Did he say where?” “No. He carried a compass.” “A compass?” Mr. Sallow nodded towards Bell’s coat pocket. “The little brass one. Green around the rim. He showed it to Madam Vey and asked what it pointed to.” Quinn looked at the officer. “Has anyone searched the pockets?” “Not yet, ma’am. We secured the body.” “Good.” She pulled on nitrile gloves and eased open Bell’s coat. The wallet sat where the officer had said. A packet of mints. A train ticket, old enough that the ink had faded. A folded receipt. No compass. She checked the inside pocket. Empty. The right pocket held a small bone token drilled through its centre, threaded on dirty string. The token had been snapped in two. “Entry token,” Eva murmured. “That got him into the Market.” “Or got him out.” Quinn lifted the broken bone token by the string. One half bore a thumbprint in rust-coloured residue. The other had a fresh fracture, clean and pale. “This broke recently,” she said. Eva peered over her shoulder. “Bone takes effort. You’d need pliers or a strong grip.” “Or panic.” Quinn set it into an evidence bag, then unfolded the receipt. The paper bore no shop name. Only a date, two nights earlier, and a list written in blunt pencil. ASH SALT THREAD OF THE UNHANGED MIRROR WATER ONE DIRECTION At the bottom sat a total: £0.00. Eva inhaled through her teeth. “That isn’t a receipt.” “What is it?” “A shopping list for a crossing ritual.” “Crossing where?” Eva looked towards the sealed tunnel. “That depends what he wanted to cross.” Quinn studied the carriage floor. The grime under the seats lay undisturbed except for one line of red grit. It began beneath Bell’s right shoe, crossed the aisle, and stopped at the centre doors. The doors had opened. No footprints led out. She crouched, touched the grit with one gloved finger, and rubbed it against her thumb. It felt dry and sharp, like crushed brick. “Officer.” “Yes, ma’am?” “Where’s the nearest building site?” “Above us? Plenty. Camden’s being pulled apart every other week.” “No. I mean a site that uses this aggregate.” She held up her fingers. “Red clay, iron-rich sand, powdered brick.” The officer blinked. “I can ask around.” “Ask the forensic team to compare it. Also get records on Lucas Bell. Financials, associates, phone data, travel. I want every missing-persons report connected to him in the last six months.” Eva stared at the grit. “You think he came from somewhere else.” “I think he did not walk into this carriage.” “Then how did he get here?” Quinn rose and examined the ceiling above the driver’s cabin. A thin line of moisture ran along the metal seam. It gathered at the edge, formed a bead, and dropped onto the dead man’s shoulder. The drop struck his coat. Steam hissed from the fabric. Quinn froze. Eva caught her arm. “Harlow.” The dead man’s coat had not gone wet. The droplet left a dark pinprick, then vanished. A smell like burnt copper spread through the carriage. Quinn looked up. Another bead swelled along the seam. “Everybody out,” she called. The officer did not move. “Now.” Uniforms spilled onto the platform. Eva grabbed her satchel and backed through the door, but Quinn stayed by the driver’s seat. The second drop fell onto the dashboard. Plastic blistered around it. Not water. Something seeped through from above. A third bead struck the floor beside the red grit. The grit blackened, curled, and drew itself into a thin line that pointed straight at Bell’s left hand. Quinn moved before Eva could stop her. She lifted Bell’s folded fingers apart. The palm had clenched around a brass compass. Verdigris crusted its casing. Protective sigils ringed the face, each etched deep enough to catch the carriage light. The needle spun once, twice, then slammed towards the driver’s cab. Not the tunnel. Not the platform. The dead man’s chest. Eva stepped into the doorway again, colour gone from her freckles. “That’s a Veil Compass.” “I gathered it wasn’t from a camping shop.” “It points to the nearest rift.” Quinn held the compass steady. The needle trembled against the glass, fixed on Bell’s sternum. The dead man’s shirt began to rise. Not with breath. The fabric tightened from beneath, a slow pressure lifting the buttons one by one. The top button snapped and struck the windscreen. A dark line appeared down the centre of his chest, narrow as a knife cut. Eva gripped the doorway. “Don’t touch him.” Quinn did not. The line widened. No blood came out. Cold blue light leaked through the opening, turning the carriage windows into sheets of ice. From inside Bell’s chest came the distant screech of metal wheels on rails. The station clock jolted forward. 2:18. Quinn’s worn watch stopped.
created_at"2026-07-09T17:53:10.443Z" 7/9/2026, 5:53:10 PM
model"openai/gpt-5.6-terra-20260709"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency577
moderation_latency(null)
generation_time33644
tokens_prompt1149
tokens_completion3524
native_tokens_prompt1009
native_tokens_completion2703
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"
usage0.0430675
router(null)
provider_responses
0
endpoint_id"3cc89000-ae34-4dde-9c7d-5ce009c8af0b"
id"resp_0166c323b755d0a4016a4fe0068be08197b6cb0d7c10589cad"
is_byokfalse
latency343
model_permaslug"openai/gpt-5.6-terra-20260709"
provider_name"OpenAI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1783619590-7Bvz7X6Gjd3XfJvx7cgt"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1783619590-8UcGROJD5xt5PP1cOwjY"
upstream_id"resp_0166c323b755d0a4016a4fe0068be08197b6cb0d7c10589cad"
total_cost0.0430675
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
totalTags8
adverbTagCount0
adverbTags(empty)
dialogueSentences112
tagDensity0.071
leniency0.143
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount2055
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)
80.54% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount2055
totalAiIsms8
found
0
word"stomach"
count1
1
word"velvet"
count1
2
word"familiar"
count1
3
word"grave"
count1
4
word"warmth"
count1
5
word"silence"
count1
6
word"etched"
count1
7
word"trembled"
count1
highlights
0"stomach"
1"velvet"
2"familiar"
3"grave"
4"warmth"
5"silence"
6"etched"
7"trembled"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences177
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount4
hedgeCount1
narrationSentences177
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)
analyzedSentences280
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
totalWords2055
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions17
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions79
wordCount1382
uniqueNames13
maxNameDensity1.88
worstName"Quinn"
maxWindowNameDensity4
worstWindowName"Mr"
discoveredNames
Circle1
Line1
Harlow1
Quinn26
Camden2
Morris1
Thames1
Kowalski1
Lucas1
Bell9
Eva19
Mr8
Sallow8
persons
0"Line"
1"Harlow"
2"Quinn"
3"Morris"
4"Kowalski"
5"Lucas"
6"Bell"
7"Eva"
8"Mr"
9"Sallow"
places
0"Thames"
globalScore0.559
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences100
glossingSentenceCount2
matches
0"looked like tiny black eyes"
1"seemed powdered"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount2055
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences280
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs199
mean10.33
std11.78
cv1.141
sampleLengths
027
137
275
38
49
53
612
79
88
945
102
114
1244
1313
1419
156
1647
171
1846
195
203
215
2216
235
2442
256
265
2717
2818
2914
305
311
3216
3343
343
354
364
377
389
398
405
4137
422
432
447
4511
463
4716
4811
498
99.32% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences177
matches
0"been closed"
1"been closed"
2"been snapped"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs231
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences280
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1385
adjectiveStacks0
stackExamples(empty)
adverbCount26
adverbRatio0.018772563176895306
lyAdverbCount3
lyAdverbRatio0.0021660649819494585
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences280
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences280
mean7.34
std5.52
cv0.753
sampleLengths
027
121
25
311
420
511
612
713
819
98
109
113
1212
139
148
154
1614
177
1820
192
204
2116
221
237
244
2516
267
276
2819
296
3012
319
329
338
349
351
3628
3718
385
393
405
4116
425
4315
4421
456
466
475
4817
495
45.80% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats16
diversityRatio0.30935251798561153
totalSentences278
uniqueOpeners86
21.37% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences156
matches
0"Only a date, two nights"
ratio0.006
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount23
totalSentences156
matches
0"It had stopped at 2:17."
1"His pale eyes tracked her"
2"She crossed the platform."
3"Her leather watch sat warm"
4"He had put blue shoe"
5"Her curly red hair had"
6"His skin held the waxy,"
7"His eyes had been closed."
8"His nails were clean."
9"His left cuff had torn"
10"It had the sheen of"
11"She leaned closer."
12"His mourning coat skimmed his"
13"He removed his hat, revealing"
14"He looked at her as"
15"She pulled on nitrile gloves"
16"She checked the inside pocket."
17"It began beneath Bell’s right"
18"She crouched, touched the grit"
19"It felt dry and sharp,"
ratio0.147
27.31% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount135
totalSentences156
matches
0"The dead man sat in"
1"Detective Harlow Quinn stood on"
2"It had stopped at 2:17."
3"The second hand shivered once,"
4"The abandoned station smelled of"
5"Stalls crowded the old platform"
6"A woman with antlers sold"
7"A boy with no shadow"
8"Quinn glanced at the constable"
9"The constable swallowed."
10"Quinn looked past him."
11"A tall man in a"
12"His pale eyes tracked her"
13"A woman with a snake"
14"She crossed the platform."
15"Her leather watch sat warm"
16"The hands moved properly on"
17"DS Morris had joked about"
18"Quinn stepped into the train"
19"A uniformed officer stood near"
ratio0.865
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences156
matches(empty)
ratio0
87.91% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences52
technicalSentenceCount4
matches
0"The dead man sat in the driver’s seat of a Circle Line train, hands folded over his stomach as if someone had posed him for a photograph."
1"Detective Harlow Quinn stood on the platform beneath Camden, one boot planted beside a puddle that reflected the cracked station clock."
2"His skin held the waxy, blue-grey cast of someone who had been dead for hours."
3"He looked at her as if he had found lint on his sleeve."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags8
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount1
fancyTags
0"Eva murmured (murmur)"
dialogueSentences112
tagDensity0.036
leniency0.071
rawRatio0.25
effectiveRatio0.018
86.5192%