Run: 2026-09-23-01M37HGHF1CE1F4EYGN9FDJHY7

Run Details

Duration:
44.4s
Cost:
$0.023418
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="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> Continue the story using the following instructions: <instructions> 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. </instructions>

Model response

AI
Rain turned the road outside the Raven’s Nest into a sheet of black glass. Its green neon sign broke across the puddles as a man shoved through the bar door and ran. Detective Harlow Quinn came after him, one hand on the doorframe, the other gripping the warrant card she had shown him ten seconds before. “Tomás Herrera. Stop.” He glanced back. Short dark curls clung to his forehead. Blood marked the cuff of his jacket, and something pale flashed between the fingers of his left hand. Then a bus cut across Quinn’s view. She stepped off the kerb behind it, caught the rail of a crossing barrier and swung round the rear bumper. A horn blared. Herrera had reached the far pavement and shouldered between two men under a shop awning. One dropped his cigarette and swore. Quinn followed the gap he had made. Her shoes struck wet stone hard enough to jar her knees. “Police. Move.” A woman hauling a suitcase pulled it out of Quinn’s path. Up ahead, Herrera turned into a narrow street where rubbish bags pressed against the brickwork. Quinn caught a last glimpse of his jacket before the dark took him. Inside the Nest, he had sat beneath a photograph of old Soho and watched her place Morris’s case file on the table. He had recognised the photograph clipped to the front. Quinn had seen it in the way his fingers stopped turning the glass on its coaster. “Where did you get this?” he had asked. “That’s what I’m asking you.” Herrera had looked past her shoulder, towards the front window. By the time Quinn turned, he was out of his chair. Now she took the corner into the narrow street and spotted him at its far end, boots splashing through water that streamed along the gutter. A delivery rider leaned beside a parked scooter. Herrera clipped its mirror; the rider shouted and lunged for it. “Which way?” Quinn called. The rider pointed, still wrestling the scooter upright. “Left. Nearly took my head off.” Herrera reached a busier road. He slipped through a crowd waiting beneath the theatre canopy and crossed against the lights. Quinn pushed past a man whose umbrella caught in her coat collar. Its metal spoke scraped her neck. “Watch it.” “Then keep it above eye level.” On the opposite pavement, Herrera looked back. For one instant she saw his face under the streetlamp: warm brown eyes, rain in his lashes, his mouth open to drag air. His left sleeve rode up as he lifted an arm to fend off a pedestrian. The long scar on his forearm caught the light. He did not look like a man who had expected to run. He looked like a man who had seen what stood behind her. Quinn checked the reflection in a darkened shop window. Traffic. Umbrellas. A couple arguing over a phone. No one closing on her. She turned back. Herrera had disappeared into the mouth of the Tube station. Quinn touched her radio. “Control, Detective Quinn. Foot pursuit. Male, twenty-nine, dark jacket. Heading into Camden Town station from the south entrance.” Static scratched her ear. A voice broke through in pieces. “—repeat location?” “Camden Town. Possible connection to Morris inquiry.” She descended the first flight of steps. Water ran down the tiled wall, carrying grit and cigarette ends towards the drains. At the bottom, the ticket hall lay half lit. A shutter covered the kiosk. The barriers stood open, their screens blank. A yellow notice hung across one set of stairs: SERVICE ENTRANCE CLOSED. Herrera had gone through the notice. Its plastic cord swung against the railing. Quinn ducked beneath it. Her watch struck the rail with a dull crack. Beyond the public staircase, the station noise thinned. No train announcement reached her. Only the rattle of distant wheels and the quick scrape of shoes below. “Herrera.” A door slammed. She reached a landing and found a maintenance corridor where three bare bulbs shone over pipes crusted with white deposits. At the end stood a steel door with a narrow wired-glass pane. Herrera’s shadow crossed it. Quinn ran. The door hit its frame before she reached it. She caught the handle, pulled and felt it give. On the other side, stairs dropped past the level of the working platforms. The air grew warmer, carrying damp stone, hot oil and a sharp sweet smell she could not place. Her radio gave a single burst of static. Quinn held the transmit button. “Control, I’m below station level. Access through maintenance stairs. Send units to the entrance.” No answer. She pocketed the radio and continued down. At the foot of the stairs, a red lamp burned above an old tiled passage. Advertisements from decades ago peeled along one wall. Herrera stood halfway down it, turned towards her. “Go back.” His Saint Christopher medallion lay outside his shirt. Rain had darkened the cloth around it. Quinn drew her baton. “Put your hands where I can see them.” Herrera opened his right hand. Empty. In his left, he held a small white disc between thumb and forefinger. It had a hole through its centre. “That corridor isn’t part of the station,” he told her. “You can explain it upstairs.” “Upstairs, you put that photograph in front of the wrong person.” “You mean yourself?” A clang rang out from the darkness beyond him. Herrera’s head turned. He closed his hand around the disc. Quinn moved while he looked away. She covered half the distance before he spun and ran through a gap in a chain-link gate. It clattered shut behind him. She reached it two seconds later. A padlock hung open from the hasp. Through the mesh, she saw a second passage bending left. Herrera’s footsteps faded around it. Quinn pulled the gate wide and passed through. The tiles ended. Rough brick closed in on both sides, and cables looped overhead in thick black ropes. At the bend, voices rose where she had expected silence. A burst of laughter. Someone bargaining over a price. A bell struck three uneven notes. Quinn slowed. The passage opened onto the edge of a disused platform. Lamps hung from the ceiling on chains, throwing pools of amber light over stalls built from packing crates, velvet-covered tables and bits of salvaged railway furniture. People filled the platform from end to end. One woman held a jar against a lamp and watched silver flecks move inside it. A man in a butcher’s apron wrapped a packet in brown paper. Behind him, a sign painted on a strip of enamel read NO REFUNDS AFTER DAWN. Beyond the platform, the tracks lay under a shallow skin of water. More stalls occupied the opposite side, reached by a footbridge made of planks and scaffold poles. The tunnel mouths at either end stayed dark. Quinn pressed herself against the brick as two customers passed. One carried a cage beneath a coat. Something inside tapped the bars in a pattern too deliberate for a trapped bird. Herrera moved through the crowd ahead of her. He stopped at a narrow booth beside an old Underground map, stripped of its station names. An elderly man sat behind a counter of stained wood. Herrera placed the white disc on it. The man touched it with one finger, then lifted a hanging strip of beads to let him through. Quinn started forward. A hand caught her sleeve. “Token.” She turned. A broad woman stood between her and the platform, a ledger tucked beneath one arm. Her other hand rested on a hook-shaped knife at her belt. “Police,” Quinn told her, showing her card. “The man who just went through. Where does that booth lead?” The woman looked at the card, then at Quinn’s face. Her eyes settled on the cropped salt-and-pepper hair, the baton held low, the mud on Quinn’s shoes. “Token,” she repeated. “He’s wanted for questioning.” “So ask him.” Quinn stepped around her. The woman shifted to block her and flicked her gaze past Quinn’s shoulder. A pair of men had come to a halt at the passage entrance. Neither wore a uniform. One held a paper cup. The other kept his hands tucked under his coat. Quinn measured the distance to Herrera’s booth. Twenty yards across a platform packed with bodies. Herrera was already behind the beads. Her radio hissed. “—Quinn? Your last—” She snatched it from her pocket. “Control. Underground market beneath Camden Town. I need units at the maintenance entrance.” The broad woman’s expression changed at the word market. She reached for the radio. Quinn caught her wrist. The woman drove a shoulder into Quinn’s chest, knocking her against the brick. The radio struck the wall and bounced across the floor. A boot from the passing crowd came down on it. Plastic cracked. “Don’t bring that in here.” The woman pulled free. Quinn raised her baton. The men at the passage entrance began walking towards them. Around the platform, conversation faltered, then rose again in lower voices. At the booth, the elderly man let the beads fall. Herrera vanished behind them. Quinn could still turn back. She knew the stairs, the broken gate, the route to the station. Her officers might find the entrance if Control had caught enough of her message. Morris had followed a lead into a locked service tunnel three years ago. The report listed a fall, though no one had found a place he could have fallen from. On the booth’s counter, beside the old man’s ledger, lay a photograph. A woman with a split lip had been caught by the camera outside a hospital entrance. Quinn recognised her from Morris’s file. She had died the week after he disappeared. The old man saw where Quinn was looking. He slid the photograph beneath the ledger. The two men reached the end of the passage. The one with the paper cup tipped its contents onto the floor. Black liquid ran between the bricks and gave off the smell of burnt sugar. Quinn slipped her warrant card into her coat and closed her fist around the baton. She took the broad woman’s knife hand by the wrist, pulled her across the path of the nearer man and stepped past them onto the platform. “Tell your friend I’m coming,” she told her. The woman jerked free. “He already knows.” Quinn pushed into the crowd towards the beaded doorway.
created_at"2026-09-23T16:27:49.609Z" 9/23/2026, 4:27:49 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2119
moderation_latency(null)
generation_time44382
tokens_prompt1104
tokens_completion2610
native_tokens_prompt984
native_tokens_completion2145
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"
usage0.023418
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790180869-yV0TJJ4hQsaD53rKSAB1"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790180869-Bm1TV7VFdSc8XbyUlHBs"
upstream_id"resp_007b5b6c390d9170016ab3fe05bf4087d1911b190becdffcb9"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_007b5b6c390d9170016ab3fe05bf4087d1911b190becdffcb9"
is_byokfalse
latency630
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.023418
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
totalTags7
adverbTagCount0
adverbTags(empty)
dialogueSentences30
tagDensity0.233
leniency0.467
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1733
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)
85.57% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1733
totalAiIsms5
found
0
word"footsteps"
count1
1
word"silence"
count1
2
word"velvet"
count1
3
word"flicked"
count1
4
word"measured"
count1
highlights
0"footsteps"
1"silence"
2"velvet"
3"flicked"
4"measured"
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
narrationSentences171
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences171
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences194
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen27
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1733
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions9
unquotedAttributions0
matches(empty)
16.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions69
wordCount1574
uniqueNames13
maxNameDensity2.16
worstName"Quinn"
maxWindowNameDensity4.5
worstWindowName"Quinn"
discoveredNames
Raven1
Nest2
Harlow1
Quinn34
Herrera18
Soho1
Morris3
Tube1
Saint1
Christopher1
Underground1
Control1
One4
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Morris"
4"Saint"
5"Christopher"
6"Control"
7"One"
places
0"Raven"
1"Nest"
2"Soho"
globalScore0.42
windowScore0.167
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences124
glossingSentenceCount1
matches
0"looked like a man who had seen what stood"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1733
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences194
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs83
mean20.88
std17
cv0.814
sampleLengths
032
124
23
328
47
544
618
72
839
947
108
115
1221
1344
144
1514
1638
172
186
1954
2024
2122
2213
2322
2412
257
2642
2712
2813
2939
301
313
3236
332
3449
3513
3614
372
3838
392
4015
4112
4226
4310
445
4511
463
4719
4828
4928
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences171
matches
0"been caught"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs259
matches
0"was looking"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences194
ratio0.005
matches
0"Herrera clipped its mirror; the rider shouted and lunged for it."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1580
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.01139240506329114
lyAdverbCount3
lyAdverbRatio0.0018987341772151898
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences194
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences194
mean8.93
std5.23
cv0.586
sampleLengths
014
118
224
33
43
57
618
77
820
93
1015
116
127
1311
142
1511
1615
1713
1822
199
2016
218
225
2310
2411
2525
268
2711
284
298
306
315
3215
3312
346
352
366
377
3823
3915
409
4112
4212
439
441
451
466
475
483
4910
54.64% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.3402061855670103
totalSentences194
uniqueOpeners66
41.41% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences161
matches
0"Then a bus cut across"
1"Only the rattle of distant"
ratio0.012
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount38
totalSentences161
matches
0"Its green neon sign broke"
1"He glanced back."
2"She stepped off the kerb"
3"Her shoes struck wet stone"
4"He had recognised the photograph"
5"he had asked"
6"He slipped through a crowd"
7"Its metal spoke scraped her"
8"His left sleeve rode up"
9"He did not look like"
10"He looked like a man"
11"She turned back."
12"She descended the first flight"
13"Its plastic cord swung against"
14"Her watch struck the rail"
15"She reached a landing and"
16"She caught the handle, pulled"
17"Her radio gave a single"
18"She pocketed the radio and"
19"His Saint Christopher medallion lay"
ratio0.236
62.48% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount128
totalSentences161
matches
0"Its green neon sign broke"
1"Detective Harlow Quinn came after"
2"He glanced back."
3"Blood marked the cuff of"
4"She stepped off the kerb"
5"A horn blared."
6"Herrera had reached the far"
7"Quinn followed the gap he"
8"Her shoes struck wet stone"
9"A woman hauling a suitcase"
10"Quinn caught a last glimpse"
11"He had recognised the photograph"
12"Quinn had seen it in"
13"he had asked"
14"Herrera had looked past her"
15"A delivery rider leaned beside"
16"Herrera clipped its mirror; the"
17"The rider pointed, still wrestling"
18"Herrera reached a busier road."
19"He slipped through a crowd"
ratio0.795
62.11% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences161
matches
0"By the time Quinn turned,"
1"Now she took the corner"
ratio0.012
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences70
technicalSentenceCount1
matches
0"Now she took the corner into the narrow street and spotted him at its far end, boots splashing through water that streamed along the gutter."
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
totalTags5
fancyCount1
fancyTags
0"she repeated (repeat)"
dialogueSentences30
tagDensity0.167
leniency0.333
rawRatio0.2
effectiveRatio0.067
90.7628%