Run: 2026-09-23-01M37HMS1M64HAMDQ6ZHMBK5DJ

Run Details

Duration:
47.0s
Cost:
$0.024188
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 ran down the back of Detective Harlow Quinn’s collar as Tomás Herrera burst out of the side door of a Camden pharmacy. He struck the pavement with one hand, caught himself and ran. Quinn followed. “Tomás. Stop.” He glanced over his shoulder. The pharmacy’s security light caught his face, then the black medical bag banging against his hip. Blood marked the cuff of his jacket. His left hand clamped the bag shut. A cab cut across Quinn’s path. She slapped its bonnet, vaulted the kerb and landed in the road behind Herrera. The driver leaned on his horn. Herrera had already slipped between two buses waiting at the lights. Quinn had watched him leave the Raven’s Nest twenty minutes earlier. He had come out beneath its green neon sign carrying the same bag, his head down against the rain. She had followed his bus north from Soho in an unmarked car. Outside the pharmacy, a man in a hood had handed Herrera a parcel and run when Quinn showed her warrant card. Herrera had run too. She pressed the button on her radio. “Quinn. Suspect on foot, northbound towards Camden High Street. Dark jacket, medical bag.” A burst of interference swallowed the reply. She clipped the radio back onto her belt and pushed through a knot of people outside a late-night takeaway. Herrera cut into an alley beside a shuttered record shop. Quinn followed him past bins that smelled of sour beer. At the far end, a chain-link gate stood open by the width of a shoulder. He turned sideways and slipped through. “Save yourself the trouble,” she called. “I saw the handover.” He stopped beyond the gate. For a moment she thought he meant to answer. Then he looked past her, towards the street, and pulled the gate shut. The latch caught before Quinn reached it. Herrera turned away. She drove her shoulder into the mesh, found the latch with two fingers and forced it up. By the time she got through, he had crossed a small service yard and vanished behind a pair of iron doors. One door struck the wall as she reached it. Beyond lay a stairwell tiled in grimy cream, its steps falling out of sight. A faded Underground roundel hung above them. Someone had painted over the station name, though the letters beneath still read CAMDEN. Herrera’s footsteps rang below. Quinn took the stairs three at a time. The city noise thinned behind her. Halfway down, she caught the smell of hot metal and incense. Voices rose from below, too many for an abandoned station. At the bottom of the first flight, Herrera struggled with a narrow door set into a security grille. A large woman stood on the other side, her hand resting on a steel bolt. “Herrera.” Her voice carried up the stairwell. “You brought company.” “She’s police. Let me through.” The woman looked up at Quinn. Her eyes rested on the warrant card Quinn held out. “Then you can wait with her.” Herrera pulled something pale from his jacket pocket. Quinn saw a small disc strung on red cord. As he thrust it towards the grille, she caught his wrist. The old scar along his left forearm showed white beneath his soaked sleeve. “Bag on the floor.” “Get off me.” He drove his elbow into her ribs. Quinn kept hold of his wrist and struck the grille with her shoulder. The disc fell between them, hit a step and rolled. Herrera twisted free. The woman threw back the bolt, hauled him inside and slammed the door against Quinn’s outstretched hand. It caught her fingertips. She pulled them clear before the bolt dropped. “Herrera!” Through the grille, she saw him hurry down another flight. Light spilled up from below: red, amber and a green that shifted across the tiles. The woman stayed beside the door. “Open it.” Quinn held up her warrant card. “Metropolitan Police.” “You can read the sign at the top, then.” “This station’s closed.” “Looks busy from here.” Quinn bent and picked up the disc. It was bone, worn smooth at its edges, with a hole drilled through its centre. A shallow groove divided one face into four unequal parts. Herrera’s wet thumbprint marked the other. The woman’s expression changed when she saw it. “Where did you get that?” “He dropped it.” “That belongs to him.” “Open the door.” The woman tightened her grip on the bolt. “Give it back when you catch him.” She slid it free. Quinn pulled the door open, then paused on the threshold. Her radio had gone quiet. Behind her, the stairs led to a street full of witnesses, traffic cameras and officers who would come if she called again. Ahead, Herrera disappeared around a bend beneath the tracks. He knew the way through. She did not. The woman held out a hand for the token. Quinn put it in her coat pocket and stepped through. “What’s your name?” she asked. The woman pushed the grille shut. “Ask him.” Quinn descended past a boarded ticket window and a row of machines with their screens torn out. She rounded the bend and stopped at the platform entrance. Stalls filled the space where passengers should have stood. Canvas awnings stretched between tiled pillars; wires carried bare bulbs over tables crowded with bottles, rusted keys and trays of teeth. A man held a glass vial to the light while something inside it beat against the cork. Farther down, a woman argued over a parcel wrapped in butcher’s paper. The rails had disappeared beneath wooden decking, though Quinn could see black water between the boards. No one wore a uniform. No one looked surprised to see her. Herrera moved through the crowd on the far side of the platform, his medical bag tucked beneath one arm. He glanced back and saw her. For the first time since the pharmacy, he slowed. Quinn pushed forward. A stallholder drew a curtain of hanging charms across her path. She swept them aside; bone and brass knocked against her wrist. “Police. Move.” The stallholder caught one swinging charm before it struck a lamp. “You’ll pay if you break it.” “Send me a bill.” Herrera ducked behind a pillar painted with an old advertisement for soap. Quinn went after him. A boy carrying a stack of empty crates stepped into her way, and she caught the top one before it fell. “Where’s he gone?” The boy stared at her warrant card, then past her shoulder. Quinn turned. A man in a long grey coat stood at the platform entrance she had just crossed. He spoke into the ear of the woman from the grille. She pointed towards Quinn. The man started down the platform. Quinn set the crate back on the stack and moved. Beyond the soap advertisement, a table displayed surgical instruments on black velvet. Several bore handles shaped from materials she could not place. Herrera stood there with the stallholder, passing over the parcel from the pharmacy. The stallholder peeled back one fold of paper. Quinn caught a glimpse of a glass ampoule packed in straw. “Herrera. Hands where I can see them.” He snatched the parcel back. The stallholder pulled his hands clear. “Don’t bring this to my table,” he told Herrera. “You told me to come here.” “I told you to come alone.” Quinn closed the distance between them. Herrera backed towards a narrow gap between the stalls. “The man outside gave you that parcel,” she told him. “I want to know what’s in it.” Herrera looked at the grey-coated man approaching from the other end of the platform. Rainwater dripped from Herrera’s curls onto his cheeks. His Saint Christopher medallion had slipped outside his shirt. “Not here.” “Put it down.” “He needs it.” “Who does?” Herrera’s eyes shifted to the passage behind Quinn. She heard a cry from deeper in the station, short and raw. Several people turned towards it. Herrera used the movement to slip into the gap. Quinn caught the strap of his bag. It jerked against her palm as he pulled away. “Enough.” “Then let go.” The grey-coated man reached the stall and planted himself beside the instruments. The stallholder drew his velvet cloth over them. Quinn drew Herrera back by the strap. The medical bag struck the table, and a steel tray fell to the boards with a crash. Herrera twisted towards her, one hand still wrapped around the paper parcel. “Open the bag,” Quinn ordered. He stared at her. The cry sounded again from the passage behind him. He set the parcel on the table, kept one hand on it and reached for the bag’s zip.
created_at"2026-09-23T16:30:08.443Z" 9/23/2026, 4:30:08 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency11577
moderation_latency(null)
generation_time47013
tokens_prompt1104
tokens_completion2185
native_tokens_prompt984
native_tokens_completion2222
native_tokens_completion_images0
native_tokens_reasoning429
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"
usage0.024188
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790181008-PrN14gCGvhKooQqRHYyu"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790181008-SoDqBGoAvseWjLKM9wvG"
upstream_id"resp_068b04ee4cf2af81016ab3fe90a21487d188f4582f572489aa"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_068b04ee4cf2af81016ab3fe90a21487d188f4582f572489aa"
is_byokfalse
latency1026
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.024188
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
totalTags8
adverbTagCount0
adverbTags(empty)
dialogueSentences40
tagDensity0.2
leniency0.4
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1444
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)
86.15% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1444
totalAiIsms4
found
0
word"footsteps"
count1
1
word"charm"
count1
2
word"velvet"
count2
highlights
0"footsteps"
1"charm"
2"velvet"
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
emotionTells1
narrationSentences132
matches
0"looked surprised"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences132
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences164
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen23
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1444
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions8
unquotedAttributions0
matches(empty)
16.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions64
wordCount1280
uniqueNames12
maxNameDensity2.34
worstName"Quinn"
maxWindowNameDensity4.5
worstWindowName"Herrera"
discoveredNames
Detective1
Harlow1
Quinn30
Tomás1
Herrera24
Camden1
Raven1
Nest1
Soho1
Underground1
Saint1
Christopher1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Raven"
5"Saint"
6"Christopher"
places
0"Soho"
globalScore0.328
windowScore0.167
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences107
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1444
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences164
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs82
mean17.61
std16.46
cv0.935
sampleLengths
034
12
22
335
437
567
67
713
826
941
1010
1127
1248
1344
144
1535
1633
1710
185
1916
206
2141
224
2310
2443
2512
261
2731
2810
299
303
314
3238
338
345
353
364
373
3815
394
4054
419
4210
435
448
4527
4675
4712
4834
4925
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences132
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs221
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount2
flaggedSentences2
totalSentences164
ratio0.012
matches
0"Canvas awnings stretched between tiled pillars; wires carried bare bulbs over tables crowded with bottles, rusted keys and trays of teeth."
1"She swept them aside; bone and brass knocked against her wrist."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1284
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.01557632398753894
lyAdverbCount1
lyAdverbRatio0.000778816199376947
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences164
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences164
mean8.8
std4.91
cv0.558
sampleLengths
023
111
22
32
45
516
67
77
86
914
106
1111
1211
1319
1412
1521
164
177
1813
197
2019
2110
2210
2315
246
256
264
275
289
2913
307
313
3217
3321
349
3514
367
3714
384
398
406
4111
4210
4318
4415
457
463
475
486
4910
53.66% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.32926829268292684
totalSentences164
uniqueOpeners54
26.25% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences127
matches
0"Then he looked past her,"
ratio0.008
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount34
totalSentences127
matches
0"He struck the pavement with"
1"He glanced over his shoulder."
2"His left hand clamped the"
3"She slapped its bonnet, vaulted"
4"He had come out beneath"
5"She had followed his bus"
6"She pressed the button on"
7"She clipped the radio back"
8"He turned sideways and slipped"
9"He stopped beyond the gate."
10"She drove her shoulder into"
11"Her voice carried up the"
12"Her eyes rested on the"
13"He drove his elbow into"
14"It caught her fingertips."
15"She pulled them clear before"
16"It was bone, worn smooth"
17"She slid it free."
18"Her radio had gone quiet."
19"He knew the way through."
ratio0.268
26.93% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount110
totalSentences127
matches
0"Rain ran down the back"
1"He struck the pavement with"
2"He glanced over his shoulder."
3"The pharmacy’s security light caught"
4"Blood marked the cuff of"
5"His left hand clamped the"
6"A cab cut across Quinn’s"
7"She slapped its bonnet, vaulted"
8"The driver leaned on his"
9"Herrera had already slipped between"
10"Quinn had watched him leave"
11"He had come out beneath"
12"She had followed his bus"
13"Herrera had run too."
14"She pressed the button on"
15"A burst of interference swallowed"
16"She clipped the radio back"
17"Herrera cut into an alley"
18"Quinn followed him past bins"
19"He turned sideways and slipped"
ratio0.866
39.37% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences127
matches
0"By the time she got"
ratio0.008
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences61
technicalSentenceCount0
matches(empty)
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
totalTags5
fancyCount1
fancyTags
0"Quinn ordered (order)"
dialogueSentences40
tagDensity0.125
leniency0.25
rawRatio0.2
effectiveRatio0.05
88.3007%