Run: 2026-09-23-01M36RE7Q6GYE7TZRF6RMMQ35S

Run Details

Duration:
59.4s
Cost:
$0.002131
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
The green neon over The Raven’s Nest broke apart in the rain, its reflection shivering across the pavement as Harlow Quinn stepped from the doorway. She kept her eyes on the man across the street. Ivo Sayer wore a dark coat with the collar turned up. He had left the bar without a drink and without looking back. That alone would have been worth noting. The oilskin packet tucked under his arm made it worth following. Quinn touched the radio clipped beneath her lapel. “Control, Detective Quinn. I’m east of the Nest, following a male on foot. Dark coat, carrying a packet. Send a car to Camden High Street and keep it moving.” Static rasped in her ear. A bus swept between her and Sayer, throwing a fan of gutter water over the kerb. Quinn stepped back from the splash, then cut through the gap behind it. Sayer had crossed against the light. He slipped past a taxi and drove his shoulder through a knot of people under a shop awning. One woman shouted after him. He never turned. Quinn’s boots struck the wet road in measured beats. She pushed through the same gap, flashed her warrant card at a man who reached for her sleeve, and kept Sayer in sight as he turned into a narrow lane. The lane funnelled sound: rain drumming on metal shutters, a delivery driver swearing into his phone, Quinn’s breath scraping behind her teeth. Sayer glanced back. Their eyes met. He lengthened his stride. Quinn’s left wrist caught the cuff of her coat. The worn leather watch beneath it had belonged to her father. She pulled the sleeve down and accelerated, jaw set, shoulders square. The lane opened onto a busier road. Sayer darted between a parked van and a cyclist, then vanished into the crowd. Quinn saw the oilskin packet rise above a woman’s umbrella. “There,” she called, cutting past a couple locked arm in arm. Sayer looked back again. His face held no panic. He moved with the care of someone following a route he knew, choosing each turn before he reached it. That bothered her more than the speed. Her radio crackled. “Quinn, confirm your location.” “Approaching Camden High Street. Suspect on foot, moving north.” “Units are six minutes out.” “I’ll keep him warm.” She pocketed the radio. Sayer reached the pavement at the top of a short hill and turned into a service alley marked by a faded sign for a shuttered cinema. Quinn followed. Rain spilled from the buildings in steady sheets. It soaked the close-cropped salt-and-pepper hair at her temples and ran cold down her collar. A delivery scooter blocked the alley mouth. She hauled it aside by the handlebar and heard its alarm start up behind her. Sayer had reached a brick wall at the far end. A black iron door stood inset in the masonry, its paint blistered and its handle polished by use. He took something from his pocket—a pale shape no larger than a coin—and pressed it against a dark plate beside the frame. The door opened inward. Quinn’s hand went to her cuffs. “Sayer! Metropolitan Police. Stop where you are.” He turned in the doorway. Rain ran from his hair down his cheeks. “You should have stayed in the bar, Detective.” “You should’ve stayed where I could see you.” His mouth tightened. He slipped through the door. Quinn reached it before it shut. She caught the edge with her palm. The black iron felt warm despite the night air. A stairwell fell away beyond it, cut into brick and lit by naked bulbs. The smell that rose from below was damp stone, hot metal and something sharp, like a match struck inside a jar. She looked at the plate. The pale object had gone. A thin impression remained in the dark surface, shaped like a human molar. “Quinn?” Control crackled in her ear. “Your signal dropped.” She stood at the threshold and listened. Footsteps descended below, quick and uneven. Far beneath them, a crowd murmured. The alley mouth lay behind her. Streetlights shone through the rain. Six minutes, perhaps less. She could hold the door, call in units, and let Sayer put another wall between himself and the street. The stairwell turned twice before it reached the bottom. No visible cameras. No exit signs. No reliable account of what waited beneath it. Three years earlier, Morris had gone down into an underground passage with a working radio and come back as a sealed file. The official report blamed a collapse. Quinn had spent the next eighteen months finding holes in the report and no clean way through them. She checked her watch. Sayer’s steps stopped below. Quinn took the stairs. The first flight ended at a landing where water seeped through the mortar and gathered in a shallow black pool. The second descended into a tiled passage, its walls marked with faded blue bands and a station name somebody had scraped away. Dust furred the old signboards. New footprints cut through it. The air warmed with every step. A voice drifted up from below. “Token.” Then Sayer: “You saw me use it.” “Token.” A small clatter bounced up the stairwell. Quinn reached the last landing. Sayer stood beyond a waist-high iron gate, facing a broad-shouldered woman in a waxed coat. He held out a pale token. The woman turned it between thumb and forefinger, inspected the carved grooves, then unlatched the gate. Quinn looked down. Another pale disc rested near the drain at her feet. She picked it up. Bone, smooth at the edges, with a hole bored through the middle. A strip of red thread passed through it. She closed her fist around it as Sayer disappeared into the station. The woman at the gate looked up. “Business?” “Police.” “Not a kind of business.” Quinn held up her badge. The woman took one look and kept the gate half shut. Sayer had moved beyond the entrance, across a platform where vendors had set up under strings of bare bulbs. Quinn heard his voice mingle with the crowd. A train had once stopped here; the rails were gone, replaced by plank bridges over a trench lined with candles. Stalls crowded the platform. Their awnings sagged with moisture. Glass jars held curled leaves, black grit, pale feathers, teeth. A man in a suit leaned over a case of silver rings while a girl with a shaved head counted coins stained blue. Quinn stared for half a second too long. “Token,” the woman repeated, holding out her hand. Quinn laid the bone disc on her palm. The woman examined the red thread, then lifted the gate. “Keep it visible. Don’t touch anything you can’t name.” “That leaves me a lot of room.” “Not here.” Quinn pushed through. Noise took her at once: bargaining voices, clinks of glass, a low mechanical hum from somewhere beyond the platform. She pulled her radio free and tried Control. “Control, Quinn. I’m underground, beneath Camden. I need units at—” The radio spat a burst of static and died. She tapped it once against her palm. No response. Sayer’s dark coat surfaced between two stalls. He cut past a table piled with tarnished watches and ducked beneath a canopy stitched from black cloth. Quinn moved after him, badge in one hand, bone token in the other. The crowd shifted around her, refusing to part. A man with a copper mask blocked the aisle. Quinn stepped around him and knocked a tray of glass vials against a post. “Watch your hands,” the vendor snapped. “Watch your merchandise.” She reached the canopy’s edge. Beyond it, the old platform narrowed between tiled pillars. The painted bands had been hidden under strips of paper covered in cramped handwriting. Sayer’s head bobbed through the crush ahead. He had stopped beside a stall where a narrow man in a grey waistcoat opened the oilskin packet. Quinn pushed forward. “Police. Move aside.” A pair of customers turned to look. One wore a fox’s jawbone over his mouth. The other lowered the hood of a rain cape, showing a scalp crossed with dark stitches. The vendor in the grey waistcoat folded the packet closed. Sayer spotted Quinn and bolted. She vaulted the low counter at the stall’s corner. A stack of tin boxes crashed onto the platform behind her. Someone cursed. She caught the edge of a pillar, swung around it, and drove into the aisle after him. A table blocked the route. A man lay across it while a broad-shouldered medic in a rolled-sleeve shirt pressed gauze to the man’s ribs. A Saint Christopher medallion flashed against the medic’s chest. “Quinn,” the medic called, his warm brown eyes fixed on her. A scar ran along his left forearm. “Not through here.” “Then clear me a path, Herrera.” Tomás Herrera kept one hand on the patient. With the other, he shoved a stool aside. “You’ll break the stitches.” “Then stitch him again.” Quinn slipped through the gap. Sayer was already at the far end of the platform, turning towards a narrow arch marked by a strip of green paint. He looked over his shoulder and raised the packet. “Want it?” he called. “Come get it.” Quinn’s sharp jaw tightened. She lowered her badge, set her shoulder, and followed him into the arch. A knot of hanging charms struck her coat as she passed. Behind her, the market’s voices filled the tiled station; ahead, Sayer’s boots struck a stair leading deeper underground. She put one hand on the wall, kept the bone token clenched in the other, and went after him.
created_at"2026-09-23T09:09:39.7Z" 9/23/2026, 9:09:39 AM
model"openai/gpt-6-luna-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency8733
moderation_latency(null)
generation_time59352
tokens_prompt1104
tokens_completion2549
native_tokens_prompt984
native_tokens_completion4065
native_tokens_completion_images0
native_tokens_reasoning2033
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"
usage0.0021309
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1790154579-Jw6efWDgkV5mEHwvUg4i"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790154579-EkihvOIeSrlk3mThvipp"
upstream_id"resp_0d1d3d51c829c9b5016ab39753cda887d181adf8f28791addd"
provider_responses
0
endpoint_id"05e94e02-b9c2-4bbb-ba55-4082ee9ad687"
id"resp_0d1d3d51c829c9b5016ab39753cda887d181adf8f28791addd"
is_byokfalse
latency499
model_permaslug"openai/gpt-6-luna-20260922"
provider_name"OpenAI"
status200
total_cost0.0021309
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
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences32
tagDensity0.188
leniency0.375
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1603
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)
90.64% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1603
totalAiIsms3
found
0
word"measured"
count1
1
word"footsteps"
count1
2
word"mechanical"
count1
highlights
0"measured"
1"footsteps"
2"mechanical"
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
narrationSentences150
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences150
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences175
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen30
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1601
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
63.61% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions54
wordCount1447
uniqueNames10
maxNameDensity1.73
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Raven1
Nest1
Harlow1
Quinn25
Sayer20
Morris1
Control2
Saint1
Christopher1
Herrera1
persons
0"Raven"
1"Nest"
2"Harlow"
3"Quinn"
4"Sayer"
5"Morris"
6"Control"
7"Saint"
8"Christopher"
9"Herrera"
places(empty)
globalScore0.636
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences105
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1601
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences175
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs90
mean17.79
std17.81
cv1.001
sampleLengths
025
110
241
38
429
534
632
739
825
93
104
1152
1210
1311
1428
157
163
174
189
195
204
2155
2222
2350
244
256
267
2713
288
298
308
3157
325
3318
349
357
3612
3734
3823
3946
404
414
424
4352
446
456
461
477
481
497
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences150
matches
0"were gone"
1"been hidden"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs257
matches(empty)
93.88% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount2
flaggedSentences3
totalSentences175
ratio0.017
matches
0"He took something from his pocket—a pale shape no larger than a coin—and pressed it against a dark plate beside the frame."
1"A train had once stopped here; the rails were gone, replaced by plank bridges over a trench lined with candles."
2"Behind her, the market’s voices filled the tiled station; ahead, Sayer’s boots struck a stair leading deeper underground."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1456
adjectiveStacks0
stackExamples(empty)
adverbCount27
adverbRatio0.018543956043956044
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences175
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences175
mean9.15
std6.02
cv0.658
sampleLengths
025
110
211
312
47
511
68
729
85
916
1013
116
1218
135
143
159
1630
1722
183
193
204
219
2211
2311
247
2514
2610
2711
284
295
3019
317
323
334
349
355
364
374
3826
392
408
4115
427
4315
4410
4518
4622
474
486
497
45.43% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats8
diversityRatio0.28
totalSentences175
uniqueOpeners49
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences145
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount38
totalSentences145
matches
0"She kept her eyes on"
1"He had left the bar"
2"He slipped past a taxi"
3"He never turned."
4"She pushed through the same"
5"Their eyes met."
6"He lengthened his stride."
7"She pulled the sleeve down"
8"she called, cutting past a"
9"His face held no panic."
10"He moved with the care"
11"Her radio crackled."
12"She pocketed the radio."
13"It soaked the close-cropped salt-and-pepper"
14"She hauled it aside by"
15"He took something from his"
16"He turned in the doorway."
17"His mouth tightened."
18"He slipped through the door."
19"She caught the edge with"
ratio0.262
4.83% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount132
totalSentences145
matches
0"The green neon over The"
1"She kept her eyes on"
2"Ivo Sayer wore a dark"
3"He had left the bar"
4"That alone would have been"
5"The oilskin packet tucked under"
6"Quinn touched the radio clipped"
7"Static rasped in her ear."
8"A bus swept between her"
9"Quinn stepped back from the"
10"Sayer had crossed against the"
11"He slipped past a taxi"
12"He never turned."
13"Quinn’s boots struck the wet"
14"She pushed through the same"
15"The lane funnelled sound: rain"
16"Sayer glanced back."
17"Their eyes met."
18"He lengthened his stride."
19"Quinn’s left wrist caught the"
ratio0.91
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences145
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences56
technicalSentenceCount1
matches
0"The lane funnelled sound: rain drumming on metal shutters, a delivery driver swearing into his phone, Quinn’s breath scraping behind her teeth."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount0
matches(empty)
87.50% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount2
fancyTags
0"the woman repeated (repeat)"
1"the vendor snapped (snap)"
dialogueSentences32
tagDensity0.156
leniency0.313
rawRatio0.4
effectiveRatio0.125
86.1964%