Run: 2026-09-23-01M36R0TTY7YXP68JENXMBBVZP

Run Details

Duration:
35.7s
Cost:
$0.001490
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 above the Raven’s Nest cut through the rain and laid a broken stripe across the pavement. Detective Harlow Quinn watched the doorway from beneath the awning opposite, her collar turned up, one hand tucked inside her coat around the radio. At 11:17, a man in a grey wool coat stepped out of the bar. He checked both ends of the street, then glanced at the black window behind him. Quinn saw his eyes find her reflection. He ran. She shoved off the wall and went after him. “Suspect moving north from Dean Street,” she snapped into the radio. “Grey coat, dark trousers. On foot. I’m in pursuit.” The man shouldered through a knot of late-night drinkers. Someone swore as he clipped a paper cup from their hand. Quinn ducked under an umbrella, boots striking the slick pavement, and kept him in sight between the swaying backs and raised hoods. He was quick. He knew the streets. At the corner of Frith Street he cut hard into an alley, stepped over a stack of beer crates and slipped through a narrow gap between two buildings. Quinn took the gap at speed. Brick scraped her shoulder. The alley spat her into a service yard where bins stood in ankle-deep water. The suspect vaulted a low gate. “Stop. Police!” He landed, stumbled, and looked back. The hard white flash of a streetlamp caught his face: narrow nose, shaved head, a pale seam of scar beneath his right eye. Quinn knew him from the photographs. Martin Voss. Two arrests, no convictions. He had appeared in the margins of three investigations tied to stolen medical supplies and a missing witness. Voss lifted one hand as if to surrender. The other stayed inside his coat. “Don’t reach for anything.” His mouth moved around a grin. Then he ran again. Quinn climbed the gate. The old leather watch on her left wrist snagged on a bent hinge and tore free. She caught it before it hit the ground, shoved it into her pocket, and drove after him. Beyond the yard, rain glazed the road silver. A black cab hissed through a puddle, throwing water across Voss’s legs. He veered between two parked cars and nearly vanished behind a delivery van. Quinn hit the street a few seconds later. Her lungs pulled cold air through her throat. She pressed the radio button with her thumb. “Suspect heading east. Still on foot.” Static answered. The buildings swallowed the signal. Voss crossed against traffic. A cyclist braked and yelled at him. Quinn raised her palm to stop a car, then ran through the gap it left, boots slapping water from the road. Her coat dragged at her knees. The city blurred into shutters, headlights, and wet brick. At the end of the block, Voss ducked through a passage marked PRIVATE. Quinn pushed in after him. The passage climbed over a railway cutting, its iron rail slick under her fingers. A train thundered beneath, rattling the bridge and shaking grit from the walls. Voss was halfway across. He looked over his shoulder. “Quinn, you should’ve taken the hint.” “Keep running. I’ve got plenty of questions.” “You’ve got no idea what you’re asking.” He reached the far end and dropped down a flight of stone steps. Quinn followed. The steps opened onto a road leading north, where the rain had thinned to a fine, needling sheet. Camden’s late-night crowds had mostly emptied. Shuttered shops lined the pavements, their metal fronts painted with murals and old flyers. Voss ran past a kebab shop, cut through a car park, and plunged into a lane between warehouses. Quinn’s calves burned. She forced her breath into a steady count: four strides in, four out. At the lane’s end, Voss seized a rusted door and pulled it open. A flight of steps descended behind it. Quinn reached the door as it began to swing shut. She caught the edge with her shoulder. Damp air rose from the stairwell, thick with metal, smoke, and something sour beneath it. A painted sign hung crooked on the wall. CAMDEN MARKET—CLOSED FOR REPAIRS. The lettering looked old enough to have survived several repairs. Quinn drew her torch and stepped inside. The door shut behind her with a hollow bang. Above, rain ticked against its metal skin. Below, Voss’s footsteps struck the stair treads and faded. “Voss!” No answer. She took the stairs two at a time. The brickwork changed as she descended, patched mortar giving way to glazed white tiles. A station name had once sat above the landing. Someone had chipped most of it off. The surviving letters spelled CAM—. Quinn stopped at the next turn. The stairwell continued into blackness. She thumbed her radio. “Control, this is Quinn. I’ve entered a disused station access beneath Camden. Need units at—” Static. She tried again, shifting the radio above her head. Nothing. The stairs ended at a platform. A rusted sign pointed towards an exit that had been bricked over. The rails below held no water, though the rest of the city ran with it. Their surface gleamed under her torch as if someone had polished them. A door stood open at the platform’s far end. A strip of warm light crossed the tiles. Quinn moved towards it with one hand near her belt. The air carried a murmur beyond the doorway: voices, metal clinks, the rumble of bargaining. She reached the threshold and saw Voss in the next passage, already fifty feet ahead. A woman in a red scarf blocked his way. Voss pulled a pale object from his pocket and pressed it into her palm. The woman checked it with her thumb, then stepped aside. He passed through a curtain of dark canvas. Quinn lowered her torch. The pale object had been carved from bone, a narrow token scored with three black lines. The woman turned her gaze towards the platform. Quinn crossed the distance, keeping her steps measured. The woman’s eyes travelled over her wet coat, her hands, the radio clipped at her shoulder. “Closed,” the woman said. “Police.” The woman’s gaze settled on the badge at Quinn’s belt. She gave it no more attention than she’d give a bus ticket. “No police here.” Quinn glanced past her. Canvas strips swayed in the passage. Beyond them, colour and motion filled a cavernous space cut into the old station: awnings crowded the platform, lamps burned behind tinted glass, and tables displayed glass vials, bundles of dried leaves, metal charms, and knives with curved black blades. People moved through the stalls in coats and masks, shoulder to shoulder. A man with a silver mask laughed beside a cage that rattled from within. Voss had disappeared among them. Quinn’s hand tightened on her radio. She could retreat, find a signal, call in a team and come back with warrants, lights, and enough officers to hold the entrances. She could also lose Voss in the crowd before the rain stopped. No marked unit knew the stairwell existed. The only person who had seen him enter stood between her and the market. The woman held out her palm. “Token.” Quinn looked at the canvas. Voices surged behind it. Somewhere in the crowd, Voss called out, and a reply rose from farther inside. She could hear the distance growing. Quinn reached into her coat. Her fingers found the broken strap of her watch, a damp notebook, then the small evidence bag she had slipped into her pocket after the chase began. Inside lay the bone token Voss had dropped at the railway steps. She set it in the woman’s hand. The woman rubbed the scored lines with her thumb, then moved aside. Quinn drew one breath through her nose, squared her shoulders, and passed beneath the canvas into the Veil Market.
created_at"2026-09-23T09:02:20.518Z" 9/23/2026, 9:02:20 AM
model"openai/gpt-6-luna-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency14667
moderation_latency(null)
generation_time35691
tokens_prompt1104
tokens_completion1943
native_tokens_prompt984
native_tokens_completion2784
native_tokens_completion_images0
native_tokens_reasoning1133
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"
usage0.0014904
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1790154140-bqlvWM1HomxV4L2jIu3n"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790154140-hD6tP6N5lXGdoLbAhbcA"
upstream_id"resp_086f3b85770213b8016ab3959c9d5c87d1b47e541b456898a8"
provider_responses
0
endpoint_id"05e94e02-b9c2-4bbb-ba55-4082ee9ad687"
id"resp_086f3b85770213b8016ab3959c9d5c87d1b47e541b456898a8"
is_byokfalse
latency681
model_permaslug"openai/gpt-6-luna-20260922"
provider_name"OpenAI"
status200
total_cost0.0014904
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
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences14
tagDensity0.143
leniency0.286
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1301
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)
88.47% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1301
totalAiIsms3
found
0
word"thundered"
count1
1
word"footsteps"
count1
2
word"measured"
count1
highlights
0"thundered"
1"footsteps"
2"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
narrationSentences125
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount1
narrationSentences125
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)
analyzedSentences137
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen40
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1300
ratio0
matches(empty)
75.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions1
matches
0"Somewhere in the crowd, Voss called out, and a reply rose from farther inside."
56.58% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions45
wordCount1231
uniqueNames9
maxNameDensity1.87
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Raven1
Nest1
Harlow1
Quinn23
Frith1
Street1
Voss15
Veil1
Market1
persons
0"Raven"
1"Harlow"
2"Quinn"
3"Voss"
4"Market"
places
0"Frith"
1"Street"
2"Veil"
globalScore0.566
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences94
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1300
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences137
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs61
mean21.31
std18.43
cv0.865
sampleLengths
043
129
27
32
49
520
642
735
830
92
1059
1114
124
1310
1437
1533
1624
176
187
1947
2045
219
226
237
247
2553
2647
277
2832
298
304
3110
3232
331
342
3543
3615
3715
3810
391
4045
4117
4240
439
4432
4528
4624
474
481
4922
99.65% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences125
matches
0"been bricked"
1"been carved"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs215
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences2
totalSentences137
ratio0.015
matches
0"CAMDEN MARKET—CLOSED FOR REPAIRS."
1"The surviving letters spelled CAM—."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1235
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.016194331983805668
lyAdverbCount4
lyAdverbRatio0.0032388663967611335
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences137
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences137
mean9.49
std6.17
cv0.65
sampleLengths
019
124
214
315
47
52
69
711
89
99
1011
1122
123
134
1428
156
164
1714
186
192
206
2123
226
232
244
2518
268
276
284
296
304
314
3216
3317
348
3512
3613
378
388
398
406
412
425
434
447
4521
466
479
4813
495
45.62% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.291970802919708
totalSentences137
uniqueOpeners40
56.50% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences118
matches
0"Then he ran again."
1"Somewhere in the crowd, Voss"
ratio0.017
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences118
matches
0"He checked both ends of"
1"She shoved off the wall"
2"she snapped into the radio"
3"He was quick."
4"He knew the streets."
5"He landed, stumbled, and looked"
6"He had appeared in the"
7"His mouth moved around a"
8"She caught it before it"
9"He veered between two parked"
10"Her lungs pulled cold air"
11"She pressed the radio button"
12"Her coat dragged at her"
13"He looked over his shoulder."
14"He reached the far end"
15"She forced her breath into"
16"She caught the edge with"
17"She took the stairs two"
18"She thumbed her radio."
19"She tried again, shifting the"
ratio0.246
23.56% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount103
totalSentences118
matches
0"The green neon above the"
1"Detective Harlow Quinn watched the"
2"He checked both ends of"
3"Quinn saw his eyes find"
4"She shoved off the wall"
5"she snapped into the radio"
6"The man shouldered through a"
7"Someone swore as he clipped"
8"Quinn ducked under an umbrella,"
9"He was quick."
10"He knew the streets."
11"Quinn took the gap at"
12"Brick scraped her shoulder."
13"The alley spat her into"
14"The suspect vaulted a low"
15"He landed, stumbled, and looked"
16"The hard white flash of"
17"Quinn knew him from the"
18"He had appeared in the"
19"Voss lifted one hand as"
ratio0.873
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences118
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences52
technicalSentenceCount1
matches
0"Their surface gleamed under her torch as if someone had polished them."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount0
matches(empty)
78.57% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount1
fancyTags
0"she snapped (snap)"
dialogueSentences14
tagDensity0.143
leniency0.286
rawRatio0.5
effectiveRatio0.143
87.4649%