Run: 2026-09-02-01M1HADATT7WTQ8NV4TR1D277Q

Run Details

Duration:
5m 9s
Cost:
$0.076336
Provider:
Alibaba

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 sign of The Raven's Nest spat sparks into the rain. Light pooled on the wet pavement and turned the puddles to sour glass. Detective Harlow Quinn sat behind the wheel of her unmarked car, hands at ten and two, shoulders square, the worn leather watch on her left wrist dark with damp. A cigarette burned in the ashtray. She left it alone. The door of the bar opened. A man in a grey coat stepped out. His hood shadowed his face. He carried a brown parcel under one arm and checked the street with a quick turn of the chin. Harlow knew that turn. She had seen it in interview rooms, in raid photographs, in the last footage of DS Morris before the river took him. She lifted the radio handset. "Target moving east from the Nest." Static crackled. "Say again, Quinn? We're boxed in on Greek Street." Harlow kept her eyes on the door. "Leave it. I have eyes." The man stopped at the kerb. Rain ran from his hood in a thin rope. He looked straight at the car. Harlow reached for the handle. He ran. The parcel vanished under his coat. He crossed the street, vaulted a fallen delivery crate, and shouldered through a knot of people sheltering under a bus shelter. Harlow hit the door with her shoulder and went after him. "Police." The word left her mouth and died in the traffic noise. Nobody moved. The man reached the far pavement and swung onto a parked motorbike. His boot kicked the starter. The engine coughed, caught, and spat blue smoke into the rain. Harlow threw herself back into the car. The key turned. The engine roared. The bike shot away, slicing between a taxi and a delivery van, its rear tyre flinging water high into the neon. She pulled out hard. The seat belt locked across her chest. Windscreen wipers slapped at the downpour. The bike ran the red at Shaftesbury Avenue and vanished around a corner past a lit kebab shop. Harlow followed. The car's tyres lost grip for one breath. She corrected, felt the road grab, and kept her foot down. The radio barked. "Quinn, back off. Units are two minutes out." She watched the bike's tail light flicker ahead. "Negative. He's making for Camden." "That's a jurisdictional mess. Wait for support." The tail light disappeared. "Can't hear you." She ended the call and dropped the handset into the cup holder. Rain drummed the roof. The city smeared past in streaks of red and white. The bike took Camden High Street with its front wheel off the ground. Harlow hit the kerb, clipped a rubbish bin, and sent black bags spinning into the gutter. Pedestrians scattered. One man shouted. His voice vanished behind her. The suspect turned left into a side street lined with shuttered shops. Harlow followed. The road narrowed. Old railway arches rose on the right, brick faces stained with soot and poster glue. The bike braked. Its rear wheel locked. The man slid sideways, one boot scraping the asphalt, and came to a stop beside a rusted gate set into a low wall. Harlow stopped the car across the mouth of the street. She left the engine running and stepped out. Water hit her scalp and ran down the back of her neck. Her salt-and-pepper hair flattened to her skull. She drew her baton, not her firearm. A gun in this weather drew eyes and made mistakes. The man abandoned the bike and pushed through the gate. Harlow ran. The gate led to a service ramp. Broken tiles lined the walls. A faded sign read CAMDEN TOWN. Paint covered another sign beneath it, but one word remained in white: PLATFORM. The smell rose from below: wet stone, rust, candle wax, and something herbal that had no business in a disused station. She reached the bottom of the ramp. A corridor stretched ahead, lit by strings of bare bulbs hooked from old cable runs. The suspect's coat disappeared around a bend. Harlow rounded it. A ticket barrier blocked the corridor. Someone had replaced the steel arms with a set of iron ribs, each one carved with shallow lines. Behind the barrier stood a booth built from salvaged train doors. A slot in the side accepted tokens. The suspect pressed a pale disc against the slot. The disc looked like bone. One side bore a scratched raven. The barrier opened with a groan. Harlow lunged forward. "Stop." The suspect looked back. His face was young, frightened, and smeared with rain or sweat. He mouthed a word she did not catch and slipped through. The barrier swung shut. Harlow struck it with the flat of her hand. The iron shivered. Nothing moved. A match flared near the booth. Tomás Herrera sat on an overturned crate, a medical bag open at his feet. His dark curls were plastered to his forehead. Rain dripped from the scar on his left forearm. The Saint Christopher medallion at his neck caught the bulb light as he touched it with his thumb. "You always make entrances like that, Detective?" Harlow kept her hand on the barrier. "He went through." "He had a token." "So do you." Tomás exhaled smoke through his nose. He wore a paramedic's jacket with the badges ripped off. Beneath it, his shirt carried fresh stains. He glanced at the corridor behind her, then at the booth. "This is the Veil Market. It moved last full moon. Tonight it sits under Camden." "I don't care where it sits. I care about the man who just went in." "Care gets people killed down there." "Your concern is noted." "It isn't concern. It's professional advice. You go in with that badge, you become a price tag." Harlow looked at the booth. No attendant. Only the slot, dark and waiting. "Give me your token." Tomás laughed. The sound had no humour in it. "I patch people up when the Market spills its guts. I don't hand out entry." "I have three officers on the way." "They'll find a wall and a story. The Market doesn't like uniforms." "I'm not wearing one." "You've got the face for it." Harlow stepped closer. Water ran from her jaw. Her hand stayed away from her cuffs. She needed the token more than she needed him frightened. "A man with that coat just carried something out of The Raven's Nest. Something tied to a dead officer." Tomás's thumb stopped on the medallion. "Which officer?" "Morris." The name sat between them. Tomás looked at the barrier. "You think he went into the Market because he's guilty?" "I think he ran because he knows what he carried." "People run from you for sport, Detective." A distant sound rolled up from beyond the barrier: low voices, metal on metal, a note of music dragged through water. Harlow listened. The corridor behind her stayed empty. Her support had not arrived. The suspect had not come back. She held out her hand. "Token." Tomás studied her face. Then he reached into his jacket and produced a small leather pouch. He loosened the drawstring and tipped a disc into his palm. Bone. Polished by fingers. A carved crescent moon marked one side. "This gets one person through. Not both of us." "I'm not bringing you." "Good. Because I'm not going back in." He did not place the token in her hand. He closed her fingers over it. His skin was warm and rough. "There are rules. No arrests without a broker. No photographs. No blood on the merchandise. You break one, the brokers toss you out." "Who will?" "Everyone." Harlow turned to the barrier. The bone token fit the slot. The iron ribs clicked. A seam of amber light opened beyond them, followed by a breath of warm air carrying resin, burnt sugar, and old paper. The market stretched through the abandoned platform in rows of stalls built from old train carriages, scaffolding, and black tarpaulin. Lanterns swung from the ceiling. Shoppers moved with their faces tilted away from the light. The suspect's grey coat vanished into the crowd. Harlow pushed the barrier open and stepped inside. The iron shut behind her.
created_at"2026-09-02T15:04:45.153Z" 9/2/2026, 3:04:45 PM
model"qwen/qwen3.8-max-20260803"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency834
moderation_latency(null)
generation_time309272
tokens_prompt1104
tokens_completion12632
native_tokens_prompt1103
native_tokens_completion12355
native_tokens_completion_images(null)
native_tokens_reasoning10532
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"stop"
service_tier(null)
usage0.076336
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788361485-UsmVHWTKsiyaNnHeF8bZ"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788361485-WEinV8pBn4DibUbfnaYB"
upstream_id"chatcmpl-08ff99b1-502d-90c7-9482-e2274974a877"
provider_responses
0
endpoint_id"6332e9fd-e0c4-4cae-8c17-d25bc774864a"
id"chatcmpl-08ff99b1-502d-90c7-9482-e2274974a877"
is_byokfalse
latency833
model_permaslug"qwen/qwen3.8-max-20260803"
provider_name"Alibaba"
status200
total_cost0.076336
cache_discount(null)
upstream_inference_cost0
provider_name"Alibaba"
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
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1366
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)
96.34% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1366
totalAiIsms1
found
0
word"flicker"
count1
highlights
0"flicker"
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
narrationSentences136
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences136
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences173
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen29
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1366
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
59.34% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions41
wordCount1103
uniqueNames15
maxNameDensity1.81
worstName"Harlow"
maxWindowNameDensity3
worstWindowName"Tomás"
discoveredNames
Raven1
Nest1
Harlow20
Quinn1
Morris1
Shaftesbury1
Avenue1
Camden1
High1
Street1
Herrera1
Saint1
Christopher1
Rain3
Tomás6
persons
0"Raven"
1"Nest"
2"Harlow"
3"Quinn"
4"Morris"
5"Herrera"
6"Saint"
7"Christopher"
8"Rain"
9"Tomás"
places
0"Shaftesbury"
1"Avenue"
2"Camden"
3"High"
4"Street"
globalScore0.593
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences87
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1366
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences173
matches
0"knew that turn"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs80
mean17.08
std18.73
cv1.097
sampleLengths
065
16
258
35
46
52
69
77
85
921
105
112
1238
131
1441
1534
1656
173
188
198
205
217
224
233
2465
2562
2654
2710
282
2952
3029
313
3268
333
341
3544
366
3749
387
397
403
414
423
4334
4415
4515
466
474
4817
4913
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences136
matches
0"were plastered"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs200
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences173
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1105
adjectiveStacks0
stackExamples(empty)
adverbCount10
adverbRatio0.00904977375565611
lyAdverbCount1
lyAdverbRatio0.0009049773755656109
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences173
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences173
mean7.9
std5.38
cv0.682
sampleLengths
013
113
229
36
44
56
68
75
819
94
1022
115
126
132
149
157
165
176
189
196
205
212
226
2321
2411
251
2611
272
2812
295
3011
317
323
333
3421
354
367
376
3818
392
408
4111
423
438
448
455
467
474
483
4912
50.67% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.3352601156069364
totalSentences173
uniqueOpeners58
53.76% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences124
matches
0"Only the slot, dark and"
1"Then he reached into his"
ratio0.016
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount31
totalSentences124
matches
0"She left it alone."
1"His hood shadowed his face."
2"He carried a brown parcel"
3"She had seen it in"
4"She lifted the radio handset."
5"He looked straight at the"
6"He crossed the street, vaulted"
7"His boot kicked the starter."
8"She pulled out hard."
9"She corrected, felt the road"
10"She watched the bike's tail"
11"She ended the call and"
12"His voice vanished behind her."
13"Its rear wheel locked."
14"She left the engine running"
15"Her salt-and-pepper hair flattened to"
16"She drew her baton, not"
17"She reached the bottom of"
18"His face was young, frightened,"
19"He mouthed a word she"
ratio0.25
0.32% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount114
totalSentences124
matches
0"The green neon sign of"
1"Light pooled on the wet"
2"Detective Harlow Quinn sat behind"
3"A cigarette burned in the"
4"She left it alone."
5"The door of the bar"
6"A man in a grey"
7"His hood shadowed his face."
8"He carried a brown parcel"
9"Harlow knew that turn."
10"She had seen it in"
11"She lifted the radio handset."
12"Harlow kept her eyes on"
13"The man stopped at the"
14"Rain ran from his hood"
15"He looked straight at the"
16"Harlow reached for the handle."
17"The parcel vanished under his"
18"He crossed the street, vaulted"
19"Harlow hit the door with"
ratio0.919
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences124
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences42
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
88.6813%