Run: 2026-04-27-01KQ77V2Q89DZEM1V7PH9WNQFT

Run Details

Duration:
3m 2s
Cost:
$0.041625
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
Rain hammered the Soho pavement and turned the gutters into rushing channels. Quinn’s boots struck the wet stone in a measured cadence. Water soaked through her trousers and clung to her shins. The figure ahead cut past a shuttered newsagent, shoulders hunched, breath tearing through the cold air. Short dark curls plastered to his skull. A silver chain whipped against his collarbone with each stride. She kept twenty paces back. Eighteen years on the Met wired the distance into her muscles. The suspect glanced over his shoulder. Brown eyes caught the sodium glare. He picked up speed. “Dispatch, I’m off the main drag. Heading north towards Camden. Suspect’s making for the old tube lines.” Static crackled against her earpiece. A voice cut through the white noise. “Copy, Detective. Backup’s eight minutes out. Roads are flooded. Hold your position.” Quinn killed the mic. She pushed harder. The suspect vaulted a rusted railing and dropped onto a service road. Tyres hissed on the wet tarmac. A courier van swerved, horn blaring. He didn’t break stride. He cut through a gap in the brickwork and vanished into the shadow of the Camden underground works. Quinn reached the breach. Damp air rushed up from the dark. It carried the stink of ozone and burnt copper. She unclipped her torch. The beam cut through the drizzle and caught a set of concrete steps slick with algae. Footprints marked the descent. Fresh. Deep heel strikes. He was running blind. She descended. The city noise faded. Dripping water echoed off tiled walls. Peeling adverts curled like dead leaves. Her torch swept over cracked mosaics and rusted turnstiles. The air grew thick. Something sweet and chemical clung to the back of her throat. Alchemical runoff. She’d smelled it once before, three years ago, in a warehouse that took Morris and left only scorch marks and a case file full of black ink. A metal gate stood ahead. Welded shut. A side entrance gaped open, hinges torn free. Quinn slipped through. The passage widened into a vaulted chamber. Platform tiles gave way to packed earth and wooden pallets. Lanterns hung from exposed pipes, casting long, wavering shadows. Stalls cobbled together from scaffolding and tarpaulin lined the tracks. Crates stacked high. Glass jars pulsed with faint, sickly light. A vendor hawked dried roots wrapped in wax paper. Another weighed silver shavings on a brass scale. The suspect stood thirty yards down, chest heaving, hands braced on his knees. He straightened. Water dripped from his jaw. He pulled a small object from his coat pocket. Bone. Carved into a disc. He pressed it against a rusted iron door set into the tunnel wall. The lock clicked. Gears ground. The door swung inward. Warm air spilled out. It carried the murmur of voices, the clink of glass, the low thrum of something that vibrated in Quinn’s teeth. The suspect stepped across the threshold. He paused. Looked back. His left forearm bore a pale ridge of scar tissue. A Saint Christopher medallion rested against his sternum. Recognition clicked. Tomás Herrera. The medic who vanished from the NHS registry after treating patients that didn’t show up on any hospital ledger. He raised a hand. Fingers curled in a sharp gesture. “You cross that line, Detective, you don’t come back wearing a badge.” Quinn’s hand rested on her holster. The leather creaked. Rainwater traced a cold line down her spine. The market behind him shifted. A stall collapsed into a fold of canvas. A woman with ink-stained fingers counted coins that gleamed like beetle shells. The air hummed. This place didn’t belong on any Ordnance Survey map. It moved. The full moon sat heavy in the sky above ground. The market had rooted itself beneath Camden for the night. Tomorrow it would be gone. “Backup’s eight minutes out. Eight minutes and this rabbit hole seals shut.” Tomás wiped water from his eyes. “Morris stood where you’re standing. He made the call. You know how that ended.” Quinn’s jaw tightened. The worn leather strap of her watch dug into her wrist. She checked the face. The second hand swept past the twelve. Every tick measured a closing window. The iron door groaned on its hinges. A draft pulled at her coat, carrying the scent of crushed herbs and hot metal. The threshold marked a line between the Met’s jurisdiction and a world that operated on older rules. Rules that swallowed partners and spat out redacted files. She stepped forward. Boot leather met the damp concrete. The gap narrowed to ten paces. Five. “Turn around, Harlow.” Tomás’s voice dropped. The medallion caught the lantern light. “Walk back up those stairs. File your report. Tell them you lost me in the rain. Keep your pension. Keep your life.” Quinn’s fingers brushed the grip of her sidearm. The metal felt cold. Solid. Real. The market breathed behind him. Shadows stretched across the tracks. A vendor slammed a crate shut. The sound echoed like a gunshot. “You treat people off the books. You patch up wounds that don’t bleed right. You know what happened to him.” Tomás’s throat worked. He glanced at the open door. The warmth beyond it pulsed. “I keep people alive. That’s the job. The rest isn’t yours to carry.” “It became mine when they wiped his name from the roster.” She took another step. The threshold lay a yard away. The iron door began to drift shut. Heavy. Relentless. The gap shrank to a sliver of amber light. Tomás backed through. His boots scuffed the stone. “Last chance.” Quinn’s breath steadied. The rain above ground meant nothing down here. The city slept. The market woke. She weighed the drop. The unknown. The file on her desk that never closed. Her hand left the holster. She adjusted her coat. Shoulders squared. Military precision locked into her spine. She stepped over the line.
created_at"2026-04-27T10:30:27.311Z" 4/27/2026, 10:30:27 AM
model"qwen/qwen3.6-max-preview-20260420"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1104
moderation_latency(null)
generation_time182018
tokens_prompt1140
tokens_completion5806
native_tokens_prompt1065
native_tokens_completion5159
native_tokens_completion_images(null)
native_tokens_reasoning3843
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"
usage0.0416247
router(null)
provider_responses
0
endpoint_id"ca7fc0c7-f23d-4ac5-b2e0-945be5b61787"
id"chatcmpl-6746c653-48b3-9249-a96c-e6d7351ddf6c"
is_byokfalse
latency1104
model_permaslug"qwen/qwen3.6-max-preview-20260420"
provider_name"Alibaba"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777285827-6udw95qzj0BM28JB69Fg"
session_id(null)
api_type"completions"
id"gen-1777285827-f9KjN0sF6EFo9rNvwmZ6"
upstream_id"chatcmpl-6746c653-48b3-9249-a96c-e6d7351ddf6c"
total_cost0.0416247
cache_discount(null)
upstream_inference_cost0
provider_name"Alibaba"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences11
tagDensity0.091
leniency0.182
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount975
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)
43.59% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount975
totalAiIsms11
found
0
word"measured"
count2
1
word"echoed"
count2
2
word"wavering"
count1
3
word"pulsed"
count2
4
word"vibrated"
count1
5
word"traced"
count1
6
word"down her spine"
count1
7
word"warmth"
count1
highlights
0"measured"
1"echoed"
2"wavering"
3"pulsed"
4"vibrated"
5"traced"
6"down her spine"
7"warmth"
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
narrationSentences131
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences131
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)
analyzedSentences141
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
totalWords975
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
96.24% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount837
uniqueNames11
maxNameDensity1.08
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Tomás"
discoveredNames
Soho1
Met2
Camden2
Morris1
Quinn9
Saint1
Christopher1
Herrera1
Ordnance1
Survey1
Tomás5
persons
0"Met"
1"Morris"
2"Quinn"
3"Saint"
4"Christopher"
5"Herrera"
6"Tomás"
places
0"Soho"
globalScore0.962
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences67
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount975
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences141
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs25
mean39
std24.47
cv0.627
sampleLengths
065
132
217
324
453
552
671
781
856
975
1022
1181
1212
1320
1479
1516
1634
1736
1820
1927
2011
2128
2210
2348
245
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences131
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs153
matches
0"was running"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences141
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount838
adjectiveStacks0
stackExamples(empty)
adverbCount7
adverbRatio0.008353221957040573
lyAdverbCount2
lyAdverbRatio0.002386634844868735
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences141
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences141
mean6.91
std4.74
cv0.685
sampleLengths
012
110
210
316
47
510
65
711
86
96
104
1117
125
137
1412
154
163
1712
186
196
204
2118
224
237
249
254
2616
274
281
293
304
312
324
336
346
359
364
3711
382
3927
405
412
428
433
447
4510
469
4710
483
497
67.14% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.4326241134751773
totalSentences141
uniqueOpeners61
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences112
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount24
totalSentences112
matches
0"She kept twenty paces back."
1"He picked up speed."
2"She pushed harder."
3"He didn’t break stride."
4"He cut through a gap"
5"It carried the stink of"
6"She unclipped her torch."
7"He was running blind."
8"Her torch swept over cracked"
9"She’d smelled it once before,"
10"He pulled a small object"
11"He pressed it against a"
12"It carried the murmur of"
13"His left forearm bore a"
14"He raised a hand."
15"She checked the face."
16"She stepped forward."
17"He glanced at the open"
18"She took another step."
19"His boots scuffed the stone."
ratio0.214
9.11% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount101
totalSentences112
matches
0"Quinn’s boots struck the wet"
1"Water soaked through her trousers"
2"The figure ahead cut past"
3"A silver chain whipped against"
4"She kept twenty paces back."
5"The suspect glanced over his"
6"Brown eyes caught the sodium"
7"He picked up speed."
8"Static crackled against her earpiece."
9"A voice cut through the"
10"Quinn killed the mic."
11"She pushed harder."
12"The suspect vaulted a rusted"
13"Tyres hissed on the wet"
14"A courier van swerved, horn"
15"He didn’t break stride."
16"He cut through a gap"
17"Quinn reached the breach."
18"It carried the stink of"
19"She unclipped her torch."
ratio0.902
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences112
matches(empty)
ratio0
83.33% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences24
technicalSentenceCount2
matches
0"It carried the murmur of voices, the clink of glass, the low thrum of something that vibrated in Quinn’s teeth."
1"A woman with ink-stained fingers counted coins that gleamed like beetle shells."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags1
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
86.6469%