Run: 2026-09-02-01M1HAB3GYY5CQ5RANHDM66F1R

Run Details

Duration:
40.0s
Cost:
$0.000632
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 fractured against the asphalt in silver sheets. Harlow Quinn drove through the deluge without breaking stride. Her trench coat soaked heavy against her shoulders. Salt and pepper hair stuck to her temples. Left hand rested on the grip of her sidearm. Right hand checked the worn leather watch band digging into her wrist. Eighteen years on the Metropolitan Police taught her to read wind and water. Tonight the city tried to scrub away evidence. It failed. Twenty yards ahead, the suspect vaulted a chain link fence. Boots scraped galvanized steel. Canvas ripped. He dropped behind a concrete drainage wall and disappeared into the narrow alley mouth. Quinn did not hesitate. She hit the fence, pulled herself over the top rail, and landed in a muddy depression. Water splashed up past her knees. Sirens wailed three blocks east. Radio chatter crackled in her earpiece. Static washed over the frequency before a dispatcher confirmed unit arrival times. Four minutes minimum. Not enough. She spotted a rusted maintenance hatch half submerged in trash bags. Iron kicked inward. The locking mechanism shattered. Cold air rushed out, thick with the smell of wet brick and stagnant runoff. Concrete stairs spiraled downward into absolute blackness. She killed her flashlight. Relied on peripheral vision and muscle memory. Thirty-six steps down. Texture shifted from smooth cement to cracked terrazzo. Faded timetables peeled from the walls in brittle curls. Camden Road Station. Officially decommissioned in ninety eight. Unofficially alive. A heavy iron gate blocked the lower tunnel. One hinge held. The other hung loose on bent metal. Quinn slid underneath. Noise flooded her ears. Low conversations. The clink of glass bottles. Something bubbling in copper pans. Torchlight reflected off polished surfaces. She switched on her beam. Cut through thick humidity. Revealed a cavernous platform. Yellow tactile paving crumbled along the drop zone. Corrugated iron pillars supported a collapsed ceiling. Crates and stalls occupied the exact footprint of disused railway tracks. Canvas tarps draped over wooden tables. Oil lanterns cast long, wavering shadows across stacked crates. Banners hung limp in the still air. Damp stains mapped the floor like old injuries. You are standing outside the perimeter. A voice echoed from a reinforced ticket booth. Glass rattled inside a warped wooden frame. Quinn killed her torch. Let her pupils dilate. Silhouettes moved behind the counter. Leather apron covered stained denim. Heavy palms rested on a ledger bound in tarnished brass. Metropolitan Police. Quinn stepped forward. Boot heels struck wet stone. I am chasing a man. Navy jacket. Fast pace. Came through here ten minutes ago. No metal past the token line. The figure did not rise. Fingers traced embossed lettering on the ledger cover. Bone only. You know the passage rules. Quinn pressed her teeth together. Jawline sharp enough to cut glass. She tapped her belt buckle. Steel clinked against heavy cotton. He bypassed your checkpoint. Ran left toward the apothecary stalls. Laughter rumbled low. Dry as pulverized chalk. Tracks overlap everyone buying tonight. You want the runner, you follow burnt sage and ozone. Third archway under the broken timetable. Watch your step near the eastern grates. Drop straight to the tidal basin. Footsteps echoed past the booth. Quick. Deliberate. Rubber soles slapped through shallow water. Which way? Quinn asked. Left. Past the herb grinder. Do not touch the amber vials. They keep what they trap. The voice dissolved into the surrounding murmur. Quinn turned toward the platform edge. Rain still dripped from broken roof panels somewhere above. Every breath tasted of oxidized iron and damp earth. Her watch ticked steadily against her wrist. Three years passed since Morris fell into a basement that never appeared on municipal blueprints. Three years since she learned certain thresholds demand payment upfront. The suspect emerged from behind a draped tarp. Navy pack slung low. Shoulders hunched against the heavy air. He paused near a vendor arranging dried roots, wrapped parchment bundles, and small glass containers filled with swirling liquid. Cash changed hands. Fingers moved too fast to track. No spoken words. Quinn slipped behind a support column. Kept her back against cold metal. Only lantern glow and dim emergency strips illuminated the corridor. The gap between stalls widened. Sufficient space for a sprint. Uniformed boots thundered above ground. Concrete vibrated with their rhythm. Voices grew sharper through the ventilation shafts. Backup cleared the surface in sixty seconds. The suspect glanced backward. Eyes locked across thirty yards. Recognition sparked. He pushed off a wooden crate and vanished into the deeper tunnel. Quinn slid her thumb along the slide release. Metal felt ice cold. Sweat pooled beneath her armpits. Protocol demanded stationary engagement. Wait for squad lead. Wait for legal authorization. Procedure evaporated here. Floorboards groaned under shifting weight. Somewhere a metal tray scraped against stone. A woman recited numbers in a language Quinn did not recognize. She stepped onto the crumbling yellow edge. Gravel shifted beneath her sole. The tunnel exhaled colder air upward. Shadows stretched thin and rigid. Nothing marked the boundary between standard police jurisdiction and the operations unfolding below. No caution tape. No painted lines. Only wet rock and patient silence. Quinn aligned her boots parallel to the drop. Weight distributed evenly across both feet. Breathing slowed. Hands dropped to holster level. Thumb rested on the safety catch. Radio static interrupted again. Dispatch requested status update. She ignored the frequency. Eyes tracked the disappearing trail of wet footprints leading into the dark. Muscles coiled. Spine straightened. She made her choice.
created_at"2026-09-02T15:03:32.176Z" 9/2/2026, 3:03:32 PM
model"qwen/qwen3.7-flash-20260727"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency387
moderation_latency(null)
generation_time39898
tokens_prompt1104
tokens_completion5336
native_tokens_prompt1065
native_tokens_completion4613
native_tokens_completion_images(null)
native_tokens_reasoning3418
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)
usage0.00063164
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788361412-TXfdLPwcXyimjWGWOlMK"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788361412-2oEPLtJAO6IWf7qMA38M"
upstream_id"chatcmpl-ad681889-9687-9b0e-b78d-5be211e0c016"
provider_responses
0
endpoint_id"5a9a0ee6-874a-4d03-92be-e5094c0df4e7"
id"chatcmpl-ad681889-9687-9b0e-b78d-5be211e0c016"
is_byokfalse
latency387
model_permaslug"qwen/qwen3.7-flash-20260727"
provider_name"Alibaba"
status200
total_cost0.00063164
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)
wordCount910
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)
23.08% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount910
totalAiIsms14
found
0
word"fractured"
count1
1
word"shattered"
count1
2
word"wavering"
count1
3
word"echoed"
count2
4
word"traced"
count1
5
word"footsteps"
count1
6
word"thundered"
count1
7
word"vibrated"
count1
8
word"weight"
count2
9
word"standard"
count1
10
word"silence"
count1
11
word"aligned"
count1
highlights
0"fractured"
1"shattered"
2"wavering"
3"echoed"
4"traced"
5"footsteps"
6"thundered"
7"vibrated"
8"weight"
9"standard"
10"silence"
11"aligned"
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
narrationSentences153
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount1
narrationSentences153
filterMatches
0"watch"
1"know"
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences153
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen19
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords910
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions22
wordCount910
uniqueNames7
maxNameDensity1.32
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Quinn12
Metropolitan2
Police2
Road1
Station1
Morris1
You3
persons
0"Quinn"
1"Police"
2"Morris"
3"You"
places
0"Road"
1"Station"
globalScore0.841
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences72
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount910
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences153
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs19
mean47.89
std36.36
cv0.759
sampleLengths
0107
1134
2111
36
415
528
625
726
831
941
1013
114
1216
1363
1481
1547
1655
1748
1859
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences153
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs174
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences153
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount911
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.018660812294182216
lyAdverbCount7
lyAdverbRatio0.007683863885839737
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences153
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences153
mean5.95
std3.17
cv0.534
sampleLengths
08
19
28
38
49
512
613
78
82
910
104
112
1214
134
1416
156
165
176
1812
193
202
2111
223
234
2414
257
264
277
283
298
309
313
325
332
348
353
367
373
384
392
405
415
425
435
444
454
468
477
4811
496
98.04% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.6993464052287581
totalSentences153
uniqueOpeners107
98.77% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount4
totalSentences135
matches
0"Officially decommissioned in ninety eight."
1"Only lantern glow and dim"
2"Somewhere a metal tray scraped"
3"Only wet rock and patient"
ratio0.03
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount19
totalSentences135
matches
0"Her trench coat soaked heavy"
1"He dropped behind a concrete"
2"She hit the fence, pulled"
3"She spotted a rusted maintenance"
4"She killed her flashlight."
5"She switched on her beam."
6"You are standing outside the"
7"I am chasing a man."
8"You know the passage rules."
9"She tapped her belt buckle."
10"He bypassed your checkpoint."
11"You want the runner, you"
12"They keep what they trap."
13"Her watch ticked steadily against"
14"He paused near a vendor"
15"He pushed off a wooden"
16"She stepped onto the crumbling"
17"She ignored the frequency."
18"She made her choice."
ratio0.141
100.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount89
totalSentences135
matches
0"Harlow Quinn drove through the"
1"Her trench coat soaked heavy"
2"Salt and pepper hair stuck"
3"Tonight the city tried to"
4"Boots scraped galvanized steel."
5"He dropped behind a concrete"
6"Quinn did not hesitate."
7"She hit the fence, pulled"
8"Water splashed up past her"
9"Radio chatter crackled in her"
10"Static washed over the frequency"
11"She spotted a rusted maintenance"
12"Iron kicked inward."
13"The locking mechanism shattered."
14"She killed her flashlight."
15"Texture shifted from smooth cement"
16"Camden Road Station."
17"A heavy iron gate blocked"
18"The other hung loose on"
19"Quinn slid underneath."
ratio0.659
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences135
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences19
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
93.4405%