Run: 2026-02-19-01KHTY25G7S30C00CE8ZSCZPX8

Run Details

Duration:
1m 4s
Cost:
$0.001329
Provider:
DeepInfra

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 rain fell in silver sheets, slicking the cobblestones of Soho with an oily sheen. Detective Harlow Quinn’s breath came in sharp, controlled bursts, a plume of steam in the frigid air. Her worn leather watch, strapped tight to her left wrist, was a damp weight against her skin. She ignored it, her entire world narrowed to the figure thirty yards ahead, a dark shape slipping between the glowing halos of streetlights. Tomás Herrera moved with a panicked grace, his shoulders hunched against the downpour. He glanced back, his warm brown eyes wide, and for a second, Harlow saw the glint of the Saint Christopher medallion at his throat. Then he was running again, his trainers slapping against the wet pavement. “Herrera! Stop!” Her voice was a hard crack, swallowed by the city’s nocturnal roar. It was an order, not a request, delivered with the military precision that still defined her bearing. He didn’t even break stride. He cut a hard left into a narrow service alley, and Harlow followed, her sharp jaw set. The alley was a canyon of dripping fire escapes and overflowing bins, the air thick with the smell of rotting produce and wet brick. Herrera was faster, lighter, but she was relentless. She’d chased down worse in her eighteen years. The memory of another chase, three years past, flickered at the edge of her consciousness—a different alley, a different suspect, the inexplicable silence after the gunshot that took Morris. She shoved the thought down, locking it away. This was now. He burst out of the alley’s far end onto a broader street, skidding on the wet tarmac. Harlow gained ground, her coat heavy with water. He was heading for Camden, away from the bright lights and crowds. The sensible part of her mind, the part that wrote reports and followed procedure, told her to call it in, to set up a perimeter. But procedure hadn’t found answers for Morris. Procedure didn’t explain the things she’d started to see in the corners of cases, the inconsistencies that smelled of something other than human corruption. Herrera vanished down a set of grimy steps leading to an abandoned Tube station entrance, a black mouth yawning open in the sidewalk. A sign, rusted and crooked, read ‘Camden Town’ but the station had been closed for years. Harlow slowed, her hand going to the service weapon holstered at her hip. This was it. His bolt-hole. She descended the steps cautiously, the sound of the rain fading behind her, replaced by the drip of water and the hum of something else, something low and electrical. The air changed, losing the chill of the night and gaining a cloying, spicy warmth. At the bottom of the steps, a figure emerged from the shadows—a tall, gaunt man with skin the colour of old parchment, blocking a heavy iron door. “Market’s not for your kind, detective.” His voice was a dry rustle, like pages turning. Harlow’s posture straightened, her right hand resting lightly on her hip, inches from her gun. “My kind?” “The daylight kind. The kind that asks for warrants.” A thin smile played on his lips. “You’re lost.” From beyond the door, she heard a burst of strange, melodic laughter and the clatter of something ceramic. Herrera was in there. She could feel it. This was the place her informants had whispered about, the place that never appeared on any official map. The Veil Market. “The man who just came down here. Tomás Herrera. I need to speak with him.” The gaunt man’s smile didn’t reach his eyes. “Many people come and go. I see no one.” Harlow took a step forward. The man didn’t move, but the air around him seemed to thicken. “Step aside.” “Do you have a token?” he asked, his gaze dropping to her empty hands. “A bone for passage? No? Then you have no business here.” Her fingers tightened. She could arrest this man for obstruction. She could radio for backup and have a dozen uniforms flood this forgotten hole in the ground in ten minutes. They’d tear the place apart. But what would they find? A damp tunnel? Some stray cats? She knew, with a cold certainty that had grown since Morris died, that they wouldn’t find the market. They wouldn’t see what she was seeing. This door, this guardian, it would vanish, and she’d be left with another dead end, another unexplained blank spot in her report. Morris had followed a lead into the unexplained. He’d never walked out. The choice was a physical weight on her shoulders. Procedure demanded she hold the line, wait for a world that made sense. But the truth—the truth about Herrera’s off-the-books patients, the truth about what really happened three years ago—was behind that door. It was in that warm, strange air and that alien laughter. She made a decision. Her hand moved away from her gun. She met the man’s gaze, her own brown eyes hard and unwavering. “What does it cost? To look around?” The rustle became a low chuckle. “For you? More than you have. But curiosity… curiosity has its own currency.” He studied her, his head tilted like a bird’s. “You have the look of someone who has already paid a price. You may enter. But remember, detective, you are a guest here. The rules are not your rules. The laws are not your laws. Cause a disturbance, and the market itself will expel you. Permanently.” He didn’t move, but the iron door swung inward without a sound, revealing not a dank tunnel, but a sprawling, impossible space. The abandoned Tube station had been transformed. stalls made of polished brass and dark wood lined the curved platforms, lit by floating orbs of gentle green light that cast long, dancing shadows. The air was thick with the scent of exotic spices, ozone, and something metallic. Creatures—some almost human, others decidedly not—moved through the crowd, bartering in a dozen languages. A vendor held up a vial of swirling silver liquid next to a cage containing something with too many eyes. And there, weaving through the crowd with the familiarity of a regular, was the back of Tomás Herrera’s jacket. Harlow Quinn took a deep breath of the strange, spicy air, and crossed the threshold. The door closed behind her with a soft, final click, sealing her inside. The sound of the London rain was gone, replaced by the murmur of the market. She was in his world now.
created_at"2026-02-19T12:30:11.468Z" 2/19/2026, 12:30:11 PM
model"deepseek/deepseek-chat-v3.1"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency742
moderation_latency(null)
generation_time63445
tokens_prompt1157
tokens_completion1639
native_tokens_prompt1003
native_tokens_completion1416
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached5
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.00132887
router(null)
provider_responses
0
endpoint_id"012f7d1f-23d4-4d03-9aa3-432d8ad82757"
id"cmpl-55e1810f5ca5435385e35ee61850e84c"
is_byokfalse
latency75
model_permaslug"deepseek/deepseek-chat-v3.1"
provider_name"DeepInfra"
status200
api_type"completions"
id"gen-1771504211-zPsl22JQeia3ftl8ykJe"
upstream_id"cmpl-55e1810f5ca5435385e35ee61850e84c"
total_cost0.00132887
cache_discount3.99e-7
upstream_inference_cost0
provider_name"DeepInfra"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags6
adverbTagCount0
adverbTags(empty)
dialogueSentences13
tagDensity0.462
leniency0.923
rawRatio0
effectiveRatio0
86.23% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1089
totalAiIsmAdverbs3
found
0
adverb"cautiously"
count1
1
adverb"lightly"
count1
2
adverb"really"
count1
highlights
0"cautiously"
1"lightly"
2"really"
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)
54.09% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1089
totalAiIsms10
found
0
word"weight"
count2
1
word"glint"
count1
2
word"flickered"
count1
3
word"silence"
count1
4
word"chill"
count1
5
word"warmth"
count1
6
word"could feel"
count1
7
word"unwavering"
count1
8
word"dancing"
count1
highlights
0"weight"
1"glint"
2"flickered"
3"silence"
4"chill"
5"warmth"
6"could feel"
7"unwavering"
8"dancing"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"air was thick with"
count1
highlights
0"The air was thick with"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences75
matches(empty)
85.71% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences75
filterMatches
0"watch"
hedgeMatches
0"started to"
1"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences83
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen46
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1080
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions31
wordCount941
uniqueNames13
maxNameDensity0.85
worstName"Harlow"
maxWindowNameDensity1.5
worstWindowName"Harlow"
discoveredNames
Soho1
Harlow8
Quinn2
Herrera6
Saint1
Christopher1
Morris4
Camden1
Tube2
Veil1
Market1
Tomás2
London1
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Saint"
4"Christopher"
5"Morris"
6"Tomás"
places
0"Soho"
1"London"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences60
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.926
wordCount1080
matches
0"not a dank tunnel, but a sprawling, impossible space"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences83
matches
0"died, that they"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs23
mean46.96
std29.64
cv0.631
sampleLengths
072
149
236
397
493
557
671
715
817
918
1047
1115
1217
1319
1425
1593
1612
1753
1830
1974
20102
2119
2249
95.91% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences75
matches
0"been transformed"
1"was gone"
68.42% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs152
matches
0"was running"
1"was heading"
2"was seeing"
5.16% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount6
semicolonCount0
flaggedSentences4
totalSentences83
ratio0.048
matches
0"The memory of another chase, three years past, flickered at the edge of her consciousness—a different alley, a different suspect, the inexplicable silence after the gunshot that took Morris."
1"At the bottom of the steps, a figure emerged from the shadows—a tall, gaunt man with skin the colour of old parchment, blocking a heavy iron door."
2"But the truth—the truth about Herrera’s off-the-books patients, the truth about what really happened three years ago—was behind that door."
3"Creatures—some almost human, others decidedly not—moved through the crowd, bartering in a dozen languages."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount478
adjectiveStacks0
stackExamples(empty)
adverbCount11
adverbRatio0.02301255230125523
lyAdverbCount1
lyAdverbRatio0.0020920502092050207
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences83
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences83
mean13.01
std8.1
cv0.623
sampleLengths
015
117
217
323
413
524
612
714
817
95
1017
1124
128
138
1429
158
163
1717
188
1912
2025
217
2224
2323
2416
2513
263
272
2829
2915
3027
3115
3215
332
3416
352
3618
374
384
3918
403
4115
428
439
445
4512
462
4714
4811
493
56.22% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.37349397590361444
totalSentences83
uniqueOpeners31
45.05% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences74
matches
0"Then he was running again,"
ratio0.014
63.24% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences74
matches
0"Her worn leather watch, strapped"
1"She ignored it, her entire"
2"He glanced back, his warm"
3"Her voice was a hard"
4"It was an order, not"
5"He didn’t even break stride."
6"He cut a hard left"
7"She’d chased down worse in"
8"She shoved the thought down,"
9"He burst out of the"
10"He was heading for Camden,"
11"She descended the steps cautiously,"
12"His voice was a dry"
13"She could feel it."
14"he asked, his gaze dropping"
15"Her fingers tightened."
16"She could arrest this man"
17"She could radio for backup"
18"They’d tear the place apart."
19"She knew, with a cold"
ratio0.392
7.30% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount67
totalSentences74
matches
0"The rain fell in silver"
1"Detective Harlow Quinn’s breath came"
2"Her worn leather watch, strapped"
3"She ignored it, her entire"
4"Tomás Herrera moved with a"
5"He glanced back, his warm"
6"Her voice was a hard"
7"It was an order, not"
8"He didn’t even break stride."
9"He cut a hard left"
10"The alley was a canyon"
11"Herrera was faster, lighter, but"
12"She’d chased down worse in"
13"The memory of another chase,"
14"She shoved the thought down,"
15"This was now."
16"He burst out of the"
17"Harlow gained ground, her coat"
18"He was heading for Camden,"
19"The sensible part of her"
ratio0.905
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences74
matches(empty)
ratio0
89.29% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences40
technicalSentenceCount3
matches
0"Then he was running again, his trainers slapping against the wet pavement."
1"The memory of another chase, three years past, flickered at the edge of her consciousness—a different alley, a different suspect, the inexplicable silence after…"
2"Procedure didn’t explain the things she’d started to see in the corners of cases, the inconsistencies that smelled of something other than human corruption."
41.67% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags6
uselessAdditionCount1
matches
0"he asked, his gaze dropping to her empty hands"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences13
tagDensity0.077
leniency0.154
rawRatio0
effectiveRatio0
79.9427%