Run: 2026-09-10-01M25DV8X55JFDERMY31J2FQVK

Run Details

Duration:
10.2s
Cost:
$0.000823
Provider:
DeepSeek

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 pavement, each drop a tiny fist against the city's concrete skin. Harlow Quinn moved through the downpour like a blade through silk, her worn trench coat plastered to her shoulders, water dripping from the brim of her cap. Her quarry, a wiry blur of a man, darted between the neon smears of late-night takeaways and the yawning mouths of closed shopfronts. Tomás Herrera. She'd been tailing him for three hours, ever since he'd left that bar in Soho. The Raven's Nest. A known nest of vipers. He glanced back, eyes wide with animal panic, and slipped down a service alley. Harlow didn't run. Running was for rookies. She moved with a measured, ground-eating stride that ate the distance between them, her breath a steady plume in the cold air. The alley stank of rot and wet cardboard. Her boots splashed through a puddle slick with diesel, the iridescent sheen swirling like an oil painting left in the gutter. He vaulted a low brick wall. She took it at a pace, one hand planted on the wet stone, her body flowing over it with a gymnast's economy. Beyond was a dead end. A door, heavy and iron, set into the grimy brick. It looked ancient, out of place, the iron scrollwork on its hinges ornate and rusted. A single green bulb buzzed above it, casting a sickly light on a symbol carved into the wood. A raven in flight. Not the bar. Different. Her instincts, honed by eighteen years on the force, screamed at her. This was a threshold. A line. Herrera shoved a hand into his pocket, fumbling. He pulled something out, his fingers clumsy with fear. A small, pale object. A bone. He pressed it against the door. A soft click, like a key turning in a lock a thousand years old. The door swung inward with a groan that vibrated in her teeth. He vanished into the black maw beyond. Harlow reached the door seconds later. The rain pelted her back, urging her forward, but her feet were lead. This wasn't a normal building. The symbol, the bone, the way he'd used it. This was supernatural. This was the world that had swallowed DS Morris whole three years ago and spat out nothing but a folded flag and a hollow funeral. Her partner. Her friend. The Met had called it a gas leak. She'd known better. She'd seen the thing in the warehouse that night. The thing that wasn't a man. Her fingers brushed the iron handle. It was cold, colder than the night, colder than the rain. A cold that seeped into the bone, a promise of something ancient and indifferent. The door was a threshold to the Veil Market. The stories whispered in the canteen, the rumours passed between constables who'd seen too much and drunk too little. A place that moved with the moon, a place beneath the city where you could buy anything for a price that had nothing to do with money. She could radio it in. Call for backup. They'd come with torches and battering rams, and they'd find nothing but an empty brick wall. She knew that with a certainty that settled in her gut like a stone. They'd laugh at her. The detective who chased ghosts. The one whose partner died under 'unexplained circumstances'. They'd already written her off as a cautionary tale. Morris's face flashed in her mind. His easy grin, the way he'd always called her 'Harls', the way he'd walked into that warehouse without a second thought. He'd wanted answers too. And the answers had killed him. The rain intensified, a curtain of water between her and the world she understood. Procedural rules. Warrants. Probable cause. None of that applied here. This was the edges of the map. This was the territory of the things that made monsters of men. Her hand tightened on the handle. She wasn't a true believer in all this hocus-pocus nonsense. She was a police officer. And Tomás Herrera was a suspect. A man who ran. A man who provided medical care to things that weren't human. He knew something about Morris. He had to. A siren wailed in the distance, a lonely sound in the drowned city. It was a reminder of the world she was leaving behind. The rational world. The world of paperwork and procedure. The world where her partner's death was a closed file. Harlow Quinn pulled out her service pistol, checked the magazine, and chambered a round. The sound was a sharp, solid click in the wet silence. She took a breath, filling her lungs with the smell of rain and decay and something else, something like ozone and old parchment that drifted from the open door. It was the smell of secrets. She stepped through the doorway, and the world she knew fell away like a discarded skin.
created_at"2026-09-10T10:29:36.298Z" 9/10/2026, 10:29:36 AM
model"deepseek/deepseek-v4.1-flash-20260910"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency809
moderation_latency(null)
generation_time10211
tokens_prompt1104
tokens_completion1501
native_tokens_prompt1029
native_tokens_completion1334
native_tokens_completion_images(null)
native_tokens_reasoning293
native_tokens_cached895
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)
usage0.000823185
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1789036176-nZevQeVD0LOT0MqT2fg6"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1789036176-tbAZZHeeYDz8auZQR1el"
upstream_id"e5a44c74-a406-4251-9392-fc5a06173115"
provider_responses
0
endpoint_id"fd104bc8-535a-4d31-a847-a8e402e86a02"
id"e5a44c74-a406-4251-9392-fc5a06173115"
is_byokfalse
latency333
model_permaslug"deepseek/deepseek-v4.1-flash-20260910"
provider_name"DeepSeek"
status200
total_cost0.000823185
cache_discount0.000131565
upstream_inference_cost0
provider_name"DeepSeek"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
0.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags2
adverbTagCount1
adverbTags
0"the way he'd always [always]"
dialogueSentences0
tagDensity1
leniency1
rawRatio0.5
effectiveRatio0.5
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount815
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)
63.19% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount815
totalAiIsms6
found
0
word"silk"
count1
1
word"measured"
count1
2
word"vibrated"
count1
3
word"maw"
count1
4
word"reminder"
count1
5
word"silence"
count1
highlights
0"silk"
1"measured"
2"vibrated"
3"maw"
4"reminder"
5"silence"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"without second thought"
count1
highlights
0"without a second thought"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells1
narrationSentences88
matches
0"y with fear"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences88
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences88
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
totalWords815
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions20
wordCount801
uniqueNames11
maxNameDensity0.5
worstName"Harlow"
maxWindowNameDensity1
worstWindowName"Herrera"
discoveredNames
Quinn2
Herrera3
Soho1
Raven1
Nest1
Morris3
Met1
Veil1
Market1
Tomás2
Harlow4
persons
0"Quinn"
1"Herrera"
2"Raven"
3"Morris"
4"Met"
5"Tomás"
6"Harlow"
places
0"Soho"
1"Veil"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences56
glossingSentenceCount1
matches
0"something like ozone and old parchment that"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount815
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences88
matches
0"left that bar"
62.29% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs12
mean67.92
std24.99
cv0.368
sampleLengths
089
172
2102
362
491
586
664
737
893
943
1060
1116
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences88
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs115
matches
0"was leaving"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences88
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount557
adjectiveStacks0
stackExamples(empty)
adverbCount5
adverbRatio0.008976660682226212
lyAdverbCount1
lyAdverbRatio0.0017953321364452424
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences88
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences88
mean9.26
std6.65
cv0.719
sampleLengths
014
127
223
32
415
53
65
714
83
94
1022
118
1221
136
1422
155
1610
1715
1818
194
203
211
2212
234
242
258
269
274
282
296
3014
3112
327
336
3413
355
369
373
3825
392
402
418
423
439
446
456
4611
4714
489
4919
35.23% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.2727272727272727
totalSentences88
uniqueOpeners24
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences79
matches(empty)
ratio0
57.97% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount32
totalSentences79
matches
0"Her quarry, a wiry blur"
1"She'd been tailing him for"
2"He glanced back, eyes wide"
3"She moved with a measured,"
4"Her boots splashed through a"
5"He vaulted a low brick"
6"She took it at a"
7"It looked ancient, out of"
8"Her instincts, honed by eighteen"
9"He pulled something out, his"
10"He pressed it against the"
11"He vanished into the black"
12"She'd known better."
13"She'd seen the thing in"
14"Her fingers brushed the iron"
15"It was cold, colder than"
16"She could radio it in."
17"They'd come with torches and"
18"She knew that with a"
19"They'd laugh at her."
ratio0.405
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount73
totalSentences79
matches
0"Harlow Quinn moved through the"
1"Her quarry, a wiry blur"
2"She'd been tailing him for"
3"The Raven's Nest."
4"A known nest of vipers."
5"He glanced back, eyes wide"
6"Harlow didn't run."
7"Running was for rookies."
8"She moved with a measured,"
9"The alley stank of rot"
10"Her boots splashed through a"
11"He vaulted a low brick"
12"She took it at a"
13"A door, heavy and iron,"
14"It looked ancient, out of"
15"A single green bulb buzzed"
16"A raven in flight."
17"Her instincts, honed by eighteen"
18"This was a threshold."
19"Herrera shoved a hand into"
ratio0.924
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences79
matches(empty)
ratio0
56.28% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences33
technicalSentenceCount4
matches
0"She moved with a measured, ground-eating stride that ate the distance between them, her breath a steady plume in the cold air."
1"A cold that seeped into the bone, a promise of something ancient and indifferent."
2"The stories whispered in the canteen, the rumours passed between constables who'd seen too much and drunk too little."
3"She took a breath, filling her lungs with the smell of rain and decay and something else, something like ozone and old parchment that drifted from the open door…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
79.1654%