Run: 2026-10-20-01M5C6MMN0CTRC7CTVR9ZEAMQ6

Run Details

Duration:
12.3s
Cost:
$0.003576
Provider:
Together

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
The rain hit Camden like a punishment. It came off the canal in sheets, drummed on the awnings of shuttered kebab shops, and turned the pavement into a black mirror that kept breaking under Harlow Quinn’s boots. She kept her pace steady, shoulders squared, eyes fixed on the figure forty yards ahead—short, dark-haired, moving with the hunched urgency of a man who knew exactly how much trouble followed him. Tomás Herrera. Former paramedic. No license, no fixed address, a scar on his left forearm that her file said came from a knife, though the file didn’t say whose knife or why. He had a Saint Christopher medallion around his neck and a satchel strap cutting across his chest. He had been leaving the Raven’s Nest an hour ago with the collar of his jacket turned up and the look of a man carrying something he shouldn’t. Quinn had been waiting in the rain ever since. She didn’t shout. She didn’t break into a sprint. She gave him ten seconds to notice her, and when he glanced back—just once, under the sickly orange glow of a streetlamp—she saw his face change. Recognition. Then fear. Then the decision. He ran. Quinn ran too. The chase went west along the high street, past a night bus sighing at its stop and a cluster of drinkers who scattered with curses. Her coat snapped around her knees. Rain found the gap at her collar and ran cold down her spine. She was forty-one years old and had eighteen years of service behind her, and she could still move when she had to. Her worn leather watch bit into her wrist as she pumped her arms. Her breath came in hard, controlled bursts. Military precision, Morris used to call it. You even panic like you’re on parade. Morris had been dead three years. She still heard him at the worst possible moments. Herrera cut left into a side street, vaulted a low fence, and landed badly on the other side. Quinn saw him stumble, saw his hand go to his satchel, and saw something small and pale spin out of his grip and skitter across the wet tarmac. He didn’t stop for it. He disappeared between two buildings, his footsteps echoing off brick and metal. Quinn reached the fence. She didn’t vault it. She went through the gap where the chain-link had been peeled back, her shoulder scraping rust. The object Herrera had dropped lay in the gutter, half submerged. She scooped it up without breaking stride, and her fingers closed around something that was not a stone and not a coin. Bone. A token, carved with a spiral and a hole through the centre, warm despite the rain. She shoved it into her pocket and kept running. The buildings narrowed. The streetlamps thinned. Ahead, a construction hoarding blocked the road, plastered with a council notice about improvement works that had clearly been abandoned years ago. Beyond it, the dark mouth of an old Tube station. The sign above the entrance had been painted over, but the shape of it remained—the rounded arch, the ironwork, the tiled lintel. A chain hung loose across the steps. Herrera ducked under it and vanished into the stairwell. Quinn stopped at the top. Her radio had been hissing static for the last five minutes. She keyed it anyway. “Control, this is Quinn. Foot pursuit, Camden. Suspect entering disused Underground station north side of—” She looked up. The street sign was obscured by grime. “—north of the lock. Request backup.” The radio answered with a crackle and a voice she couldn’t make out. She tried again. Nothing. The stairwell breathed up at her. Warm air, wet stone, a smell of earth and copper and something sweetly chemical. She could hear sounds from below—not the hollow echo of an empty tunnel, but voices. Many voices. A low murmur, the clink of glass, the scrape of a chair. Somewhere deeper, a burst of laughter. She knew about the Veil Market. Every detective in the Met had heard the whispers, usually from informants who were drunk or desperate or both. A market that moved with the full moon. A place beneath the city where you could buy things that didn’t exist, or shouldn’t. She had never seen it. She had never wanted to. Her job was the world above—the one with warrants and custody records and CCTV. But Herrera was down there. Herrera, who had been treating people off the books for years, stitching up wounds that never got reported, prescribing things that never came from a pharmacy. Herrera, who knew something about Morris. She was sure of it. She had no evidence. She had a feeling, and she had a bone token in her pocket, and she had the memory of her partner’s voice saying, You even panic like you’re on parade. She took the steps two at a time. The descent was longer than it should have been. The tiled walls gave way to brick, then to concrete slick with seepage. The light from the street faded. The chain at the bottom of the stairs had been cut, and a heavy door stood open just wide enough for a man to slip through. Quinn pressed herself against the frame and listened. The voices were louder now. She could smell incense, charcoal smoke, and the sharp mineral tang of the river seeping into old tunnels. She took out the bone token. It was still warm. She turned it over. On the other side, someone had scratched a single word: pass. “Pass,” she murmured. “Right.” She went through the door. The market opened before her like a wound. The old platform had been transformed—stalls built from pallets and scaffolding, tarpaulins strung overhead, bulbs hanging on cords that looped from the ceiling. The tracks were still there, two dark rails running through the middle of everything, and people walked between them as if it were the most natural thing in the world. Hooded figures. Women in silk. Men in suits with the looks of accountants. A child—a child—selling glass vials from a tray. The air was thick with smoke and steam and the low hum of commerce. Quinn kept her head down. She was still in her coat, still rain-soaked, still obviously police. She could feel eyes on her. The token in her fist was a cold comfort. Herrera was fifty feet ahead, moving fast between the stalls. She saw the flash of his medallion under a bulb, saw him glance back once more. Their eyes met. Then he was gone, swallowed by the crowd. Quinn pushed forward. A man with a burn-scarred face stepped into her path. She showed him the token and did not slow down. He watched her pass with a smile that was all teeth. The market went deeper. The platform ended, but the tunnel did not. She followed the flow of people down a ramp, past a stall selling bottled memories, past a woman who whispered her name—her real name, not her rank—and past a curtained alcove where someone was crying quietly. Her heart hammered. Her hand was inside her coat, on the grip of her radio, useless as a brick. She had no warrant. No backup. No authority down here except what she could carry. She was a detective who had just walked into a place that did not appear on any map, chasing a man who might know why her partner died, and every instinct she had was telling her to turn around. She thought of Morris. She thought of the way he had looked at her in the hospital, before the end, when he had tried to tell her something and the words had come out wrong. She kept walking. The tunnel curved. The lights grew dimmer. The crowd thinned. And ahead, at the edge of the darkness, a door closed—a heavy metal door, rusted and riveted, with a symbol on it she didn’t recognise. Herrera’s symbol. The spiral. Quinn reached the door and put her hand against it. It was cold. The market murmured behind her, indifferent. The bone token in her pocket felt heavier than it should. She could call it in. She could wait for morning. She could pretend she had never followed him this far. She pushed the door open. The darkness beyond smelled of rain and old stone and something else—something patient. Somewhere in that darkness, Tomás Herrera was waiting for her. And Quinn stepped through.
created_at"2026-10-20T08:25:25.415Z" 10/20/2026, 8:25:25 AM
model"deepseek/deepseek-v4.1-flash-20261017"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency82
moderation_latency(null)
generation_time12300
tokens_prompt888
tokens_completion3338
native_tokens_prompt853
native_tokens_completion2955
native_tokens_completion_images(null)
native_tokens_reasoning1158
native_tokens_cached768
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)
usage0.003576108
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1792484725-2uuLZiPZgsVCzNwB8AHu"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1792484725-muwL4JIYMtWE4icikXTD"
upstream_id"cd89e8d8-aws_ue1"
provider_responses
0
endpoint_id"34cd16bf-a525-40b2-beeb-5f1809202c06"
id"cd89e8d8-aws_ue1"
is_byokfalse
latency53
model_permaslug"deepseek/deepseek-v4.1-flash-20261017"
provider_name"Together"
status200
total_cost0.003576108
cache_discount0.000225792
upstream_inference_cost0
provider_name"Together"
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
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences4
tagDensity0.5
leniency1
rawRatio0
effectiveRatio0
96.50% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1427
totalAiIsmAdverbs1
found
0
adverb"sweetly"
count1
highlights
0"sweetly"
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)
78.98% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1427
totalAiIsms6
found
0
word"down her spine"
count1
1
word"footsteps"
count1
2
word"echoing"
count1
3
word"echo"
count1
4
word"silk"
count1
5
word"could feel"
count1
highlights
0"down her spine"
1"footsteps"
2"echoing"
3"echo"
4"silk"
5"could feel"
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
narrationSentences136
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount1
narrationSentences136
filterMatches
0"watch"
1"notice"
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences138
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen39
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1414
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions39
wordCount1391
uniqueNames15
maxNameDensity0.79
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Quinn"
discoveredNames
Camden1
Harlow1
Quinn11
Herrera10
Saint1
Christopher1
Raven1
Nest1
Morris4
Tube1
Veil1
Market1
Met1
You2
Tomás2
persons
0"Camden"
1"Harlow"
2"Quinn"
3"Herrera"
4"Saint"
5"Christopher"
6"Raven"
7"Morris"
8"Market"
9"You"
10"Tomás"
places(empty)
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences85
glossingSentenceCount1
matches
0"-soaked, still obviously police"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.707
wordCount1414
matches
0"not the hollow echo of an empty tunnel, but voices"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences138
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs37
mean38.22
std30.24
cv0.791
sampleLengths
069
177
29
341
42
53
6100
715
863
983
1076
115
1246
1317
1455
1572
1676
178
1885
1925
204
215
2296
2331
2429
258
2634
2767
2854
2935
303
3135
324
3330
3420
355
3627
87.20% Passive voice overuse
Target: ≤2% passive sentences
passiveCount7
totalSentences136
matches
0"been peeled"
1"been abandoned"
2"been painted"
3"was obscured"
4"got reported"
5"been transformed"
6"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs234
matches
0"was crying"
1"was telling"
2"was waiting"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount13
semicolonCount0
flaggedSentences10
totalSentences138
ratio0.072
matches
0"She kept her pace steady, shoulders squared, eyes fixed on the figure forty yards ahead—short, dark-haired, moving with the hunched urgency of a man who knew exactly how much trouble followed him."
1"She gave him ten seconds to notice her, and when he glanced back—just once, under the sickly orange glow of a streetlamp—she saw his face change."
2"The sign above the entrance had been painted over, but the shape of it remained—the rounded arch, the ironwork, the tiled lintel."
3"She could hear sounds from below—not the hollow echo of an empty tunnel, but voices."
4"Her job was the world above—the one with warrants and custody records and CCTV."
5"The old platform had been transformed—stalls built from pallets and scaffolding, tarpaulins strung overhead, bulbs hanging on cords that looped from the ceiling."
6"A child—a child—selling glass vials from a tray."
7"She followed the flow of people down a ramp, past a stall selling bottled memories, past a woman who whispered her name—her real name, not her rank—and past a curtained alcove where someone was crying quietly."
8"And ahead, at the edge of the darkness, a door closed—a heavy metal door, rusted and riveted, with a symbol on it she didn’t recognise."
9"The darkness beyond smelled of rain and old stone and something else—something patient."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1409
adjectiveStacks0
stackExamples(empty)
adverbCount39
adverbRatio0.027679205110007096
lyAdverbCount8
lyAdverbRatio0.0056777856635912
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences138
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences138
mean10.25
std8.43
cv0.823
sampleLengths
07
130
232
32
42
528
617
728
89
93
106
1126
121
132
143
152
163
1725
186
1913
2022
2113
227
237
247
256
269
2718
2828
295
3012
314
324
3316
3411
3522
361
3716
389
393
403
4122
4210
4322
447
459
465
4711
484
4918
26.09% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats33
diversityRatio0.2608695652173913
totalSentences138
uniqueOpeners36
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount4
totalSentences123
matches
0"Then the decision."
1"Somewhere deeper, a burst of"
2"Then he was gone, swallowed"
3"Somewhere in that darkness, Tomás"
ratio0.033
37.89% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount56
totalSentences123
matches
0"It came off the canal"
1"She kept her pace steady,"
2"He had a Saint Christopher"
3"He had been leaving the"
4"She didn’t shout."
5"She didn’t break into a"
6"She gave him ten seconds"
7"Her coat snapped around her"
8"She was forty-one years old"
9"Her worn leather watch bit"
10"Her breath came in hard,"
11"You even panic like you’re"
12"She still heard him at"
13"He didn’t stop for it."
14"He disappeared between two buildings,"
15"She didn’t vault it."
16"She went through the gap"
17"She scooped it up without"
18"She shoved it into her"
19"Her radio had been hissing"
ratio0.455
12.85% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount110
totalSentences123
matches
0"The rain hit Camden like"
1"It came off the canal"
2"She kept her pace steady,"
3"He had a Saint Christopher"
4"He had been leaving the"
5"Quinn had been waiting in"
6"She didn’t shout."
7"She didn’t break into a"
8"She gave him ten seconds"
9"Quinn ran too."
10"The chase went west along"
11"Her coat snapped around her"
12"Rain found the gap at"
13"She was forty-one years old"
14"Her worn leather watch bit"
15"Her breath came in hard,"
16"Military precision, Morris used to"
17"You even panic like you’re"
18"Morris had been dead three"
19"She still heard him at"
ratio0.894
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences123
matches(empty)
ratio0
37.04% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences54
technicalSentenceCount8
matches
0"It came off the canal in sheets, drummed on the awnings of shuttered kebab shops, and turned the pavement into a black mirror that kept breaking under Harlow Qu…"
1"She kept her pace steady, shoulders squared, eyes fixed on the figure forty yards ahead—short, dark-haired, moving with the hunched urgency of a man who knew ex…"
2"Every detective in the Met had heard the whispers, usually from informants who were drunk or desperate or both."
3"Herrera, who had been treating people off the books for years, stitching up wounds that never got reported, prescribing things that never came from a pharmacy."
4"The old platform had been transformed—stalls built from pallets and scaffolding, tarpaulins strung overhead, bulbs hanging on cords that looped from the ceiling…"
5"The tracks were still there, two dark rails running through the middle of everything, and people walked between them as if it were the most natural thing in the…"
6"He watched her pass with a smile that was all teeth."
7"She followed the flow of people down a ramp, past a stall selling bottled memories, past a woman who whispered her name—her real name, not her rank—and past a c…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount0
matches(empty)
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount1
fancyTags
0"she murmured (murmur)"
dialogueSentences4
tagDensity0.25
leniency0.5
rawRatio1
effectiveRatio0.5
79.2177%