Run: 2026-09-03-01M1KBS4KRS0TSE3491VP6ATGY

Run Details

Duration:
4m 49s
Cost:
$0.000532
Provider:
Inceptron

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 came down in sheets, hammering the pavement so hard it bounced back up in a fine mist that clung to the sodium glow of the streetlamps. Detective Harlow Quinn's boots slapped against the wet cobbles of the alley, each stride sending cold spray up the backs of her calves. She'd shed her coat three blocks back—too heavy, too much drag—and now her shirt clung to her skin like a second layer of cold. The figure ahead moved with a predator's economy. Black coat, hood up, but she'd caught the face in the window of a closed kebab shop before the runner had taken off. Thirty seconds of eye contact through smeared glass, and then the table flipped, glasses shattered, and the chase began. He knew these streets. Kept to the narrow passages, the cut-throughs that smelled of rot and urine, the places where the CCTV had blind spots. Quinn's lungs burned but she kept the pace, her worn leather watch slapping against her wrist with every pump of her arms. Military precision had its uses; it taught you to ignore the body when the body wanted to quit. He vaulted a low railing, landed wrong, stumbled. Quinn closed the gap. Five metres. Four. She could hear his breath now, ragged and wet, same rhythm as her own. The runner cut left, through a doorway she hadn't noticed—an old service entrance, its paint peeling in long curls like dead skin. Quinn skidded on the wet tiles, caught herself on the frame. The corridor beyond sloped downward and the lights were dead. Just black, swallowing the shape of him whole. She pulled her torch from her belt. The beam cut a weak circle through the dark, catching dust motes and the glisten of damp brick. The sound of his footsteps echoed from somewhere below, bouncing off walls she couldn't see. "Metropolitan Police." Her voice came out hard and clipped, the voice she used in interviews. "Stop running. This ends badly for you either way." The footsteps didn't stop. She went down. The stairs were narrow, worn smooth by decades of use, and the walls pressed in close enough that her shoulders scraped either side. Water dripped somewhere, a steady metronome. The air changed—cooler, stale, carrying a faint metallic tang she couldn't place. Not rust. Something else. At the bottom, a corridor opened into a wider space. The torch revealed brick arches, Victorian engineering, and a set of heavy iron gates that should have been locked. They stood ajar, chains hanging loose like shed skin. Beyond the gates, shadows moved. Figures. A lot of them. Quinn killed the torch and pressed herself against the wall. Her heart hammered against her ribs as she waited for her eyes to adjust. There was light ahead—dim, greenish, flickering like gas flames. It leaked through cracks in the masonry and cast moving silhouettes on the walls. She edged closer. The runner had disappeared into a warren of stalls and temporary structures that filled what must have been an abandoned Tube station. Shelves stacked with jars of things she couldn't identify, bunches of dried herbs hanging from strings, glass cases holding objects that glinted with unsavoury intent. The green light came from lanterns, wrought iron and filigree, swinging gently in a breeze that had no business existing underground. Pallets of goods, crates stencilled with symbols she didn't recognise. A woman in a heavy cloak haggled with a man whose face was half-covered in tattoos, their voices low and urgent. A child sat cross-legged beside a cage of small, winged things that clicked their beaks like castanets. Quinn's throat tightened. She'd heard rumours. Whispers from informants who'd gone quiet or gone missing. Stories about a market that moved with the moon, that sold the kind of things the law couldn't name. The runner was between two stalls now, fifty metres ahead, pausing to speak with someone. A tall figure in a long coat, hands clasped behind the back. They exchanged words, then the runner pointed back over his shoulder, directly at Quinn. She froze. But the distance was too great, the light too dim. He couldn't have seen her. The tall figure turned. Even at this distance, even in the dark, Quinn felt the weight of that gaze land on her like something physical. The temperature in the tunnel dropped. The clicking of the small winged things stopped. Her hand went to the grip of her pistol. The leather of her watch strap creaked as her fist tightened. The runner was already moving again, deeper into the market, weaving between the stalls, heading for a corridor on the far side. The tall figure didn't move. Just stood there, watching, a silent barrier between Quinn and her quarry. She had options. Turn back, call for backup, try again another day. Let the runner disappear into this strange world and carry whatever secrets he held back into the city she was sworn to protect. Or follow him deeper, past the watching figure, into a place where her authority meant nothing. Her partner's face surfaced. DS Morris, the way he'd looked in the split second before the case went bad—eyes wide, mouth open, a question that never quite became a word. Three years, and she still didn't know what had killed him. The file was classified under a dozen different codes, reports contradicting each other at every turn. But she remembered the last place he'd been called to. A location near an old Tube station that didn't exist on any map. The runner disappeared into the far corridor. Quinn stepped out from the shadows and walked through the market, past the stalls and the green lanterns and the people whose eyes followed her like a procession of silent judges. She didn't break stride. The tall figure watched her approach, unmoving, and when she passed within a foot of them, they didn't speak. She followed the corridor, and the darkness swallowed her whole.
created_at"2026-09-03T10:07:09.447Z" 9/3/2026, 10:07:09 AM
model"deepseek/deepseek-v4-flash-20260731"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency712
moderation_latency(null)
generation_time277862
tokens_prompt1104
tokens_completion1701
native_tokens_prompt1003
native_tokens_completion1436
native_tokens_completion_images(null)
native_tokens_reasoning228
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)
usage0.00053247
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788430029-WAVETV1HVDMNcPjSjx3M"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788430029-mapi1y0zHEc561PKM3uY"
upstream_id"chatcmpl-c29b48fac16f0d652abf93d075ffebc0"
provider_responses
0
endpoint_id"682c6334-ee4e-44f9-80d3-481aa5fd22b6"
is_byokfalse
latency344
model_permaslug"deepseek/deepseek-v4-flash-20260731"
provider_name"Ambient"
status504
1
endpoint_id"f954a48e-1c90-433b-9348-4720f8030331"
is_byokfalse
latency196
model_permaslug"deepseek/deepseek-v4-flash-20260731"
provider_name"OpenInference"
status429
2
endpoint_id"89e67dfe-8499-4a5c-a1eb-2baf0e8d63ee"
id"chatcmpl-c29b48fac16f0d652abf93d075ffebc0"
is_byokfalse
latency207
model_permaslug"deepseek/deepseek-v4-flash-20260731"
provider_name"Inceptron"
status200
total_cost0.00053247
cache_discount(null)
upstream_inference_cost0
provider_name"Inceptron"
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
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences2
tagDensity0.5
leniency1
rawRatio0
effectiveRatio0
94.99% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount998
totalAiIsmAdverbs1
found
0
adverb"gently"
count1
highlights
0"gently"
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)
69.94% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount998
totalAiIsms6
found
0
word"predator"
count1
1
word"shattered"
count1
2
word"footsteps"
count2
3
word"echoed"
count1
4
word"weight"
count1
highlights
0"predator"
1"shattered"
2"footsteps"
3"echoed"
4"weight"
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
narrationSentences81
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences81
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences82
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen31
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords992
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
99.03% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions15
wordCount981
uniqueNames5
maxNameDensity1.02
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn10
Victorian1
Tube2
Morris1
persons
0"Harlow"
1"Quinn"
2"Morris"
places(empty)
globalScore0.99
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
totalMatches0
per1kWords0
wordCount992
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences82
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs26
mean38.15
std21.27
cv0.557
sampleLengths
075
150
265
329
451
540
624
74
848
938
1010
1147
123
1368
1448
1534
1641
1717
1839
1920
2039
2151
2280
237
2454
2510
92.27% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences81
matches
0"been locked"
1"was sworn"
2"been called"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs166
matches
0"was already moving"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount6
semicolonCount1
flaggedSentences6
totalSentences82
ratio0.073
matches
0"She'd shed her coat three blocks back—too heavy, too much drag—and now her shirt clung to her skin like a second layer of cold."
1"Military precision had its uses; it taught you to ignore the body when the body wanted to quit."
2"The runner cut left, through a doorway she hadn't noticed—an old service entrance, its paint peeling in long curls like dead skin."
3"The air changed—cooler, stale, carrying a faint metallic tang she couldn't place."
4"There was light ahead—dim, greenish, flickering like gas flames."
5"DS Morris, the way he'd looked in the split second before the case went bad—eyes wide, mouth open, a question that never quite became a word."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount990
adjectiveStacks0
stackExamples(empty)
adverbCount28
adverbRatio0.028282828282828285
lyAdverbCount2
lyAdverbRatio0.00202020202020202
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences82
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences82
mean12.1
std7.5
cv0.62
sampleLengths
028
123
224
38
423
519
64
721
822
918
108
114
122
131
1414
1522
1611
1710
188
197
2018
2115
2215
239
244
253
2623
276
2812
292
302
3110
3219
339
345
351
364
3710
3814
399
4014
413
4222
4325
4421
4510
4621
4717
483
493
67.07% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.43902439024390244
totalSentences82
uniqueOpeners36
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences75
matches
0"Just black, swallowing the shape"
1"A lot of them."
2"Just stood there, watching, a"
ratio0.04
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount19
totalSentences75
matches
0"She'd shed her coat three"
1"He knew these streets."
2"He vaulted a low railing,"
3"She could hear his breath"
4"She pulled her torch from"
5"Her voice came out hard"
6"She went down."
7"They stood ajar, chains hanging"
8"Her heart hammered against her"
9"It leaked through cracks in"
10"She edged closer."
11"She'd heard rumours."
12"They exchanged words, then the"
13"He couldn't have seen her."
14"Her hand went to the"
15"She had options."
16"Her partner's face surfaced."
17"She didn't break stride."
18"She followed the corridor, and"
ratio0.253
66.67% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount59
totalSentences75
matches
0"The rain came down in"
1"Detective Harlow Quinn's boots slapped"
2"She'd shed her coat three"
3"The figure ahead moved with"
4"He knew these streets."
5"Quinn's lungs burned but she"
6"Military precision had its uses;"
7"He vaulted a low railing,"
8"Quinn closed the gap."
9"She could hear his breath"
10"The runner cut left, through"
11"Quinn skidded on the wet"
12"The corridor beyond sloped downward"
13"She pulled her torch from"
14"The beam cut a weak"
15"The sound of his footsteps"
16"Her voice came out hard"
17"The footsteps didn't stop."
18"She went down."
19"The stairs were narrow, worn"
ratio0.787
66.67% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences75
matches
0"Even at this distance, even"
ratio0.013
66.87% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences47
technicalSentenceCount5
matches
0"The rain came down in sheets, hammering the pavement so hard it bounced back up in a fine mist that clung to the sodium glow of the streetlamps."
1"Kept to the narrow passages, the cut-throughs that smelled of rot and urine, the places where the CCTV had blind spots."
2"The runner had disappeared into a warren of stalls and temporary structures that filled what must have been an abandoned Tube station."
3"The green light came from lanterns, wrought iron and filigree, swinging gently in a breeze that had no business existing underground."
4"A child sat cross-legged beside a cage of small, winged things that clicked their beaks like castanets."
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
90.7835%