Run: 2026-03-25-01KMJ7WC98FQANFJFSK6XCYJ96

Run Details

Duration:
1m 36s
Cost:
$0.001323
Provider:
Novita

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 swatted Harlow Quinn's collar as she turned the corner, her worn boots skidding against wet cobblestone. The neon glare from *The Raven’s Nest* cast jagged shadows, but the hooded figure slipping around the bar’s back entrance couldn't hide. Five nights on the manhunt hollowed her ribs into stone, the unsolved case of DS Morris gnawing at her every breath. She recognized the gait now—short, stiff, calculated. Tommy Herrera balanced on the edge of the alley like a thief weighing a ledger, not the danger of running from a decorated MPD detective who’d once given him a second chances. She’d reissued his paramedic license, long after the sting winding in his left arm exposed the truth. "You’re coughing up blood again," Quinn growled, reaching for her baton. Her left wrist throbbed, where the watch rope bitten into her pulse. "That's not your NHS special this time—is it?" Tommy spun, his olive skin glistening, and Quinn caught the flash of a silver medallion as he dodged. The damn Saint Christopher relic hung loose enough to bounce. It had been around Herrera’s neck since he lost his license trying to stitch a werewolf’s spleen back on. "This don’t concern you, Quinn," he muttered, already dashing down the alley. Mud splattered her hands when she grabbed his ankle—teeth bared, she wrenched him down into the slush. "Your badge done lost relevance with the rest of the *mundo sin ti*." His laughter was sharp as a blade. "Why you still carrying it like a crutch?" She said nothing, just flipped his coat inside out while the rain stitched her trench coat to her chest. The pocket yielded a bone token, pitted and dark. Quinn squinted at it, already processing. Abandoned Tube stations under Camden housed the *Veil Market* now—bonetokens were the price of admission. Herrera’s trail was cooling fast. She wrenched his arm, ignoring the scar straining under the pressure. "Who’s bleeding you for antiseptics? Of cures doesn’t work on the things you’re treating." He spat a mouthful of mud and blood at her boots. "You think you special? You lost someone. Everyone here lost someone. Half the City’s rotting—why you got the monopoly on pain?" Quinn shoved off, her fingers brushing the token. Herrera vanished into the downpour, a ripple in the doorway of the Tube stairs. Above, the green *Raven’s Nest* sign flickered out, plunging the alley into black. Quinn stared at the token. Herrera’s right—this part of London wasn’t coded into her evidence logs. But DS Morris’ report still haunted her desk drawer, filled with hollunders and unpronounceable streets. The Tube corridor stank of rust and mildew, the stone steps slick. Quinn’s baton hummed at her thigh as she descended. Herrera’s footprints gliowed faintly on the wall, smudged with alchemical ash. A tapestry near the tracks shifted suddenly—concealed doors. She pried the bookshelf loose, revealing the market’s entrance. Herrera was waiting, already gripping a tattered map. Quinn’s gun dug into his throat before he could turn. "You’re on my block, Tommy. Let’s talk." He arched an eyebrow, but the fear in his soft brown eyes was real. "Talk’s why Morris ended up drowned in his own blood. You sure about this side of the tracks?" The Tube station opened into a cavern of shadows. Stalls folded into each other, their wares glowing faintly: eyes in amber vials, a shopkeeper’s grin of molten silver. Herrera’s token slipped past her fingers into a vendor’s hand before she could stop it. The merchant, a pale woman with a raven’s-feather comb in her hair, waved them through with a grin. Quinn’s heel caught on a loose grating. Herrera leaned close, voice a whisper as footsteps echoed. "You gonna need a new partner down here, Quinn." The token was burning hot now, the air thick with ozone. Herrera vanished into the crowd, but Quinn’s hand clamped his arm again, forcing him behind a silk-draped table of surgical tools. Her fingers brushed his wound—circular scars where wellhead fluid had erupted through his skin. The same tecnique a Necromancer had used on Morris. Herrera snatched his arm back, breath fast. "You always overstock suture kits? Or you dealing like the rest of them?" "Alphabet soup police can’t read. You want to stop the bleeding, we went to the source." He licked his lips, revealing the Salesforce of a man who’d made peace with the dark. "There’s a counter in the next aisle. The apothecary has unlimited referrals." Quinn’s side ached, but Herrera was already tugging her deeper. The market’s hum thickened—a low vibrate course through her bones. She spotted the medical counter first: bottles of black liquid clinking like abdominal alcohol, and paths of veins shelved by zip code. Herrera elbowed her to the side as he pulled out a vial, but Quinn caught the look. He was baiting her, walking backward toward an exit while haggling language phrases off his hand. Her stare cut through him. "You think I afraid of it? Of what’s really going on?" Herrera paused, and for a second, the old man’s face sagged. “You suppose you well-armed, Quinn. But you don’t see the girls scabinating after their operations. Or the guys with holes in their hands who can't stop bleeding till morning.” His whisper almost drowned in the clamor of the dancers and rustling shadows. “You chasing a ghost in a warehouse of teeth and daggers.” Quinn glared, the token now cold. Herrera made his move—a push into the crowd, but her baton caught his shoulder, the hooked end embedding in his coat. She wrenched him sideways into a postero market aisle, where a mirror frame section caught the light just enough to show his twin piques of defiance. “This doesn’t need to be a spree,” she muttered. “You could’ve kepme in the loop three years ago.” He bit the inside of his cheek, nodding slightly. “You think you found something once, don’t you.” His grip tightened on her wrist, a final, intransient cough of blood. "But the status wirks on both sides." Tomás Herrera vanished—Quinn watched he slipped into a crowd, the silver medallion catching light. The index card jingled from her hand. Rain pattered up, echoing, but the tunnel beyond was dry. No sobbing, just the scent of Lycopodium and the promise of a cleaner crime scene. Quinn slipped into the tunnel, her hand gripping the token. The mouth of the next entrance creaked open behind a lifeless leaf wall. The step past it ornate, with its own sign flickering at Madame Zeeba’s stall. A closer look at Herrera’s dossier whispered warnings, but the DI’s badge in her palm felt like chains. Quinn took one step forward through the eerie threshold.
created_at"2026-03-25T10:15:43.148Z" 3/25/2026, 10:15:43 AM
model"qwen/qwen3-32b-04-28"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency629
moderation_latency(null)
generation_time96429
tokens_prompt1164
tokens_completion3189
native_tokens_prompt1008
native_tokens_completion2715
native_tokens_completion_images(null)
native_tokens_reasoning1440
native_tokens_cached0
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"
usage0.00132255
router(null)
provider_responses
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endpoint_id"d342f1c5-34b5-4a5c-b2ea-a0cdcbf72e70"
id"387f658d-51d2-4a5c-a4d1-ab1b301357df"
is_byokfalse
latency628
model_permaslug"qwen/qwen3-32b-04-28"
provider_name"Novita"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer(null)
api_type"completions"
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upstream_id"387f658d-51d2-4a5c-a4d1-ab1b301357df"
total_cost0.00132255
cache_discount(null)
upstream_inference_cost0
provider_name"Novita"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags5
adverbTagCount0
adverbTags(empty)
dialogueSentences20
tagDensity0.25
leniency0.5
rawRatio0
effectiveRatio0
86.63% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1122
totalAiIsmAdverbs3
found
0
adverb"suddenly"
count1
1
adverb"really"
count1
2
adverb"slightly"
count1
highlights
0"suddenly"
1"really"
2"slightly"
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)
37.61% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1122
totalAiIsms14
found
0
word"calculated"
count1
1
word"throbbed"
count1
2
word"pulse"
count1
3
word"glistening"
count1
4
word"flickered"
count1
5
word"coded"
count1
6
word"tapestry"
count1
7
word"eyebrow"
count1
8
word"whisper"
count2
9
word"footsteps"
count1
10
word"echoed"
count1
11
word"silk"
count1
12
word"echoing"
count1
highlights
0"calculated"
1"throbbed"
2"pulse"
3"glistening"
4"flickered"
5"coded"
6"tapestry"
7"eyebrow"
8"whisper"
9"footsteps"
10"echoed"
11"silk"
12"echoing"
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
narrationSentences70
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences70
filterMatches(empty)
hedgeMatches(empty)
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
maxSentenceWordsSeen43
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans4
markdownWords10
totalWords1111
ratio0.009
matches
0"The Raven’s Nest"
1"mundo sin ti"
2"Veil Market"
3"Raven’s Nest"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions53
wordCount867
uniqueNames17
maxNameDensity1.96
worstName"Herrera"
maxWindowNameDensity3.5
worstWindowName"Herrera"
discoveredNames
Harlow1
Quinn16
Raven2
Morris2
Herrera17
Saint1
Christopher1
Mud1
Tube4
Camden1
London1
Necromancer1
Salesforce1
Tomás1
Lycopodium1
Madame1
Zeeba1
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Morris"
4"Herrera"
5"Saint"
6"Christopher"
7"Mud"
8"Camden"
9"Necromancer"
10"Tomás"
11"Zeeba"
places
0"London"
1"Madame"
globalScore0.52
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences65
glossingSentenceCount1
matches
0"felt like chains"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1111
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences83
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs24
mean46.29
std26.31
cv0.568
sampleLengths
0116
131
247
357
465
514
632
766
867
97
1032
1177
129
1362
1413
1544
1675
1716
1864
1953
2018
2136
2269
2341
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences70
matches(empty)
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs143
matches
0"was cooling"
1"was waiting"
2"was burning"
3"was already tugging"
4"was baiting"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount9
semicolonCount0
flaggedSentences9
totalSentences83
ratio0.108
matches
0"She recognized the gait now—short, stiff, calculated."
1"Mud splattered her hands when she grabbed his ankle—teeth bared, she wrenched him down into the slush."
2"Abandoned Tube stations under Camden housed the *Veil Market* now—bonetokens were the price of admission."
3"Herrera’s right—this part of London wasn’t coded into her evidence logs."
4"A tapestry near the tracks shifted suddenly—concealed doors."
5"Her fingers brushed his wound—circular scars where wellhead fluid had erupted through his skin."
6"The market’s hum thickened—a low vibrate course through her bones."
7"Herrera made his move—a push into the crowd, but her baton caught his shoulder, the hooked end embedding in his coat."
8"Tomás Herrera vanished—Quinn watched he slipped into a crowd, the silver medallion catching light."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount477
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.029350104821802937
lyAdverbCount1
lyAdverbRatio0.0020964360587002098
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
mean13.39
std6.44
cv0.481
sampleLengths
017
122
221
37
432
517
611
712
88
918
1010
1119
1212
1317
1420
158
1619
179
186
1915
205
2111
2214
2311
2421
258
2614
2713
285
2911
3015
3112
329
3311
348
359
368
3710
387
3914
4018
419
4219
4315
4418
457
469
479
4811
4921
51.81% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.3253012048192771
totalSentences83
uniqueOpeners27
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences68
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount20
totalSentences68
matches
0"She recognized the gait now—short,"
1"She’d reissued his paramedic license,"
2"Her left wrist throbbed, where"
3"It had been around Herrera’s"
4"he muttered, already dashing down"
5"His laughter was sharp as"
6"She said nothing, just flipped"
7"She wrenched his arm, ignoring"
8"He spat a mouthful of"
9"She pried the bookshelf loose,"
10"He arched an eyebrow, but"
11"Her fingers brushed his wound—circular"
12"He licked his lips, revealing"
13"She spotted the medical counter"
14"He was baiting her, walking"
15"Her stare cut through him."
16"His whisper almost drowned in"
17"She wrenched him sideways into"
18"He bit the inside of"
19"His grip tightened on her"
ratio0.294
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount64
totalSentences68
matches
0"Rain swatted Harlow Quinn's collar"
1"The neon glare from *The"
2"She recognized the gait now—short,"
3"Tommy Herrera balanced on the"
4"She’d reissued his paramedic license,"
5"Quinn growled, reaching for her"
6"Her left wrist throbbed, where"
7"Tommy spun, his olive skin"
8"The damn Saint Christopher relic"
9"It had been around Herrera’s"
10"he muttered, already dashing down"
11"Mud splattered her hands when"
12"His laughter was sharp as"
13"She said nothing, just flipped"
14"The pocket yielded a bone"
15"Quinn squinted at it, already"
16"Herrera’s trail was cooling fast."
17"She wrenched his arm, ignoring"
18"He spat a mouthful of"
19"Quinn shoved off, her fingers"
ratio0.941
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences68
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences42
technicalSentenceCount2
matches
0"Tommy Herrera balanced on the edge of the alley like a thief weighing a ledger, not the danger of running from a decorated MPD detective who’d once given him a …"
1"She wrenched his arm, ignoring the scar straining under the pressure."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags5
uselessAdditionCount0
matches(empty)
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount3
fancyTags
0"Quinn growled (growl)"
1"he muttered (mutter)"
2"she muttered (mutter)"
dialogueSentences20
tagDensity0.15
leniency0.3
rawRatio1
effectiveRatio0.3
74.2017%