Run: 2026-02-20-01KHXQHEY5W16GZ3HVCBFCGX6D

Run Details

Duration:
18.8s
Cost:
$0.001826
Provider:
Mistral

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 came down in sheets, turning the London streets into a slick, shimmering maze of neon and shadow. Detective Harlow Quinn moved with the precision of a woman who had spent half her life chasing ghosts through worse weather. Her boots splashed through puddles that reflected the flickering glow of streetlamps, her breath coming in sharp, controlled bursts. The suspect—Tomás Herrera—was fast, but Quinn was relentless. She had spotted him slipping out of *The Raven’s Nest* like a man who knew he was being watched. The green neon sign above the bar had buzzed and sputtered as he vanished into the alley, his dark curls plastered to his forehead, the Saint Christopher medallion glinting at his throat. Quinn had given chase without hesitation, her leather watch creaking against her wrist as she pumped her arms, her sharp jaw set. Herrera was no ordinary suspect. He was connected—too connected. The clique he ran with, the ones who moved through the city’s underbelly like smoke, they weren’t just criminals. They were something else. Something *worse*. And Quinn had spent three years trying to prove it, ever since Morris had died in that alley, his body found with wounds no knife could explain. The chase led them deeper into Camden, the streets narrowing, the crowds thinning. Herrera ducked into a side street, his boots skidding on the wet pavement as he cut left. Quinn followed, her pulse hammering in her throat. She wasn’t losing him. Not tonight. Then he vanished. One second, he was there—a flash of olive skin, a glimpse of the scar on his forearm—and the next, he was gone. Quinn skidded to a halt, her breath ragged, her eyes scanning the alley. A rusted metal door stood slightly ajar, its hinges groaning in the wind. She pushed it open, the scent of damp earth and something older, something *wrong*, hitting her like a fist. Stairs. Narrow, spiraling down into darkness. Quinn hesitated. She was armed, but this wasn’t a part of the city she knew. This wasn’t *her* territory. But Herrera was down there. And if he was running, it meant he had something to hide. She descended. The air grew thicker, warmer, laced with the scent of burning herbs and something metallic. The walls were lined with strange symbols, glowing faintly in the dim light. Quinn’s fingers brushed the cold stone as she moved, her instincts screaming at her to turn back. But she didn’t. The stairs opened into a cavernous space, the ceiling lost in shadow. Stalls lined the walls, their wares hidden beneath tattered cloths. A low hum of voices filled the air, the murmur of deals being struck in hushed tones. The *Veil Market*. Quinn’s stomach twisted. She had heard whispers of this place—Morris had, too, before he died. A black market for things that shouldn’t exist. Things that *moved* on their own. Things that *watched* you back. Herrera was ahead, weaving through the crowd, his head down. Quinn followed, her shoulders tense, her hand resting on the grip of her sidearm. The market was a labyrinth of shadows and secrets, the air thick with the scent of old magic and older sins. A woman with too many teeth offered her a vial of swirling liquid. A man with hollow eyes tried to sell her a knife that hummed when she touched it. She ignored them all, her focus locked on Herrera. He turned a corner, disappearing behind a stall selling what looked like jars of *teeth*. Quinn quickened her pace, shoving past a group of cloaked figures. She rounded the corner— And found herself face to face with a wall of muscle and menace. A man—if he could be called that—blocked her path. His skin was the color of old parchment, his eyes black pits. He smiled, revealing rows of needle-thin teeth. "Bone token," he rasped. Quinn’s hand twitched toward her gun. "I don’t have one." The man’s smile widened. "Then you don’t belong." Behind him, Herrera glanced back, his warm brown eyes locking onto hers. For a second, something flickered in his gaze—fear, maybe. Or guilt. Then he turned and melted into the crowd. Quinn made her choice. She lunged.
created_at"2026-02-20T14:33:55.92Z" 2/20/2026, 2:33:55 PM
model"mistralai/mistral-large-2512" 1/1/2512, 12:00:00 AM
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency420
moderation_latency(null)
generation_time18683
tokens_prompt914
tokens_completion1071
native_tokens_prompt840
native_tokens_completion937
native_tokens_completion_images(null)
native_tokens_reasoning0
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"
usage0.0018255
router(null)
provider_responses
0
endpoint_id"fa718841-07ea-4b7e-b8a3-6069545c7e6a"
id"53a37e01d8a64749a9dc605bb35f44d6"
is_byokfalse
latency420
model_permaslug"mistralai/mistral-large-2512" 1/1/2512, 12:00:00 AM
provider_name"Mistral"
status200
api_type"completions"
id"gen-1771598035-eSk0ZAa9nDGRzAtoInlA"
upstream_id"53a37e01d8a64749a9dc605bb35f44d6"
total_cost0.0018255
cache_discount(null)
upstream_inference_cost0
provider_name"Mistral"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences3
tagDensity0.333
leniency0.667
rawRatio0
effectiveRatio0
92.93% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount707
totalAiIsmAdverbs1
found
0
adverb"slightly"
count1
highlights
0"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)
57.57% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount707
totalAiIsms6
found
0
word"glinting"
count1
1
word"pulse"
count1
2
word"scanning"
count1
3
word"stomach"
count1
4
word"quickened"
count1
5
word"flickered"
count1
highlights
0"glinting"
1"pulse"
2"scanning"
3"stomach"
4"quickened"
5"flickered"
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
narrationSentences66
matches(empty)
99.57% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences66
filterMatches
0"watch"
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences68
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen32
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans8
markdownWords11
totalWords697
ratio0.016
matches
0"The Raven’s Nest"
1"worse"
2"wrong"
3"her"
4"Veil Market"
5"moved"
6"watched"
7"teeth"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
55.39% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions29
wordCount687
uniqueNames10
maxNameDensity1.89
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
London1
Harlow1
Quinn13
Tomás1
Herrera7
Raven1
Saint1
Christopher1
Morris2
Camden1
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Raven"
5"Saint"
6"Christopher"
7"Morris"
places
0"London"
1"Camden"
globalScore0.554
windowScore1
91.86% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences43
glossingSentenceCount1
matches
0"looked like jars of *teeth*"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount697
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences68
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs23
mean30.3
std24.79
cv0.818
sampleLengths
067
173
261
344
43
567
66
736
82
948
1042
1134
1275
139
1430
1513
1628
174
1810
198
2031
214
222
84.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences66
matches
0"was connected"
1"was gone"
2"were lined"
3"being struck"
38.71% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs124
matches
0"was being"
1"wasn’t losing"
2"was running"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount10
semicolonCount0
flaggedSentences7
totalSentences68
ratio0.103
matches
0"The suspect—Tomás Herrera—was fast, but Quinn was relentless."
1"He was connected—too connected."
2"One second, he was there—a flash of olive skin, a glimpse of the scar on his forearm—and the next, he was gone."
3"She had heard whispers of this place—Morris had, too, before he died."
4"She rounded the corner—"
5"A man—if he could be called that—blocked her path."
6"For a second, something flickered in his gaze—fear, maybe."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount697
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.020086083213773313
lyAdverbCount3
lyAdverbRatio0.00430416068866571
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences68
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences68
mean10.25
std6.89
cv0.672
sampleLengths
019
121
219
38
419
532
622
75
84
919
104
112
1227
1313
1417
158
164
172
183
1922
2013
2113
2219
231
245
252
2613
274
285
2912
302
3115
3213
3317
343
3512
3610
3717
383
393
4012
418
426
435
4410
4514
4621
4713
4817
499
59.31% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.38235294117647056
totalSentences68
uniqueOpeners26
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences58
matches
0"Then he vanished."
1"Then he turned and melted"
ratio0.034
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount13
totalSentences58
matches
0"Her boots splashed through puddles"
1"She had spotted him slipping"
2"He was connected—too connected."
3"They were something else."
4"She wasn’t losing him."
5"She pushed it open, the"
6"She was armed, but this"
7"She had heard whispers of"
8"She ignored them all, her"
9"He turned a corner, disappearing"
10"She rounded the corner—"
11"His skin was the color"
12"He smiled, revealing rows of"
ratio0.224
46.21% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount48
totalSentences58
matches
0"The rain came down in"
1"Detective Harlow Quinn moved with"
2"Her boots splashed through puddles"
3"The suspect—Tomás Herrera—was fast, but"
4"She had spotted him slipping"
5"The green neon sign above"
6"Quinn had given chase without"
7"Herrera was no ordinary suspect."
8"He was connected—too connected."
9"The clique he ran with,"
10"They were something else."
11"The chase led them deeper"
12"Herrera ducked into a side"
13"Quinn followed, her pulse hammering"
14"She wasn’t losing him."
15"One second, he was there—a"
16"Quinn skidded to a halt,"
17"A rusted metal door stood"
18"She pushed it open, the"
19"She was armed, but this"
ratio0.828
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences58
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences36
technicalSentenceCount2
matches
0"Detective Harlow Quinn moved with the precision of a woman who had spent half her life chasing ghosts through worse weather."
1"Her boots splashed through puddles that reflected the flickering glow of streetlamps, her breath coming in sharp, controlled bursts."
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
84.1846%