Run: 2026-02-20-01KHXPVRND7Y377CXGQ3Y2TAWF

Run Details

Duration:
25.9s
Cost:
$0.002353
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="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <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> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. 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 abandoned Tube station smelled of damp concrete and rust, the kind of scent that clung to the back of your throat like a bad memory. Detective Harlow Quinn stepped over the police tape, her boots scuffing against the cracked tiles of what had once been Camden Town station. The overhead lights flickered, casting long shadows that stretched like grasping fingers across the graffiti-scarred walls. Her leather watch creaked as she adjusted it, the worn strap familiar against her wrist. "Quinn." The voice came from the platform below, where a cluster of uniforms milled about like lost sheep. Detective Sergeant Cole stood near the body, his hands shoved deep in his pockets, his expression grim. "Took you long enough." She ignored the jab. "What've we got?" Cole jerked his chin toward the far end of the platform, where a sheet-covered figure lay sprawled across the tracks. "Male, mid-thirties. No ID. Looks like he took a header onto the rails, but—" He hesitated, rubbing the back of his neck. "There's something off about it." Quinn crouched beside the body, her sharp jaw tightening as she lifted the sheet. The victim's face was frozen in a rictus of terror, his eyes wide and unblinking, mouth stretched in a silent scream. His clothes were expensive—tailored wool coat, Italian leather shoes—but his hands were raw, knuckles split like he'd been clawing at something. Or someone. "Defensive wounds?" Cole offered. "Maybe." Quinn ran her fingers along the man's sleeve, pausing at the cuff. A fine layer of dust clung to the fabric, glittering faintly under the harsh station lights. She rubbed it between her fingers. Not dust. Ash. "You check the pockets?" "Empty. No wallet, no phone, nothing." She stood, scanning the platform. The usual detritus of a Tube station was absent—no discarded tickets, no chewing gum stains, no lost gloves. Just more of that ash, scattered in a thin trail leading toward the tunnel mouth. "Where's the CCTV?" Cole snorted. "You're joking, right? This place has been shut down since the '90s. No cameras, no power, nothing." Quinn exhaled through her nose. That was the problem with these old stations. Too many blind spots. Too many ways for things to slip through the cracks. She stepped closer to the tunnel, her pulse kicking up a notch as she caught the faintest whisper of something—like wind through a crack in a window. But the air was still. Dead still. "Quinn." Cole's voice was low, urgent. "You're not buying this suicide angle, are you?" She didn't answer. Instead, she reached into her coat pocket and pulled out a small brass compass, its casing etched with strange, looping sigils. The needle trembled, then swung violently toward the tunnel. Cole's eyes narrowed. "What the hell is that?" "Nothing." She snapped the compass shut and tucked it away. "Just a hunch." Cole stepped closer, his voice dropping to a whisper. "You think this is connected to the Morris case." It wasn't a question. Quinn's fingers twitched at her side. Three years. Three years since DS Morris had walked into a similar abandoned station and never walked out. The official report called it a gas leak. A tragic accident. But Quinn had seen the body. Had seen the way his skin had been stretched too tight over his bones, like something had been *sucked* out of him. She forced herself to focus. "We need to canvass the area. Someone had to have seen something." Cole shook his head. "Already did. No one saw a damn thing. It's like this guy just materialized out of thin air." Quinn's gaze flicked back to the tunnel. The ash. The compass. The way the victim's fingers looked like he'd been *digging* at something. She thought of the stories Morris used to tell her—whispers of a black market hidden beneath the city, a place where things that weren't quite human traded in things that weren't quite legal. She thought of the bone token in her pocket. "Quinn." Cole's voice was sharp now. "You're not seriously considering—" She cut him off with a look. "I'm considering the facts. And the facts don't add up." She turned back to the body, her mind racing. The ash. The lack of ID. The way the victim's terror didn't match the scene. Suicides didn't claw at the air like they were trying to escape something. They didn't leave trails of glittering dust behind. She crouched again, this time pulling a pair of latex gloves from her pocket. The victim's coat was torn at the shoulder, the fabric frayed like it had been caught on something. She peeled it back, revealing a small, circular burn mark on the skin beneath. Not a burn. A brand. A sigil, its edges too precise to be accidental. Cole leaned in. "What the hell is that?" Quinn's stomach twisted. She'd seen that symbol before. In Morris's notes. In the margins of a case file he'd been obsessed with before he died. A case involving a missing researcher from the British Museum. A case that had led him straight to the Veil Market. She stood abruptly, her military precision snapping back into place. "We're done here. Get the body to the morgue. I want a full tox screen, and I want that symbol run through every database we've got." Cole frowned. "You're not coming?" "Not yet." She was already moving toward the tunnel, her boots echoing against the concrete. "I've got a lead to follow." Cole grabbed her arm. "Quinn, whatever you're thinking—don't. Morris went down this road. Look where it got him." She met his gaze, her expression unreadable. "I know." And she did. She knew exactly where this road led. But she was going anyway.
created_at"2026-02-20T14:22:04.984Z" 2/20/2026, 2:22:04 PM
model"mistralai/mistral-large-2512" 1/1/2512, 12:00:00 AM
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency475
moderation_latency(null)
generation_time25816
tokens_prompt923
tokens_completion1448
native_tokens_prompt875
native_tokens_completion1277
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"
usage0.002353
router(null)
provider_responses
0
endpoint_id"fa718841-07ea-4b7e-b8a3-6069545c7e6a"
id"5e84e4be36e64a55a56a03c93d6524c3"
is_byokfalse
latency475
model_permaslug"mistralai/mistral-large-2512" 1/1/2512, 12:00:00 AM
provider_name"Mistral"
status200
api_type"completions"
id"gen-1771597324-T2V4gSkbdfm0IH6n1gFv"
upstream_id"5e84e4be36e64a55a56a03c93d6524c3"
total_cost0.002353
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
totalTags7
adverbTagCount1
adverbTags
0"She turned back [back]"
dialogueSentences29
tagDensity0.241
leniency0.483
rawRatio0.143
effectiveRatio0.069
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount959
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)
27.01% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount959
totalAiIsms14
found
0
word"flickered"
count1
1
word"familiar"
count1
2
word"scanning"
count1
3
word"pulse"
count1
4
word"whisper"
count2
5
word"etched"
count1
6
word"trembled"
count1
7
word"flicked"
count1
8
word"racing"
count1
9
word"stomach"
count1
10
word"database"
count1
11
word"echoing"
count1
12
word"unreadable"
count1
highlights
0"flickered"
1"familiar"
2"scanning"
3"pulse"
4"whisper"
5"etched"
6"trembled"
7"flicked"
8"racing"
9"stomach"
10"database"
11"echoing"
12"unreadable"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences82
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences82
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences102
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen34
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords2
totalWords951
ratio0.002
matches
0"sucked"
1"digging"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
71.16% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions36
wordCount761
uniqueNames14
maxNameDensity1.58
worstName"Cole"
maxWindowNameDensity2.5
worstWindowName"Cole"
discoveredNames
Tube2
Harlow1
Quinn8
Camden1
Town1
Detective2
Sergeant1
Cole12
Italian1
Morris3
British1
Museum1
Veil1
Market1
persons
0"Harlow"
1"Quinn"
2"Sergeant"
3"Cole"
4"Morris"
5"Market"
places
0"Camden"
1"Town"
2"British"
3"Veil"
globalScore0.712
windowScore0.833
45.83% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences48
glossingSentenceCount2
matches
0"looked like he'd been *digging* at someth"
1"quite human traded in things that weren't quite legal"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount951
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences102
matches
0"seen that symbol"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs34
mean27.97
std21.75
cv0.778
sampleLengths
080
139
27
347
458
54
642
76
841
919
1061
1114
1233
138
1413
1518
1667
1717
1822
1956
209
2110
2262
2360
248
2535
2611
2736
285
2921
3018
319
3210
335
88.15% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences82
matches
0"was frozen"
1"been stretched"
2"been *sucked"
3"was torn"
4"been caught"
5"been obsessed"
93.33% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs125
matches
0"were trying"
1"was going"
30.81% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount5
semicolonCount0
flaggedSentences4
totalSentences102
ratio0.039
matches
0"His clothes were expensive—tailored wool coat, Italian leather shoes—but his hands were raw, knuckles split like he'd been clawing at something."
1"The usual detritus of a Tube station was absent—no discarded tickets, no chewing gum stains, no lost gloves."
2"She stepped closer to the tunnel, her pulse kicking up a notch as she caught the faintest whisper of something—like wind through a crack in a window."
3"She thought of the stories Morris used to tell her—whispers of a black market hidden beneath the city, a place where things that weren't quite human traded in things that weren't quite legal."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount767
adjectiveStacks0
stackExamples(empty)
adverbCount27
adverbRatio0.035202086049543675
lyAdverbCount4
lyAdverbRatio0.005215123859191656
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences102
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences102
mean9.32
std7.04
cv0.755
sampleLengths
026
123
216
315
418
517
64
74
83
920
1022
115
1214
1321
1421
152
164
1713
1816
196
202
211
224
236
245
2518
2615
273
282
2917
305
318
324
3310
3427
355
362
376
388
393
4021
419
423
435
4410
453
469
479
484
496
50.65% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.3627450980392157
totalSentences102
uniqueOpeners37
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount4
totalSentences70
matches
0"Just more of that ash,"
1"Too many blind spots."
2"Too many ways for things"
3"Instead, she reached into her"
ratio0.057
88.57% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount23
totalSentences70
matches
0"Her leather watch creaked as"
1"She ignored the jab."
2"He hesitated, rubbing the back"
3"His clothes were expensive—tailored wool"
4"She rubbed it between her"
5"She stood, scanning the platform."
6"She stepped closer to the"
7"She didn't answer."
8"She snapped the compass shut"
9"It wasn't a question."
10"She forced herself to focus."
11"She thought of the stories"
12"She thought of the bone"
13"She cut him off with"
14"She turned back to the"
15"They didn't leave trails of"
16"She crouched again, this time"
17"She peeled it back, revealing"
18"She'd seen that symbol before."
19"She stood abruptly, her military"
ratio0.329
52.86% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount57
totalSentences70
matches
0"The abandoned Tube station smelled"
1"Detective Harlow Quinn stepped over"
2"The overhead lights flickered, casting"
3"Her leather watch creaked as"
4"The voice came from the"
5"Detective Sergeant Cole stood near"
6"She ignored the jab."
7"Cole jerked his chin toward"
8"He hesitated, rubbing the back"
9"Quinn crouched beside the body,"
10"The victim's face was frozen"
11"His clothes were expensive—tailored wool"
12"Quinn ran her fingers along"
13"A fine layer of dust"
14"She rubbed it between her"
15"She stood, scanning the platform."
16"The usual detritus of a"
17"Quinn exhaled through her nose."
18"That was the problem with"
19"She stepped closer to the"
ratio0.814
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences70
matches(empty)
ratio0
89.95% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences27
technicalSentenceCount2
matches
0"The abandoned Tube station smelled of damp concrete and rust, the kind of scent that clung to the back of your throat like a bad memory."
1"The overhead lights flickered, casting long shadows that stretched like grasping fingers across the graffiti-scarred walls."
53.57% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount1
matches
0"She turned back, her mind racing"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount1
fancyTags
0"She snapped (snap)"
dialogueSentences29
tagDensity0.034
leniency0.069
rawRatio1
effectiveRatio0.069
83.0630%