Run: 2026-03-18-01KM095YC6Q8GS087SRFZV1N3Y

Run Details

Duration:
15.2s
Cost:
$0.001076
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 Tube station had been sealed for decades, its tiled walls slick with condensation, the original signage half peeling off like dead skin. The air smelled of rust and old damp, the kind of chill that settled into your bones and never left. Detective Harlow Quinn adjusted the cuffs of her dark wool coat as she stepped over a police tape flapping weakly against a rusted stanchion. The scene was bathed in the sickly yellow glow of crime scene lamps, their cables snaking through puddles of water that had pooled on the cracked concrete floor. She hadn’t expected a call like this — not here. Not beneath Camden, where the underground pulsed with something older than the city above. Detective Quinn moved forward, her leather watch glinting under the artificial light. Her boots made little sound on the wet ground. A body lay sprawled near the center of the platform, limbs twisted at unnatural angles, fingers curled into claws. DS Morris’s voice echoed in her memory: “Quinn, you’re jumping at shadows again.” She hated that she heard it now. Three years gone, but still. “Evening, Detective,” a voice said behind her. Quinn didn’t turn. She didn’t need to. The tone was light, almost playful, but she could hear the tension thrumming beneath it. Eva Kowalski stood a few feet away, her round glasses reflecting the lamplight, her curly red hair tucked behind her ears in a nervous motion she’d done since they were teens in Aurora. Only now, Eva wasn’t a schoolgirl — she was a researcher, her satchel bulging with books she’d probably pulled from the British Museum’s restricted archives. “Eva,” Quinn said, voice low. “What the hell are you doing here?” “I got a tip,” Eva said, stepping forward, her satchel swaying. “Something about ‘unusual residue’ near the platform. I thought you’d want to see it.” Quinn frowned. “You didn’t call the station?” “I tried. Your sergeant said you were already on scene.” Eva’s green eyes flickered toward the body. “Is that…?” “Victor Kale,” Quinn said, reading from a case file in her mind. “Missing three days. Local historian. Known folklorist. Found by a homeless man near the old canal lock.” She crouched beside the body, ignoring the way her stomach twisted. No blood. Not on the skin, not on the tiles. Not even in the air — which, given the violence of the death, should have reeked of copper and fear. Quinn reached into her coat pocket and withdrew a pair of nitrile gloves. She snapped them on, the sound sharp in the silence. “Suicide?” Eva asked, though she didn’t sound convinced. “Jumped from the platform?” Quinn muttered. “No defensive wounds. No hesitation marks. But look.” She pointed to the victim’s temple. “There’s a mark — tiny, almost a pinprick. Like something was injected.” Eva leaned in, her breath quickening. “No entry wound I can see. No exit either.” “And no bruising around the mouth,” Quinn said. “No ligature marks. No rope burns. No broken bones from impact — his wrists aren’t fractured, his ribs aren’t shattered. He didn’t fall.” Eva exhaled sharply. “So he was… placed?” Quinn stood slowly, eyes scanning the platform. The platform. Not the tracks. Not the ceiling. The bloodless death. The uncanny stillness. “He wasn’t dropped,” she said. “He was arranged.” Eva’s fingers twitched at her side, the telltale sign she was reciting facts. “According to the coroner’s report on Morris —” Quinn cut her off with a sharp look. “Don’t.” Eva fell silent. Quinn walked the perimeter of the platform, boots splashing in shallow water. The tiles were uneven, some cracked, some loose. At the far end, near an old advertisement for Ovaltine in faded red and yellow, she stopped. There, in the grout between two tiles, was a mark — a symbol scratched into the cement. Not with a knife. Not with a tool. It looked like it had been pressed in with a finger, still damp, faintly glowing a sickly green under the lamplight. Quinn knelt, pulling a small flashlight from her belt. The symbol wasn’t English, wasn’t Latin. It looked like twisted vines forming a sigil — one she’d seen in Eva’s old research notes. “Eva,” she said, voice tight. “What is this?” Eva’s face drained of color. She knelt beside Quinn, adjusting her glasses, then recoiled as if burned. “I don’t know. But it’s not… it’s not from any textbook I’ve read.” “You’ve read it before,” Quinn said. Eva hesitated. Then nodded. “In fragments. In marginalia. It’s a Veil sigil. Used to mark places where the borders between worlds are thin.” Quinn’s pulse quickened. The Veil Market moved beneath London, but only once a month — on the full moon. And only to those who carried a bone token. Or so the legends said. She stood again, scanning the platform. The air hummed. Not with electricity — with something older. Something like anticipation. “Eva,” Quinn said quietly, “how many people know about this station?” Eva bit her lip. “I don’t think anyone above ground even remembers it exists.” Quinn pulled out her phone, dialed a number. After a moment, a gruff voice answered. “Hargrove.” “DI Hargrove? It’s Quinn. I need you to check something.” She gave the address — a disused platform beneath Camden Town. “See if this station has ever been surveilled in the last week. Footage, sensors, anything.” A pause. Then: “You’re not serious.” “I am. And get me access to the restricted archives at the British Museum. Eva Kowalski might be able to help narrow it down.” Hargrove exhaled. “Quinn, this isn’t some ghost hunt.” “I know what I saw,” she said. “And what I didn’t.” She hung up, turning to Eva. “You said you got a tip.” Eva nodded. “A colleague mentioned seeing ‘someone moving through the shadows’ down here. Not a person. Not quite. Said it had no face. Just… darkness wearing a coat.” Quinn’s stomach dropped. A coat. Like the one Kale was wearing — tailored wool, slightly damp, as if he’d walked through fog. Quinn pulled out the Veil Compass from her coat pocket. The brass casing was cold, the verdigris pattern deepening in the dim light. She tapped the face — the needle spun wildly, then steadied, pointing not toward the tracks, not toward the platform’s edge, but toward the center of the platform itself. Where Victor Kale lay. His body twitched. Quinn froze. Eva gasped. Kale’s fingers curled again. His eyes flew open — black. Not pupils. Not irises. Just void. And then he whispered, one word: “Tell.” The lanterns flickered. The platform shuddered. The sigil in the grout burned brighter, green fire licking up the tiles like vines. Quinn’s breath came fast. “Eva, run.” But Eva wasn’t looking at her. She was looking at the shadows. And the shadows were moving toward them.
created_at"2026-03-18T10:52:05.396Z" 3/18/2026, 10:52:05 AM
model"mistralai/mistral-small-2603" 1/1/2603, 12:00:00 AM
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency430
moderation_latency(null)
generation_time15136
tokens_prompt923
tokens_completion1871
native_tokens_prompt887
native_tokens_completion1597
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached112
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"
usage0.00107613
router(null)
provider_responses
0
endpoint_id"f5ed6283-4e17-457d-98cd-2ec0c318171d"
id"ff62a52077164524828686e6e5c5b94a"
is_byokfalse
latency430
model_permaslug"mistralai/mistral-small-2603" 1/1/2603, 12:00:00 AM
provider_name"Mistral"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer(null)
api_type"completions"
id"gen-1773831125-VaCMlhuu9grN7dqt6yto"
upstream_id"ff62a52077164524828686e6e5c5b94a"
total_cost0.00107613
cache_discount0.00001512
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
totalTags17
adverbTagCount1
adverbTags
0"Quinn said quietly [quietly]"
dialogueSentences42
tagDensity0.405
leniency0.81
rawRatio0.059
effectiveRatio0.048
86.64% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1123
totalAiIsmAdverbs3
found
0
adverb"sharply"
count1
1
adverb"slowly"
count1
2
adverb"slightly"
count1
highlights
0"sharply"
1"slowly"
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)
19.86% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1123
totalAiIsms18
found
0
word"chill"
count1
1
word"pulsed"
count1
2
word"glinting"
count1
3
word"echoed"
count1
4
word"tension"
count1
5
word"flickered"
count2
6
word"stomach"
count2
7
word"silence"
count1
8
word"fractured"
count1
9
word"shattered"
count1
10
word"scanning"
count2
11
word"uncanny"
count1
12
word"pulse"
count1
13
word"quickened"
count1
14
word"anticipation"
count1
highlights
0"chill"
1"pulsed"
2"glinting"
3"echoed"
4"tension"
5"flickered"
6"stomach"
7"silence"
8"fractured"
9"shattered"
10"scanning"
11"uncanny"
12"pulse"
13"quickened"
14"anticipation"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"stomach dropped/sank"
count1
highlights
0"stomach dropped"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences102
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences102
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences126
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen33
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1136
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions16
unquotedAttributions0
matches(empty)
16.34% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions62
wordCount823
uniqueNames21
maxNameDensity2.67
worstName"Quinn"
maxWindowNameDensity4.5
worstWindowName"Quinn"
discoveredNames
Tube1
Harlow1
Quinn22
Camden2
Morris1
Kowalski1
Aurora1
Eva17
British1
Museum1
Ovaltine1
English1
Latin1
Veil2
Market1
London1
Town1
Hargrove1
Kale3
Compass1
Victor1
persons
0"Harlow"
1"Quinn"
2"Morris"
3"Kowalski"
4"Eva"
5"Museum"
6"Market"
7"Hargrove"
8"Kale"
9"Victor"
places
0"Camden"
1"Aurora"
2"British"
3"London"
4"Town"
globalScore0.163
windowScore0.167
57.41% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences54
glossingSentenceCount2
matches
0"looked like it had been pressed in with a"
1"looked like twisted vines forming a sigil"
23.94% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords1.761
wordCount1136
matches
0"not toward the tracks, not toward the platform’s edge, but toward the center of the platform itself"
1"not toward the platform’s edge, but toward the center of the platform itself"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences126
matches
0"hated that she"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs56
mean20.29
std19.91
cv0.982
sampleLengths
095
124
265
37
480
512
625
77
819
970
1023
118
1232
1315
1431
157
1621
178
1821
199
203
2137
2246
2332
248
2530
266
2723
2833
2919
3011
3114
3216
3336
346
3524
368
3711
3812
3928
403
412
4217
4352
444
453
462
472
4816
496
94.94% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences102
matches
0"been sealed"
1"was bathed"
2"been pressed"
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs143
matches
0"was reciting"
1"was wearing "
2"wasn’t looking"
3"was looking"
4"were moving"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount11
semicolonCount0
flaggedSentences11
totalSentences126
ratio0.087
matches
0"She hadn’t expected a call like this — not here."
1"Only now, Eva wasn’t a schoolgirl — she was a researcher, her satchel bulging with books she’d probably pulled from the British Museum’s restricted archives."
2"Not even in the air — which, given the violence of the death, should have reeked of copper and fear."
3"There, in the grout between two tiles, was a mark — a symbol scratched into the cement."
4"It looked like twisted vines forming a sigil — one she’d seen in Eva’s old research notes."
5"The Veil Market moved beneath London, but only once a month — on the full moon."
6"Not with electricity — with something older."
7"“DI Hargrove? It’s Quinn. I need you to check something.” She gave the address — a disused platform beneath Camden Town."
8"Like the one Kale was wearing — tailored wool, slightly damp, as if he’d walked through fog."
9"She tapped the face — the needle spun wildly, then steadied, pointing not toward the tracks, not toward the platform’s edge, but toward the center of the platform itself."
10"His eyes flew open — black."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount668
adjectiveStacks0
stackExamples(empty)
adverbCount16
adverbRatio0.023952095808383235
lyAdverbCount9
lyAdverbRatio0.01347305389221557
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences126
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences126
mean9.02
std7.27
cv0.807
sampleLengths
023
120
224
328
410
514
612
79
819
920
105
117
123
134
1415
1533
1625
175
187
1911
2014
212
225
2317
242
2512
2628
272
288
2920
3013
3110
328
336
3414
3512
366
379
388
3923
403
414
427
432
443
453
463
473
485
493
50.26% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.3492063492063492
totalSentences126
uniqueOpeners44
40.65% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences82
matches
0"Only now, Eva wasn’t a"
ratio0.012
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount17
totalSentences82
matches
0"She hadn’t expected a call"
1"Her boots made little sound"
2"She didn’t need to."
3"She crouched beside the body,"
4"She snapped them on, the"
5"She pointed to the victim’s"
6"It looked like it had"
7"It looked like twisted vines"
8"she said, voice tight"
9"She knelt beside Quinn, adjusting"
10"She stood again, scanning the"
11"She gave the address —"
12"She hung up, turning to"
13"She tapped the face —"
14"His body twitched."
15"His eyes flew open —"
16"She was looking at the"
ratio0.207
75.85% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount63
totalSentences82
matches
0"The Tube station had been"
1"The air smelled of rust"
2"Detective Harlow Quinn adjusted the"
3"The scene was bathed in"
4"She hadn’t expected a call"
5"Detective Quinn moved forward, her"
6"Her boots made little sound"
7"A body lay sprawled near"
8"DS Morris’s voice echoed in"
9"a voice said behind her"
10"Quinn didn’t turn."
11"She didn’t need to."
12"The tone was light, almost"
13"Eva Kowalski stood a few"
14"Quinn said, voice low"
15"Eva said, stepping forward, her"
16"Eva’s green eyes flickered toward"
17"Quinn said, reading from a"
18"She crouched beside the body,"
19"Quinn reached into her coat"
ratio0.768
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences82
matches(empty)
ratio0
87.91% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences26
technicalSentenceCount2
matches
0"The scene was bathed in the sickly yellow glow of crime scene lamps, their cables snaking through puddles of water that had pooled on the cracked concrete floor…"
1"She knelt beside Quinn, adjusting her glasses, then recoiled as if burned."
66.18% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags17
uselessAdditionCount2
matches
0"Quinn said, voice low"
1"she said, voice tight"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags12
fancyCount1
fancyTags
0"Quinn muttered (mutter)"
dialogueSentences42
tagDensity0.286
leniency0.571
rawRatio0.083
effectiveRatio0.048
73.9998%