Run: 2026-02-20-01KHY8JD5Y7N1XG962BTF95WYB

Run Details

Duration:
4.7s
Cost:
$0.000276
Provider:
Mistral

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 hammered against the pavement in relentless sheets, each drop a tiny hammer striking the metal grates beneath Quinn’s boots. She didn’t slow. Didn’t hesitate. The suspect—some low-level dealer with a habit of slipping through the cracks—had bolted into the shadows near the old Tube station entrance, his coat flapping like a flag in the wind. Quinn’s breath came sharp, her fingers curling around the grip of her service revolver. The gun was cold, the weight familiar. She’d carried it through enough nights to know its rhythm. A flicker of movement. A flash of dark fabric disappearing into the mouth of the tunnel. Quinn didn’t think. She moved. The air grew thick with the scent of damp stone and something older—something metallic, like old blood left to rust. The tunnel sloped downward, the walls slick with condensation. Her boots splashed through puddles that glowed faintly under the flickering neon of a distant sign. *The Raven’s Nest.* She recognised it. A dive bar, but not the kind that served gin and gossip. The kind that served things that didn’t belong in the daylight. The suspect was already gone. No footprints in the mud. No trail of breath in the cold air. Just the echo of his retreat, swallowed by the dark. Quinn pressed her back against the wall, listening. The tunnel stretched ahead, a labyrinth of rusted pipes and flickering bulbs. Somewhere beyond the next bend, the suspect had vanished. Or worse—he’d found a way out she didn’t know about. A sound. Not footsteps. Something else. A low, rhythmic *thump*. Like a heartbeat. Or a pulse. She tensed. Then she saw it—a door, half-hidden behind a tangle of wires. Not the kind of door you’d expect in a Tube tunnel. This one was old, its wood warped, its brass handle tarnished. The kind of door that shouldn’t be here at all. Quinn’s pulse spiked. She reached for her radio, then hesitated. No signal down here. No backup. Just her and the dark. The thumping grew louder. Closer. She stepped forward, her boot scraping against the stone. The door creaked when she pushed it open. Inside, the air was thick with the scent of herbs and something sharper—alcohol, maybe, or something stronger. A room. Not a bar. A *market*. Stalls lined the walls, draped in velvet and lined with glass jars filled with powders and liquids that shimmered under the dim light. People moved between them, their faces half-lit by flickering lanterns. Some wore masks. Others didn’t bother. A man in a long coat stood near the back, his back to her. He wasn’t the suspect. Not yet. But he was watching something—a table laden with bones. Human bones. Arranged in patterns. Some still fresh, their marrow glistening. Quinn’s grip tightened on her revolver. She didn’t know what she was walking into. But she knew one thing for certain. She wasn’t leaving without answers. The man at the table didn’t turn. Didn’t react. Just kept his eyes on the bones, his fingers tracing the edges of one that looked like it had been recently cut. Quinn stepped forward, her boots silent on the warped floorboards. “You’re not supposed to be here,” the man said, his voice low, smooth. He didn’t sound scared. Just… amused. She didn’t answer. She didn’t have to. The suspect appeared behind him, his face pale in the dim light. He looked like he’d seen a ghost. The man at the table finally turned. His eyes locked onto Quinn’s. And for the first time, she saw the truth in them. He wasn’t selling bones. He was selling *memories*.
created_at"2026-02-20T19:31:32.678Z" 2/20/2026, 7:31:32 PM
model"mistralai/ministral-8b-2512"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency419
moderation_latency(null)
generation_time4468
tokens_prompt1140
tokens_completion939
native_tokens_prompt1027
native_tokens_completion811
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"
usage0.0002757
router(null)
provider_responses
0
endpoint_id"c85d26e1-1e0c-449b-9775-2afce7ae510b"
id"69bea34ac54e4f5e96f5928f02c9fcec"
is_byokfalse
latency419
model_permaslug"mistralai/ministral-8b-2512"
provider_name"Mistral"
status200
api_type"completions"
id"gen-1771615892-PGK0lt1Zv57VCucTDhup"
upstream_id"69bea34ac54e4f5e96f5928f02c9fcec"
total_cost0.0002757
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)
dialogueSentences1
tagDensity1
leniency1
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount610
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)
1.64% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount610
totalAiIsms12
found
0
word"weight"
count1
1
word"familiar"
count1
2
word"flicker"
count1
3
word"echo"
count1
4
word"footsteps"
count1
5
word"rhythmic"
count1
6
word"pulse"
count2
7
word"velvet"
count1
8
word"shimmered"
count1
9
word"glistening"
count1
10
word"tracing"
count1
highlights
0"weight"
1"familiar"
2"flicker"
3"echo"
4"footsteps"
5"rhythmic"
6"pulse"
7"velvet"
8"shimmered"
9"glistening"
10"tracing"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"air was thick with"
count1
highlights
0"the air was thick with"
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
filterCount0
hedgeCount0
narrationSentences81
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences81
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen34
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans4
markdownWords6
totalWords600
ratio0.01
matches
0"The Raven’s Nest."
1"thump"
2"market"
3"memories"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions2
unquotedAttributions0
matches(empty)
82.66% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions11
wordCount594
uniqueNames3
maxNameDensity1.35
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Quinn8
Tube2
Raven1
persons
0"Quinn"
1"Raven"
places
0"Tube"
globalScore0.827
windowScore1
0.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences42
glossingSentenceCount3
matches
0"looked like it had been recently cut"
1"appeared behind him, his face pale in the dim light"
2"looked like he’d seen a ghost"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount600
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences81
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs24
mean25
std22.36
cv0.894
sampleLengths
088
121
274
328
439
516
62
743
821
95
1017
1163
1240
1321
145
1531
1610
1719
187
1919
2012
2111
224
234
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences81
matches(empty)
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs96
matches
0"was watching"
1"was walking"
2"wasn’t leaving"
3"wasn’t selling"
4"was selling"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount7
semicolonCount0
flaggedSentences6
totalSentences81
ratio0.074
matches
0"The suspect—some low-level dealer with a habit of slipping through the cracks—had bolted into the shadows near the old Tube station entrance, his coat flapping like a flag in the wind."
1"The air grew thick with the scent of damp stone and something older—something metallic, like old blood left to rust."
2"Or worse—he’d found a way out she didn’t know about."
3"Then she saw it—a door, half-hidden behind a tangle of wires."
4"Inside, the air was thick with the scent of herbs and something sharper—alcohol, maybe, or something stronger."
5"But he was watching something—a table laden with bones."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount604
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.028145695364238412
lyAdverbCount3
lyAdverbRatio0.004966887417218543
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences81
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences81
mean7.41
std5.72
cv0.772
sampleLengths
021
13
22
331
414
57
610
74
812
93
102
1120
129
1316
146
1512
1611
175
185
198
2010
218
2212
239
2410
252
262
272
284
293
303
312
3211
3311
3411
3510
363
377
384
392
405
414
421
439
448
4517
462
473
482
4923
51.03% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.35802469135802467
totalSentences81
uniqueOpeners29
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount5
totalSentences66
matches
0"Just the echo of his"
1"Somewhere beyond the next bend,"
2"Then she saw it—a door,"
3"Just her and the dark."
4"Just kept his eyes on"
ratio0.076
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount15
totalSentences66
matches
0"She didn’t slow."
1"She’d carried it through enough"
2"Her boots splashed through puddles"
3"She reached for her radio,"
4"She stepped forward, her boot"
5"He wasn’t the suspect."
6"She didn’t know what she"
7"She wasn’t leaving without answers."
8"He didn’t sound scared."
9"She didn’t answer."
10"She didn’t have to."
11"He looked like he’d seen"
12"His eyes locked onto Quinn’s."
13"He wasn’t selling bones."
14"He was selling *memories*."
ratio0.227
96.36% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount48
totalSentences66
matches
0"The rain hammered against the"
1"She didn’t slow."
2"The suspect—some low-level dealer with"
3"Quinn’s breath came sharp, her"
4"The gun was cold, the"
5"She’d carried it through enough"
6"A flicker of movement."
7"A flash of dark fabric"
8"Quinn didn’t think."
9"The air grew thick with"
10"The tunnel sloped downward, the"
11"Her boots splashed through puddles"
12"*The Raven’s Nest.* She recognised"
13"A dive bar, but not"
14"The kind that served things"
15"The suspect was already gone."
16"Quinn pressed her back against"
17"The tunnel stretched ahead, a"
18"A low, rhythmic *thump*."
19"This one was old, its"
ratio0.727
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences66
matches(empty)
ratio0
85.71% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences25
technicalSentenceCount2
matches
0"The suspect—some low-level dealer with a habit of slipping through the cracks—had bolted into the shadows near the old Tube station entrance, his coat flapping …"
1"Her boots splashed through puddles that glowed faintly under the flickering neon of a distant sign."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags1
uselessAdditionCount1
matches
0"the man said, his voice low, smooth"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences1
tagDensity1
leniency1
rawRatio0
effectiveRatio0
77.2469%