Run: 2026-02-20-01KHYAC02FXGJT1B97PQQRN54M

Run Details

Duration:
5.7s
Cost:
$0.000322
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 down in sheets, turning the pavement slick as Quinn’s boots splashed through puddles. She kept her pace steady, the leather of her coat pulled tight against the cold. The suspect—some low-level dealer, probably—had bolted into the shadows near the old Tube station entrance, his hood pulled low. She didn’t recognise him, but that didn’t matter. The scent of damp concrete and something metallic clung to the air, sharp enough to make her nostrils flare. A flicker of movement near the rusted metal grate. Quinn didn’t hesitate. She lunged, fingers curling around the edge, hauling herself down into the dark. The moment her boots hit the uneven stone, she knew she was in the wrong place. The air smelled wrong—wet earth, something sour, like old coins left in a grave. Her flashlight cut through the gloom, illuminating the warren of tunnels ahead. The suspect was already moving, his footsteps echoing off the damp walls. Quinn adjusted her grip on her baton, the weight familiar in her palm. She didn’t like this. Not one bit. A narrow alley opened up ahead, the walls lined with flickering lanterns—oil, not electric. The kind of place that didn’t belong in London anymore. The suspect ducked into a side passage, his coat flapping behind him like a flag of surrender. Quinn followed, her breath steady despite the adrenaline. Then she saw the sign. A jagged green neon glow pulsed above a door half-hidden by peeling wallpaper. *The Raven’s Nest*. The name sent a prickle down her spine. She’d heard whispers about places like this—underground, off the grid, where things didn’t follow the rules. But she wasn’t here for the gossip. She was here for the suspect. The door creaked open under her touch. Inside, the air was thick with smoke and the low hum of voices. A bar stretched along one wall, its shelves lined with bottles she didn’t recognise. A few figures sat in the shadows, their faces half-lit by the dim glow of candles. The suspect was already disappearing into the back, his movements too quick, too sure. Quinn stepped inside, her boots sinking slightly into the uneven floor. A man behind the bar—a gaunt figure with a scar running down his cheek—glanced up, his eyes narrowing. "Evening, Detective," he said, voice smooth as oil. "You’re not usually this deep underground." She didn’t answer. She didn’t have time. The suspect was already through a door marked with a faded *Private* sign. Quinn followed, her pulse hammering in her ears. The back room was smaller, the air heavier. A table stood in the centre, its surface littered with papers and a half-empty glass of something amber. A man sat in the chair, his back to her. Tomás Herrera. She recognised the medallion around his neck, the one she’d seen in old photos—Saint Christopher, ironically enough. He turned just as she stepped in. His dark eyes locked onto hers, unblinking. "Detective Quinn," he said, voice calm. "I was wondering when you’d show up." She didn’t move. Didn’t reach for her cuffs. "Where is he?" Herrera’s lips curled, just slightly. "Who?" "The dealer. The one you were selling to." A beat of silence. Then, quietly: "You’re not here for that." Quinn’s fingers twitched. She knew better than to trust him. But she also knew she was running out of time. "I’m here for the truth," she said. "And right now, I don’t have it." Herrera stood, slow and deliberate. "Then you’ll have to take it from me." The door behind her creaked open. A woman stepped in, her dark hair pulled back in a tight bun. She carried a knife, its blade catching the light. "Detective," she said, voice low. "You shouldn’t have come." Quinn didn’t look at her. She kept her eyes on Herrera. "Where is he?" Herrera exhaled, long and slow. "He’s not here anymore." The woman’s hand tightened on the knife. "He’s gone. And so are you, if you’re not careful." Quinn’s breath hitched. She could feel the weight of the situation pressing down on her. She wasn’t here to play games. She was here to find answers. She took a step forward, her voice steady. "Then tell me where he went." Herrera’s gaze flicked to the woman, then back to Quinn. "You’re not ready for what you’ll find." Quinn didn’t flinch. "I’m ready." The woman laughed, sharp and bitter. "You don’t know that." The air between them thickened. Quinn could feel the tension, the unspoken threat. She wasn’t leaving without answers. Not now. She reached into her coat, her fingers brushing against the cold metal of her baton. "I’ll take what I need." Herrera’s eyes widened, just for a second. Then he spoke, his voice cutting through the tension like a blade. "Then you’ll have to go through me." The woman’s hand tightened on the knife. "Or her." Quinn didn’t hesitate. She moved.
created_at"2026-02-20T20:02:59.8Z" 2/20/2026, 8:02:59 PM
model"mistralai/ministral-8b-2512"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency205
moderation_latency(null)
generation_time4934
tokens_prompt1140
tokens_completion1276
native_tokens_prompt1027
native_tokens_completion1121
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached256
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"
usage0.0003222
router(null)
provider_responses
0
endpoint_id"c85d26e1-1e0c-449b-9775-2afce7ae510b"
id"564008c3698247f895799388950ebc09"
is_byokfalse
latency205
model_permaslug"mistralai/ministral-8b-2512"
provider_name"Mistral"
status200
api_type"completions"
id"gen-1771617779-DrDWPOYUqXaBuVhrl2zp"
upstream_id"564008c3698247f895799388950ebc09"
total_cost0.0003222
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
totalTags4
adverbTagCount0
adverbTags(empty)
dialogueSentences23
tagDensity0.174
leniency0.348
rawRatio0
effectiveRatio0
87.88% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount825
totalAiIsmAdverbs2
found
0
adverb"slightly"
count2
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)
0.00% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount825
totalAiIsms19
found
0
word"flicker"
count1
1
word"grave"
count1
2
word"gloom"
count1
3
word"footsteps"
count1
4
word"echoing"
count1
5
word"weight"
count2
6
word"familiar"
count1
7
word"electric"
count1
8
word"pulsed"
count1
9
word"down her spine"
count1
10
word"pulse"
count1
11
word"silence"
count1
12
word"could feel"
count2
13
word"flicked"
count1
14
word"tension"
count2
15
word"unspoken"
count1
highlights
0"flicker"
1"grave"
2"gloom"
3"footsteps"
4"echoing"
5"weight"
6"familiar"
7"electric"
8"pulsed"
9"down her spine"
10"pulse"
11"silence"
12"could feel"
13"flicked"
14"tension"
15"unspoken"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"eyes widened/narrowed"
count1
1
label"air was thick with"
count1
highlights
0"eyes widened"
1"the air was thick with"
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
filterCount0
hedgeCount0
narrationSentences82
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences100
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen22
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords4
totalWords813
ratio0.005
matches
0"The Raven’s Nest"
1"Private"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions7
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount704
uniqueNames7
maxNameDensity1.85
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Quinn"
discoveredNames
Quinn13
Tube1
London1
Raven1
Herrera7
Saint1
Christopher1
persons
0"Quinn"
1"Raven"
2"Herrera"
3"Saint"
4"Christopher"
places
0"London"
globalScore0.577
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences55
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount813
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences100
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs31
mean26.23
std19.97
cv0.761
sampleLengths
077
167
232
349
45
553
664
743
828
955
1027
1111
126
138
1411
1534
1613
1737
1814
199
2017
2127
2214
2317
245
2510
2620
2720
2826
299
305
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences82
matches(empty)
93.33% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs125
matches
0"was running"
1"wasn’t leaving"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount0
flaggedSentences6
totalSentences100
ratio0.06
matches
0"The suspect—some low-level dealer, probably—had bolted into the shadows near the old Tube station entrance, his hood pulled low."
1"The air smelled wrong—wet earth, something sour, like old coins left in a grave."
2"A narrow alley opened up ahead, the walls lined with flickering lanterns—oil, not electric."
3"She’d heard whispers about places like this—underground, off the grid, where things didn’t follow the rules."
4"A man behind the bar—a gaunt figure with a scar running down his cheek—glanced up, his eyes narrowing."
5"She recognised the medallion around his neck, the one she’d seen in old photos—Saint Christopher, ironically enough."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount716
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.027932960893854747
lyAdverbCount5
lyAdverbRatio0.006983240223463687
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences100
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences100
mean8.13
std4.57
cv0.562
sampleLengths
016
115
219
38
419
59
63
713
816
914
1012
1112
1213
134
143
1514
1610
1717
188
195
2013
213
228
2316
247
256
267
2713
2814
2916
3014
3111
3218
338
346
353
364
3713
388
398
4018
4110
422
4317
447
457
466
477
483
495
40.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.22
totalSentences100
uniqueOpeners22
86.58% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences77
matches
0"Then she saw the sign."
1"Then he spoke, his voice"
ratio0.026
90.13% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount25
totalSentences77
matches
0"She kept her pace steady,"
1"She didn’t recognise him, but"
2"She lunged, fingers curling around"
3"Her flashlight cut through the"
4"She didn’t like this."
5"She’d heard whispers about places"
6"She was here for the"
7"he said, voice smooth as"
8"She didn’t answer."
9"She didn’t have time."
10"She recognised the medallion around"
11"He turned just as she"
12"His dark eyes locked onto"
13"he said, voice calm"
14"She didn’t move."
15"She knew better than to"
16"She carried a knife, its"
17"she said, voice low"
18"She kept her eyes on"
19"She could feel the weight"
ratio0.325
11.95% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount69
totalSentences77
matches
0"The rain hammered down in"
1"She kept her pace steady,"
2"The suspect—some low-level dealer, probably—had"
3"She didn’t recognise him, but"
4"The scent of damp concrete"
5"A flicker of movement near"
6"Quinn didn’t hesitate."
7"She lunged, fingers curling around"
8"The moment her boots hit"
9"The air smelled wrong—wet earth,"
10"Her flashlight cut through the"
11"The suspect was already moving,"
12"Quinn adjusted her grip on"
13"She didn’t like this."
14"A narrow alley opened up"
15"The kind of place that"
16"The suspect ducked into a"
17"Quinn followed, her breath steady"
18"A jagged green neon glow"
19"*The Raven’s Nest*."
ratio0.896
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences77
matches(empty)
ratio0
96.77% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences31
technicalSentenceCount2
matches
0"The suspect was already moving, his footsteps echoing off the damp walls."
1"A man behind the bar—a gaunt figure with a scar running down his cheek—glanced up, his eyes narrowing."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount3
matches
0"he said, voice smooth as oil"
1"he said, voice calm"
2"she said, voice low"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount0
fancyTags(empty)
dialogueSentences23
tagDensity0.174
leniency0.348
rawRatio0
effectiveRatio0
77.4437%