Run: 2026-02-20-01KHYB8Q1MZ5M980HW05Y7NBWT

Run Details

Duration:
3.3s
Cost:
$0.000199
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 neon glow of the Raven’s Nest pulsed like a heartbeat against the rain-slicked pavement, its green sign flickering weakly. Detective Harlow Quinn’s breath fogged in the cold air as she sprinted past the dimly lit windows, her boots splashing through puddles. The scent of aged wood and something metallic—old blood, maybe—cut through the damp. She didn’t slow down. Ahead, Tomás Herrera moved with the fluid grace of someone who’d spent years dodging bullets, his dark curls damp but unbroken. He turned a corner, disappearing into the labyrinth of alleyways that led deeper into Soho. Quinn’s fingers tightened around the grip of her revolver, her jaw set. She’d been chasing this lead for weeks, but every step felt like a gamble. The air grew thicker, the scent of damp stone and something older, something *wrong*, seeping from the cracks in the pavement. She followed the sound of voices—low, urgent, muffled. Ahead, the alley split, and she saw the flicker of a lantern, casting long shadows over a crumbling Tube station entrance. The door was ajar. Quinn hesitated. The Veil Market wasn’t just a place—it was a trap. But Tomás wasn’t the kind to walk away from a fight. She took a deep breath, her military precision kicking in. The door groaned as she pushed it open, the cold draft of the underground hitting her like a slap. The station was a maze of rusted tracks and flickering bulbs, the air thick with the scent of damp earth and something darker. The voices grew louder, closer. Quinn’s pulse hammered in her throat as she stepped forward, her boots sinking slightly into the uneven floor. Then she saw him. Tomás stood in the center of the station, his back to her, his Saint Christopher medallion glinting under the dim light. Beside him, a figure moved—tall, cloaked, their face obscured by the shadows. Quinn’s instincts screamed at her to run, but her training wouldn’t let her. She had to know. “Herrera,” she called, her voice steady despite the adrenaline. “You’re not alone.” Tomás didn’t turn. “I know.” The cloaked figure spoke, their voice smooth, dangerous. “She’s too late.” Quinn’s grip on her revolver tightened. “Who the hell are you?” The figure stepped forward, their silhouette sharp against the dim light. “You’ve been looking for answers, Detective. But answers don’t stay where they’re found.” Tomás exhaled sharply, his voice low. “She’s not here to fight.” Quinn’s eyes flicked to him, then back to the stranger. “Then why are you both here?” The figure’s hand moved, and Quinn barely had time to react before a shadow lashed out— Tomás was there first, his body blocking the strike, his forearm slamming into the stranger’s ribs. Pain flared along his scarred skin, but he didn’t flinch. Quinn’s revolver was already drawn, her finger tightening on the trigger. “Drop it,” she ordered, her voice a low growl. The stranger didn’t move. “You don’t understand what you’re walking into.” Quinn’s breath came fast. “Then explain it.” The figure’s laughter was dark, echoing through the station. “The Veil Market doesn’t sell just goods. It sells secrets. And secrets have teeth.” Tomás’s grip on the stranger’s arm tightened, his voice a growl. “We’re not leaving until you talk.” The stranger’s eyes burned with something Quinn couldn’t read. Then, with a final smirk, they vanished into the shadows. Tomás exhaled, his shoulders slumping slightly. “That was the wrong end of the stick.” Quinn didn’t lower her weapon. “You’re not the only one who’s been playing games.” The station was silent except for the distant hum of the Tube, the rain still falling outside. Quinn’s mind raced, her instincts screaming at her to move, to run. But she couldn’t leave yet. Tomás stepped forward, his voice low. “We need to talk. About what happened to Morris.” Quinn’s jaw tightened. “I don’t have time for this.” Tomás’s gaze locked onto hers, his eyes warm but weary. “Then we do it now.” She didn’t argue. The Veil Market wasn’t just a place—it was a place where the past caught up with you. And Quinn wasn’t about to let it leave her behind.
created_at"2026-02-20T20:18:40.829Z" 2/20/2026, 8:18:40 PM
model"mistralai/ministral-3b-2512"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency223
moderation_latency(null)
generation_time3055
tokens_prompt1140
tokens_completion1143
native_tokens_prompt1027
native_tokens_completion959
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"
usage0.0001986
router(null)
provider_responses
0
endpoint_id"b9f6828f-aef9-498a-91f5-6816fbf72420"
id"6425af86eaeb4a6c8042b4ed05f2c582"
is_byokfalse
latency223
model_permaslug"mistralai/ministral-3b-2512"
provider_name"Mistral"
status200
api_type"completions"
id"gen-1771618720-csaA1B8l1HNvurXeSbh9"
upstream_id"6425af86eaeb4a6c8042b4ed05f2c582"
total_cost0.0001986
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
totalTags2
adverbTagCount0
adverbTags(empty)
dialogueSentences18
tagDensity0.111
leniency0.222
rawRatio0
effectiveRatio0
78.39% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount694
totalAiIsmAdverbs3
found
0
adverb"slightly"
count2
1
adverb"sharply"
count1
highlights
0"slightly"
1"sharply"
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)
49.57% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount694
totalAiIsms7
found
0
word"pulsed"
count1
1
word"flicker"
count1
2
word"pulse"
count1
3
word"glinting"
count1
4
word"flicked"
count1
5
word"echoing"
count1
6
word"raced"
count1
highlights
0"pulsed"
1"flicker"
2"pulse"
3"glinting"
4"flicked"
5"echoing"
6"raced"
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
narrationSentences54
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences54
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences70
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen23
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords687
ratio0.001
matches
0"wrong"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
16.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions38
wordCount580
uniqueNames12
maxNameDensity2.59
worstName"Quinn"
maxWindowNameDensity4.5
worstWindowName"Quinn"
discoveredNames
Raven1
Nest1
Harlow1
Quinn15
Tomás10
Herrera1
Soho1
Tube2
Veil2
Market2
Saint1
Christopher1
persons
0"Raven"
1"Harlow"
2"Quinn"
3"Tomás"
4"Herrera"
5"Saint"
6"Christopher"
places
0"Soho"
globalScore0.207
windowScore0.167
89.02% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences41
glossingSentenceCount1
matches
0"felt like a gamble"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount687
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences70
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs29
mean23.69
std17.32
cv0.731
sampleLengths
059
162
254
352
446
54
650
712
85
911
1011
1124
1211
1316
1416
1537
169
1711
187
1923
2017
2119
2214
2314
2434
2515
269
2715
2830
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences54
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs100
matches(empty)
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount7
semicolonCount0
flaggedSentences6
totalSentences70
ratio0.086
matches
0"The scent of aged wood and something metallic—old blood, maybe—cut through the damp."
1"She followed the sound of voices—low, urgent, muffled."
2"The Veil Market wasn’t just a place—it was a trap."
3"Beside him, a figure moved—tall, cloaked, their face obscured by the shadows."
4"The figure’s hand moved, and Quinn barely had time to react before a shadow lashed out—"
5"The Veil Market wasn’t just a place—it was a place where the past caught up with you."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount587
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.028960817717206135
lyAdverbCount6
lyAdverbRatio0.010221465076660987
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences70
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences70
mean9.81
std5.65
cv0.576
sampleLengths
020
122
213
34
421
515
612
714
821
98
1021
114
122
1310
1411
1510
1619
1723
185
1918
204
2121
2212
2313
244
259
263
273
282
298
303
316
325
3311
3413
356
365
3710
386
3916
4016
4110
4211
439
444
457
464
473
489
4914
45.71% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.2714285714285714
totalSentences70
uniqueOpeners19
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences53
matches
0"Then she saw him."
1"Then, with a final smirk,"
ratio0.038
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount9
totalSentences53
matches
0"She didn’t slow down."
1"He turned a corner, disappearing"
2"She’d been chasing this lead"
3"She followed the sound of"
4"She took a deep breath,"
5"She had to know."
6"she called, her voice steady"
7"she ordered, her voice a"
8"She didn’t argue."
ratio0.17
35.47% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount45
totalSentences53
matches
0"The neon glow of the"
1"Detective Harlow Quinn’s breath fogged"
2"The scent of aged wood"
3"She didn’t slow down."
4"He turned a corner, disappearing"
5"Quinn’s fingers tightened around the"
6"She’d been chasing this lead"
7"The air grew thicker, the"
8"She followed the sound of"
9"The door was ajar."
10"The Veil Market wasn’t just"
11"She took a deep breath,"
12"The door groaned as she"
13"The station was a maze"
14"The voices grew louder, closer."
15"Quinn’s pulse hammered in her"
16"Tomás stood in the center"
17"Quinn’s instincts screamed at her"
18"She had to know."
19"she called, her voice steady"
ratio0.849
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences53
matches(empty)
ratio0
73.73% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences31
technicalSentenceCount3
matches
0"Ahead, Tomás Herrera moved with the fluid grace of someone who’d spent years dodging bullets, his dark curls damp but unbroken."
1"He turned a corner, disappearing into the labyrinth of alleyways that led deeper into Soho."
2"Tomás was there first, his body blocking the strike, his forearm slamming into the stranger’s ribs."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags2
uselessAdditionCount2
matches
0"she called, her voice steady despite the adrenaline"
1"she ordered, her voice a low growl"
94.44% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount1
fancyTags
0"she ordered (order)"
dialogueSentences18
tagDensity0.111
leniency0.222
rawRatio0.5
effectiveRatio0.111
79.4336%