Run: 2026-02-20-01KHYB7DWWZFQFWAG68TZJK96H

Run Details

Duration:
2.7s
Cost:
$0.000168
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="4412" name="Aurora Carter" aliases="Rory, Laila, Aurora, Carter, Malphora" pronouns="she/her" species="Human" storyRole="Protagonist"> <eyeColor>bright blue</eyeColor> <hair>straight shoulder-length black</hair> <height>5'6"</height> <age>25</age> <scar>small crescent-shaped scar on her left wrist from a childhood accident</scar> <description>Aurora, referred to by her friends as Rory, is cool-headed, intelligent, and known for quick out-of-the-box thinking.</description> <backstory>Born in Cardiff to an Irish barrister father (Brendan Carter) and Welsh teacher mother (Jennifer Carter née Ellis), Rory reluctantly pursued Pre-Law at Cardiff University. She fled to London at the behest of her childhood friend Eva after leaving an abusive ex named Evan. By day, Rory works part-time as a delivery person for Yu-Fei Cheung's Golden Empress restaurant. She lives in a flat above Silas' bar.</backstory> </character> <character id="4415" name="Lucien Moreau" aliases="Lucien, Luc, the Frenchman" pronouns="he/him" species="Half-Demon" storyRole="Ally"> <eyeColor>heterochromatic — one amber, one black</eyeColor> <hair>slicked-back platinum blond</hair> <height>5'11"</height> <age>32</age> <cane>ivory-handled cane that conceals a thin blade</cane> <dress>tailored charcoal suits</dress> <description>An impeccably dressed fixer and information broker in London's supernatural underworld. He speaks four languages fluently.</description> <backstory>Born in Marseille to a human mother and a demon father from the realm of Avaros.</backstory> </character> <location id="858" name="Eva's Flat" aliases="Eva's place, the flat on Brick Lane" realm="Earth"> <cat>tabby cat named Ptolemy</cat> <security>three deadbolts on the front door</security> <description>A cramped one-bedroom flat above a curry house on Brick Lane, East London. Every surface is covered with books, scrolls, and research notes.</description> </location> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the romance genre. Two people who parted on complicated terms are forced together again when one shows up unannounced at the other's flat. There's history between them — attraction, hurt, and things left unsaid. Write the scene from the moment the door opens. 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 front door of Eva’s flat groaned under the weight of the deadbolt, the old hinges protesting like a tired old man. Aurora Carter stepped inside, her breath catching at the scent of old paper and something faintly metallic—Ptolemy’s fur, curled around the edge of a half-eaten can of tuna. She kicked off her boots, the soles cold against the worn linoleum. “You’re late,” Eva said without looking up from her scrolls, though her voice was soft, just loud enough to carry over the hum of the flat’s single bulb. Aurora didn’t answer. She moved past the cluttered desk, the weight of her backpack dragging against her hips. The flat smelled like ink and something sharp, like the edge of a blade she’d once tried to hide. She kicked off her boots again, the soles cold against the linoleum. Eva finally glanced up, her dark eyes sharp. “You’re not supposed to be here.” Aurora didn’t turn around. “I’m not.” A beat. The air between them thickened, the kind of silence that pressed against your ribs like a fist. Eva exhaled, slow and deliberate. “You came for the job.” Aurora finally faced her. “I came for you.” Eva’s fingers twitched toward the cane resting on the desk, but she didn’t draw it. “You don’t have to do this.” “Do what?” Aurora’s voice was low, rough. “Tell me to leave?” Eva’s jaw tightened. “No.” Aurora stepped closer, the scent of her perfume—something floral and bitter—filling the space. “Then tell me why you didn’t answer my texts.” Eva’s hands clenched around the cane. “Because I didn’t want to see you.” Aurora’s laugh was bitter. “You didn’t *not* want to see me. You just didn’t want to admit it.” A sharp intake of breath. Eva’s eyes flicked to the door, then back to Aurora. “You’re here because of Lucien.” Aurora’s fingers curled into the fabric of her shirt. “He told me you’d be here.” Eva’s voice dropped, dangerous. “He’s not supposed to be involved.” “He’s always been involved,” Aurora said, her voice quieter now. “With you. With me. With everything.” Eva’s gaze snapped to her, sharp as a blade. “You don’t know what you’re talking about.” Aurora stepped back, the weight of the past pressing down. “I know you let him walk away from me.” Eva’s breath hitched. “He didn’t walk away.” “He did,” Aurora said, her voice breaking just a little. “He left me behind.” Eva’s hands shook. “That’s not true.” Aurora’s eyes burned. “Then tell me what happened.” The silence stretched, thick and suffocating. Eva’s fingers dug into the cane’s handle. “You’re not supposed to be here.” Aurora didn’t answer. She turned, her back to Eva, and reached for the door. The deadbolt clicked shut behind her, the lock engaging with a final, satisfying *click*. Eva’s voice followed her out, sharp and cold. “You’re making a mistake.” Aurora didn’t look back. The door swung open, the night air sharp against her skin. She didn’t turn around. She didn’t look back.
created_at"2026-02-20T20:17:58.694Z" 2/20/2026, 8:17:58 PM
model"mistralai/ministral-3b-2512"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency244
moderation_latency(null)
generation_time2461
tokens_prompt1034
tokens_completion842
native_tokens_prompt959
native_tokens_completion723
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached512
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"
usage0.0001682
router(null)
provider_responses
0
endpoint_id"b9f6828f-aef9-498a-91f5-6816fbf72420"
id"79631d18162f425fa08afef99eaa744e"
is_byokfalse
latency244
model_permaslug"mistralai/ministral-3b-2512"
provider_name"Mistral"
status200
api_type"completions"
id"gen-1771618678-QLvAuF9xwKKNGGHxvhEy"
upstream_id"79631d18162f425fa08afef99eaa744e"
total_cost0.0001682
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
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences26
tagDensity0.115
leniency0.231
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount502
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)
40.24% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount502
totalAiIsms6
found
0
word"weight"
count3
1
word"silence"
count2
2
word"flicked"
count1
highlights
0"weight"
1"silence"
2"flicked"
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
emotionTells1
narrationSentences41
matches
0"was bitter"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences41
filterMatches(empty)
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences63
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen30
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords2
totalWords498
ratio0.004
matches
0"not"
1"click"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions12
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions32
wordCount365
uniqueNames4
maxNameDensity4.11
worstName"Eva"
maxWindowNameDensity6.5
worstWindowName"Eva"
discoveredNames
Eva15
Carter1
Ptolemy1
Aurora15
persons
0"Eva"
1"Carter"
2"Ptolemy"
3"Aurora"
places(empty)
globalScore0
windowScore0
45.83% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences24
glossingSentenceCount1
matches
0"smelled like ink and something sharp, like"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount498
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences63
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs27
mean18.44
std12.61
cv0.684
sampleLengths
062
128
249
314
46
529
68
721
811
94
1022
1113
1218
1320
1415
1510
1616
1716
1819
197
2014
216
228
2319
2428
2512
2623
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences41
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs60
matches(empty)
52.15% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount0
flaggedSentences2
totalSentences63
ratio0.032
matches
0"Aurora Carter stepped inside, her breath catching at the scent of old paper and something faintly metallic—Ptolemy’s fur, curled around the edge of a half-eaten can of tuna."
1"Aurora stepped closer, the scent of her perfume—something floral and bitter—filling the space."
94.69% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount369
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.04607046070460705
lyAdverbCount3
lyAdverbRatio0.008130081300813009
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences63
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences63
mean7.9
std5.68
cv0.718
sampleLengths
022
128
212
328
43
515
619
712
88
96
104
112
122
1317
145
155
164
174
1815
196
207
214
223
231
2413
259
266
277
284
2914
305
3110
325
339
346
354
366
3710
386
399
407
4110
429
433
444
4510
464
473
483
493
43.65% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.23809523809523808
totalSentences63
uniqueOpeners15
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences40
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount6
totalSentences40
matches
0"She kicked off her boots,"
1"She moved past the cluttered"
2"She kicked off her boots"
3"She turned, her back to"
4"She didn’t turn around."
5"She didn’t look back."
ratio0.15
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount40
totalSentences40
matches
0"The front door of Eva’s"
1"Aurora Carter stepped inside, her"
2"She kicked off her boots,"
3"Eva said without looking up"
4"Aurora didn’t answer."
5"She moved past the cluttered"
6"The flat smelled like ink"
7"She kicked off her boots"
8"Eva finally glanced up, her"
9"Aurora didn’t turn around."
10"The air between them thickened,"
11"Eva exhaled, slow and deliberate."
12"Aurora finally faced her."
13"Eva’s fingers twitched toward the"
14"Aurora’s voice was low, rough"
15"Eva’s jaw tightened."
16"Aurora stepped closer, the scent"
17"Eva’s hands clenched around the"
18"Aurora’s laugh was bitter."
19"A sharp intake of breath."
ratio1
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences40
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences14
technicalSentenceCount0
matches(empty)
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount3
matches
0"Eva said, though her voice was soft, just loud enough to carry over the hum of the flat’s single bulb"
1"Aurora said, her voice quieter now"
2"Aurora said, her voice breaking just a little"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount0
fancyTags(empty)
dialogueSentences26
tagDensity0.115
leniency0.231
rawRatio0
effectiveRatio0
75.8855%