Run: 2026-02-19-01KHT0QTF8GS7YWHN8SZRNY35P

Run Details

Duration:
1m 8s
Cost:
$0.001532
Provider:
DeepInfra

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 knock at the door was sharp, deliberate. Rory froze mid-step, takeaway bag in hand, and glanced at the clock. Too late for a delivery, too early for Eva to be back from her night shift. She set the bag on the kitchen counter and crossed the flat, her socks silent on the worn hardwood. Through the peephole, the hall light caught platinum blond hair slicked back, the sharp angle of a jaw she hadn’t seen in months. Her breath hitched. She unlocked the three deadbolts in quick succession and pulled the door open. “Lucien.” “Aurora.” His voice was smooth, low, and carried that faint French accent she’d always found infuriatingly charming. He stood in the hallway, impeccably dressed as always in a charcoal suit, his ivory-handled cane resting at his side. His heterochromatic eyes—one amber, one black—locked onto hers with an intensity that made her stomach twist. “What are you doing here?” She crossed her arms, leaning against the doorframe. Her tone was sharper than she intended, but the sight of him dredged up a mix of emotions she hadn’t fully unpacked. “You haven’t answered my calls.” His gaze flicked over her face, searching for something. “Or my texts. Or my emails.” “And yet, here you are.” She shrugged, feigning nonchalance. “Showing up unannounced isn’t going to change that.” His lips thinned, a flicker of irritation crossing his features. “We need to talk.” “We talked.” She pushed off the doorframe, stepping back into the flat. “Months ago. You made your position clear.” “And you made yours.” He followed her inside, closing the door behind him. The click of the latch echoed in the cramped space. Ptolemy, Eva’s tabby cat, darted out from beneath the couch, eyeing Lucien with suspicion before retreating to the safety of the bedroom. Rory leaned against the kitchen counter, arms still crossed. The scent of curry from downstairs mingled with the faint hint of Lucien’s cologne—something woody and expensive. “So, what? You thought you’d just show up and we’d pick up where we left off?” “No.” He stepped closer, his cane tapping softly against the floor. “I thought I’d show up and we’d finally have the conversation we should’ve had months ago.” “There’s nothing left to say.” She turned her back to him, busying herself with the takeaway bag. The steam from the container fogged the air, and she focused on the warmth of it, the familiarity, anything to keep her hands steady. “You’re lying.” His voice was closer now, just behind her. She could feel the heat of him, the proximity she’d once craved now unnerving. “You’ve never been a good liar, Aurora.” She spun around, the takeaway container clutched in her hand. “And you’ve never been good at taking no for an answer.” His gaze darkened, and for a moment, silence stretched between them. Then he reached out, his fingers brushing against her wrist, just above the small crescent-shaped scar she’d carried since childhood. “You’re still wearing the bracelet.” She glanced down at the delicate silver chain he’d given her on her birthday, just before everything fell apart. “It’s a bracelet, Lucien. It doesn’t mean anything.” “Bullshit.” His thumb traced the edge of the silver links, his touch igniting a spark of memory she’d tried to bury. “You don’t keep things that don’t mean something to you.” She pulled her hand away, setting the takeaway container on the counter with a thud. “Why are you here? Really?” He hesitated, his cane tapping against the floor as he shifted his weight. “I need your help.” She barked a laugh, harsh and humorless. “Of course you do. It’s always about what you need, isn’t it?” “It’s not just about me.” His voice was quiet, but there was an edge to it she couldn’t ignore. “There’s something happening in the city, something dangerous. And I can’t do this alone.” She crossed her arms, leaning back against the counter. “You’ve got plenty of allies, Lucien. People who haven’t spent the last six months trying to forget you.” His jaw tightened, and for a moment, she thought he might leave. Instead, he stepped closer, his amber and black eyes locking onto hers. “You’re right. I do have allies. But none of them are you.” Her chest tightened, but she forced herself to hold his gaze. “I’m not the same person I was when we met.” “Neither am I.” His voice softened, and she hated how it made her heart ache. “But I think we both know that doesn’t change what’s between us.” She looked away, her gaze landing on the books and scrolls scattered across the flat. Eva’s research notes, Ptolemy’s paw prints smudging the edges. Anything to avoid the intensity of his stare. “You hurt me, Lucien.” “And you hurt me.” His hand brushed against hers, tentative, questioning. “But I’m here. And I’m asking for your help. Not just for me, but for everyone.” She closed her eyes, exhaling slowly. The memory of their last argument played in her mind—sharp words, accusations, the sting of betrayal. But underneath it all was the undeniable pull she’d felt from the moment they met. A connection that neither time nor distance had managed to sever. When she opened her eyes, he was still there, waiting. His expression was unreadable, but there was something in his gaze—something raw and vulnerable—that made her chest tighten. “Fine.” She swallowed hard, forcing the word out before she could change her mind. “I’ll help you. But this doesn’t mean we’re okay.” A flicker of relief crossed his features, and he nodded. “Thank you.” She turned back to the takeaway container, her hands trembling as she pried it open. The scent of curry filled the air, grounding her. “You’re staying for dinner?” “If you’ll have me.” She glanced at him over her shoulder, her lips quirking in the hint of a smile. “Don’t push your luck.”
created_at"2026-02-19T03:57:43.793Z" 2/19/2026, 3:57:43 AM
model"deepseek/deepseek-chat-v3"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency223
moderation_latency(null)
generation_time68261
tokens_prompt1034
tokens_completion1595
native_tokens_prompt938
native_tokens_completion1384
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"
usage0.00153192
router(null)
provider_responses
0
endpoint_id"5294d55f-9012-496b-8f22-8cc919432dcd"
id"chatcmpl-RduWhtAvd4n05rL6TJSb6M4X"
is_byokfalse
latency53
model_permaslug"deepseek/deepseek-chat-v3"
provider_name"DeepInfra"
status200
api_type"completions"
id"gen-1771473463-arxs46jinYGRnmWJ0SLR"
upstream_id"chatcmpl-RduWhtAvd4n05rL6TJSb6M4X"
total_cost0.00153192
cache_discount(null)
upstream_inference_cost0
provider_name"DeepInfra"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags13
adverbTagCount2
adverbTags
0"that faint French accent she’d always [always]"
1"She swallowed hard [hard]"
dialogueSentences41
tagDensity0.317
leniency0.634
rawRatio0.154
effectiveRatio0.098
84.83% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount989
totalAiIsmAdverbs3
found
0
adverb"softly"
count1
1
adverb"really"
count1
2
adverb"slowly"
count1
highlights
0"softly"
1"really"
2"slowly"
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)
34.28% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount989
totalAiIsms13
found
0
word"intensity"
count2
1
word"stomach"
count1
2
word"flicked"
count1
3
word"flicker"
count2
4
word"echoed"
count1
5
word"warmth"
count1
6
word"could feel"
count1
7
word"silence"
count1
8
word"traced"
count1
9
word"weight"
count1
10
word"unreadable"
count1
highlights
0"intensity"
1"stomach"
2"flicked"
3"flicker"
4"echoed"
5"warmth"
6"could feel"
7"silence"
8"traced"
9"weight"
10"unreadable"
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
narrationSentences55
matches
0"A flicker of relief"
90.91% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount2
narrationSentences55
filterMatches(empty)
hedgeMatches
0"tried to"
1"managed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences82
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen24
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords980
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions8
wordCount707
uniqueNames4
maxNameDensity0.42
worstName"Eva"
maxWindowNameDensity1
worstWindowName"Lucien"
discoveredNames
Eva3
French1
Lucien2
Ptolemy2
persons
0"Eva"
1"Lucien"
2"Ptolemy"
places(empty)
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences53
glossingSentenceCount0
matches(empty)
0.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords2.041
wordCount980
matches
0"Not just for me, but for everyone"
1"neither time nor"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences82
matches(empty)
96.26% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs34
mean28.82
std14.03
cv0.487
sampleLengths
081
114
253
335
420
517
614
719
845
942
1027
1141
1231
1321
1436
1527
1631
1720
1817
1919
2033
2127
2236
2321
2427
2536
2627
2748
2828
2923
3012
3128
324
3320
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences55
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs120
matches(empty)
3.48% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount6
semicolonCount0
flaggedSentences4
totalSentences82
ratio0.049
matches
0"His heterochromatic eyes—one amber, one black—locked onto hers with an intensity that made her stomach twist."
1"The scent of curry from downstairs mingled with the faint hint of Lucien’s cologne—something woody and expensive."
2"The memory of their last argument played in her mind—sharp words, accusations, the sting of betrayal."
3"His expression was unreadable, but there was something in his gaze—something raw and vulnerable—that made her chest tighten."
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount716
adjectiveStacks1
stackExamples
0"small crescent-shaped scar"
adverbCount26
adverbRatio0.036312849162011177
lyAdverbCount6
lyAdverbRatio0.008379888268156424
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences82
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences82
mean11.95
std5.22
cv0.437
sampleLengths
08
112
216
319
423
53
613
71
817
920
1016
1113
1222
1314
146
159
168
1710
184
1912
207
2113
2210
2322
249
2517
2616
2711
2816
2917
3024
3110
3214
337
3410
3511
3611
3720
385
3919
408
4121
4210
4315
445
4513
464
477
4812
4919
76.02% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.4634146341463415
totalSentences82
uniqueOpeners38
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences55
matches
0"Too late for a delivery,"
1"Then he reached out, his"
2"Instead, he stepped closer, his"
ratio0.055
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount36
totalSentences55
matches
0"She set the bag on"
1"Her breath hitched."
2"She unlocked the three deadbolts"
3"His voice was smooth, low,"
4"He stood in the hallway,"
5"His heterochromatic eyes—one amber, one"
6"She crossed her arms, leaning"
7"Her tone was sharper than"
8"His gaze flicked over her"
9"She shrugged, feigning nonchalance"
10"His lips thinned, a flicker"
11"She pushed off the doorframe,"
12"He followed her inside, closing"
13"He stepped closer, his cane"
14"She turned her back to"
15"His voice was closer now,"
16"She could feel the heat"
17"She spun around, the takeaway"
18"His gaze darkened, and for"
19"She glanced down at the"
ratio0.655
14.55% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount49
totalSentences55
matches
0"The knock at the door"
1"Rory froze mid-step, takeaway bag"
2"She set the bag on"
3"Her breath hitched."
4"She unlocked the three deadbolts"
5"His voice was smooth, low,"
6"He stood in the hallway,"
7"His heterochromatic eyes—one amber, one"
8"She crossed her arms, leaning"
9"Her tone was sharper than"
10"His gaze flicked over her"
11"She shrugged, feigning nonchalance"
12"His lips thinned, a flicker"
13"She pushed off the doorframe,"
14"He followed her inside, closing"
15"The click of the latch"
16"Ptolemy, Eva’s tabby cat, darted"
17"Rory leaned against the kitchen"
18"The scent of curry from"
19"He stepped closer, his cane"
ratio0.891
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences55
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences32
technicalSentenceCount1
matches
0"His heterochromatic eyes—one amber, one black—locked onto hers with an intensity that made her stomach twist."
86.54% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags13
uselessAdditionCount1
matches
0"He stepped, his cane tapping softly against the floor"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
79.3622%