Run: 2026-02-20-01KHY8T78501R38N7EW4T5R92W

Run Details

Duration:
41.8s
Cost:
$0.000303
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="4413" name="Silas Blackwood" aliases="Silas, Si, the Spymaster" pronouns="he/him" species="Human" storyRole="Mentor"> <eyeColor>hazel</eyeColor> <hair>grey-streaked auburn</hair> <height>6'1"</height> <age>58</age> <beard>neatly trimmed, matching his grey-streaked auburn hair</beard> <limp>slight limp in his left leg from an old knee injury</limp> <signetRing>silver signet ring, always worn on his right hand</signetRing> <description>Silas is a retired intelligence operative turned bar owner. He carries himself with quiet authority.</description> <backstory>Former MI6 field agent who retired after a botched operation in Prague left him with a permanent knee injury. He opened "The Raven's Nest" bar in Soho as a front for his network of contacts.</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> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the literary fiction genre. Two old friends who haven't seen each other in years run into each other unexpectedly at a bar. One of them has changed significantly. Through their conversation and the tension between who they were and who they've become, reveal the weight of time and unspoken regret. 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 green neon of The Raven’s Nest bled onto the slick pavement outside. Rain plastered strands of Aurora's hair to her cheeks as she wrestled a delivery bag from her bike, the scent of orange chicken and sweet chili sauce battling the city’s grime. A Tuesday night, nearing ten. Usually a slow bleed of regulars, a handful of tourists, perhaps a lost soul seeking temporary solace. She shook the water from her jacket, pushing the door open to the warm, smoky air. Silas was polishing glasses, a slow, deliberate motion. The bar smelled of stale beer and something like woodsmoke and regret. “Rough night?” Silas asked, not looking up. “You know it.” She tossed her keys onto the bar, the chime a familiar sound. “Yu-Fei's got me running all over for a double order to some hotel in Mayfair. Feels like half the city is hiding from the weather.” Silas finally met her gaze, a flicker of something unreadable in his hazel eyes. “Weather’s a good excuse for most things.” He slid a damp cloth across the polished wood. “The usual?” “Please.” He poured her a whiskey, neat. She took a sip, the burn a welcome counterpoint to the chill. The bar wasn't crowded. Old Man Hemmings occupied his corner booth, nursing a pint and staring into the middle distance. A couple huddled near the fireplace, speaking in hushed tones. Then she saw him. Leaning against the bar, halfway between the entrance and Silas, was a man who looked… familiar, but wrong. The suit was tailored, expensive. Hair, once a riot of dark curls, was now cropped short, silver threading through the black. He’d filled out, softened around the edges. But it was the eyes that held her captive. Still the same intense, captivating green, but dulled, shadowed. “Well, well,” the man said, his voice a low rasp. He didn’t bother to turn and face her. “If it isn’t Aurora Carter. Or should I say, Malphora?” The name hung in the air, a shard of broken glass. She hadn’t heard it in years. Not since… She set her glass down with a thud. "Evan?" He finally turned, a slow, deliberate movement. A ghost of a smile touched his lips. It didn’t reach his eyes. “The one and only. Though I’ve been going by Edward for a while now.” “Edward.” She tested the name, the way it felt foreign on her tongue. “Right.” “You haven't changed much,” he observed, his gaze sweeping over her, lingering for a beat too long on the crescent-shaped scar on her wrist. “Still rocking the black. Still looking like you’re about to solve a crime.” “Just delivering dinner.” She managed a tight smile. “And I’d rather not discuss my fashion choices with the man who once suggested I dye my hair blonde.” He chuckled, a dry, brittle sound. “A long time ago. Different man, Aurora.” “Is that what you are?” “What do you think?” He flagged down Silas, requesting a scotch. “I'm a solicitor now, for god’s sake. Dealing with mergers and acquisitions rather than… other things.” “Other things.” She mirrored his tone. The memory of those “other things” felt like a bruise deep beneath her skin. A network of shady dealings, quick money, and a constant state of anxiety. And him, at the center of it all, radiating a dangerous charisma. “Heard you stayed in London.” He took a sip of his scotch, watching her over the rim of the glass. “Silas ever mention me?” “Silas has a lot of customers, Evan. Or Edward. Whatever you're calling yourself these days.” “Came across your name in a case file, actually.” He paused. “Small world.” “What kind of case file?” He shrugged, dismissing her question with a wave of his hand. “Corporate espionage. Nothing exciting. Though it did remind me of… old times.” "Funny how those ‘old times’ conveniently vanish when you’re building a respectable life.” His jaw tightened. “Respectable is a strong word.” “Is it?” She leaned closer, her voice barely a whisper. “You’re wearing a Savile Row suit, calling yourself Edward, and pretending to be a pillar of society. Sounds pretty respectable to me." “People change, Aurora.” “Do they?” She traced the rim of her glass. “Or do they just become better at hiding?” The silence stretched, punctuated only by the clinking of glasses and the murmur of conversation. Silas, seemingly oblivious, continued to polish glasses, though Aurora was sure he’d heard every word. “I could ask about Eva.” He said it casually, like he was discussing the weather. “Is she still…?” “Don’t.” The word was sharp, a warning. Eva was the one constant in her life, the reason she’d even moved to London. Talking about her with him felt like a betrayal. “She's doing well. She doesn’t need you bringing up the past.” “Just curious.” He raised his hands in mock surrender. “I always did have a soft spot for Eva. She was the smart one, wasn't she? The one who saw through all my…charm.” “She saw what you were.” That was all she’d say. He swallowed the rest of his scotch. “Look, Aurora. I get it. You’re angry. You have every right to be. But a lot of water has passed under the bridge.” “Some things you can’t just wash away with time, Evan.” “Edward.” He corrected her, his voice laced with irritation. “Doesn't matter.” She stood up, reaching for her bag. "Enjoy your scotch, Edward. I have actual work to do.” “Leaving so soon?” He didn’t try to stop her. Just watched her, his expression unreadable. “I don’t have time for nostalgia trips.” She paused, her hand on the door handle. “Or for ghosts.” “We all have ghosts, Aurora.” She didn't respond. Didn’t look back. Pushed through the door and into the rain-washed night.
created_at"2026-02-20T19:35:48.751Z" 2/20/2026, 7:35:48 PM
model"google/gemma-3-27b-it"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency487
moderation_latency(null)
generation_time41637
tokens_prompt1117
tokens_completion1558
native_tokens_prompt1039
native_tokens_completion1372
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"
usage0.00030264
router(null)
provider_responses
0
endpoint_id"8f22002c-c045-446f-a1b9-9896133536b8"
id"chatcmpl-RcnrK69SV0UxeYCzS2L8rlBQ"
is_byokfalse
latency49
model_permaslug"google/gemma-3-27b-it"
provider_name"DeepInfra"
status200
api_type"completions"
id"gen-1771616148-rDwhYdjFFWkBmHCf4Lc1"
upstream_id"chatcmpl-RcnrK69SV0UxeYCzS2L8rlBQ"
total_cost0.00030264
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
totalTags20
adverbTagCount0
adverbTags(empty)
dialogueSentences52
tagDensity0.385
leniency0.769
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount964
totalAiIsmAdverbs0
found(empty)
highlights(empty)
100.00% AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0"Blackwood"
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
42.95% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount964
totalAiIsms11
found
0
word"solace"
count1
1
word"familiar"
count2
2
word"flicker"
count1
3
word"unreadable"
count2
4
word"chill"
count1
5
word"whisper"
count1
6
word"traced"
count1
7
word"silence"
count1
8
word"charm"
count1
highlights
0"solace"
1"familiar"
2"flicker"
3"unreadable"
4"chill"
5"whisper"
6"traced"
7"silence"
8"charm"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"hung in the air"
count1
highlights
0"hung in the air"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences65
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences65
filterMatches(empty)
hedgeMatches
0"try to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences95
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen31
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords962
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions13
unquotedAttributions0
matches(empty)
99.75% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions15
wordCount597
uniqueNames9
maxNameDensity1.01
worstName"Silas"
maxWindowNameDensity2
worstWindowName"Silas"
discoveredNames
Raven1
Nest1
Aurora2
Tuesday1
Silas6
Man1
Hemmings1
Eva1
London1
persons
0"Raven"
1"Nest"
2"Aurora"
3"Silas"
4"Man"
5"Hemmings"
6"Eva"
places
0"London"
globalScore0.997
windowScore1
0.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences50
glossingSentenceCount4
matches
0"something like woodsmoke and regret"
1"felt like a bruise deep beneath her ski"
2"Silas, seemingly oblivious, continue"
3"felt like a betrayal"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount962
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences95
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs42
mean22.9
std15.54
cv0.679
sampleLengths
066
136
27
340
432
51
652
764
828
919
109
1134
1214
1337
1427
1513
165
1727
1845
1924
2015
2113
225
2323
2413
258
2632
273
2817
2930
3018
3142
3232
3310
3430
3510
369
3719
3815
3918
405
4115
99.87% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences65
matches
0"was tailored"
61.11% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs96
matches
0"was polishing"
1"was discussing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences95
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount599
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.03005008347245409
lyAdverbCount7
lyAdverbRatio0.011686143572621035
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences95
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences95
mean10.13
std5.89
cv0.582
sampleLengths
013
131
25
317
416
58
612
77
815
925
1014
1116
122
131
146
1512
164
1716
1810
194
2015
213
225
2316
247
259
269
2710
288
2910
3011
316
322
338
341
357
368
375
3814
3913
401
4124
4213
438
4419
456
467
475
4811
4916
91.93% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.5578947368421052
totalSentences95
uniqueOpeners53
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences63
matches
0"Usually a slow bleed of"
1"Then she saw him."
2"Just watched her, his expression"
ratio0.048
29.52% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount30
totalSentences63
matches
0"She shook the water from"
1"She tossed her keys onto"
2"He slid a damp cloth"
3"He poured her a whiskey,"
4"She took a sip, the"
5"He’d filled out, softened around"
6"He didn’t bother to turn"
7"She hadn’t heard it in"
8"She set her glass down"
9"He finally turned, a slow,"
10"It didn’t reach his eyes."
11"She tested the name, the"
12"he observed, his gaze sweeping"
13"She managed a tight smile"
14"He chuckled, a dry, brittle"
15"He flagged down Silas, requesting"
16"She mirrored his tone"
17"He took a sip of"
18"He shrugged, dismissing her question"
19"His jaw tightened."
ratio0.476
55.24% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount51
totalSentences63
matches
0"The green neon of The"
1"Rain plastered strands of Aurora's"
2"A Tuesday night, nearing ten."
3"She shook the water from"
4"Silas was polishing glasses, a"
5"The bar smelled of stale"
6"Silas asked, not looking up"
7"She tossed her keys onto"
8"Silas finally met her gaze,"
9"He slid a damp cloth"
10"He poured her a whiskey,"
11"She took a sip, the"
12"The bar wasn't crowded."
13"A couple huddled near the"
14"The suit was tailored, expensive."
15"Hair, once a riot of"
16"He’d filled out, softened around"
17"the man said, his voice"
18"He didn’t bother to turn"
19"The name hung in the"
ratio0.81
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences63
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences19
technicalSentenceCount0
matches(empty)
50.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags20
uselessAdditionCount3
matches
0"Silas asked, not looking up"
1"the man said, his voice a low rasp"
2"She leaned, her voice barely a whisper"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount2
fancyTags
0"he observed (observe)"
1"He corrected (correct)"
dialogueSentences52
tagDensity0.096
leniency0.192
rawRatio0.4
effectiveRatio0.077
84.3454%