Run: 2026-07-25-01KYCW17AH23QHGB8YRDHMPB2H

Run Details

Duration:
6.2s
Cost:
$0.003052
Provider:
Google AI Studio

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
Green neon hummed against the damp Soho brickwork. Inside The Raven's Nest, mahogany tables absorbed the amber wash of overhead lamps. Maps crinkled behind glass frames while old photographs of men in trench coats dissolved into the gloom. Silas wiped a tumbler with a grey linen cloth. His left leg dragged three inches shorter than the other as he shifted weight toward the register. A silver signet ring tapped against the polished counter. Aurora pushed through the door, breath pluming in the draft. Straight black hair brushed the collar of her worn leather jacket. She unzipped the canvas delivery bag, dropping it onto the nearest stool. Bright blue eyes scanned the empty booths before landing on the bartender. The delivery route ran late tonight. Traffic stalled near Oxford Circus, and the cold bit through denim. Glass squeaked under the linen. Silas did not look up immediately. He set the tumbler beside a row of identical bottles. Ten pounds for the pad Thai and spring rolls. Yu-Fei expects the receipt back by midnight. Silas rested his palms on the dark wood. Hazel eyes narrowed past the reading glasses perched on the bridge of his nose. Grey-streaked auburn hair caught the amber glow from the pendant lamp above the taps. You trade pre-law textbooks for grease-stained bags now. Aurora pulled a crumpled slip of paper from her pocket and dropped it onto the counter. Her left thumb traced the small crescent-shaped scar across her wrist, pressing hard enough to turn the skin white. Cardiff courtrooms lost their appeal. A heavy oak door swung open from the back alley, admitting a blast of London grit and an unfamiliar figure. The man wore a sharply tailored charcoal overcoat that smelled faintly of dry cleaning and expensive cologne. Broad shoulders filled the frame of the doorway. He paused, scanning the dim interior with dark, assessing eyes. Julian. The name slipped from Aurora’s lips like cold ash. Her hand froze over her wrist. The easy posture vanished, replaced by the rigid stillness of a trapped animal. Julian stopped five paces from the bar. His gaze locked onto Aurora, sweeping down the length of her delivery jacket and the battered canvas bag. A thin smile touched the corners of his mouth. Small city. Aurora did not blink. Her fingers curled into the denim of her thigh. You lost your address six years ago. Julian stepped closer, the heels of his leather shoes clicking sharply against the floorboards. He shed no coat, carrying the chill of the street inside with him. Oxford lost a promising mind. Your father still asks if you visit the firm on weekends. Aurora’s jaw tightened. A muscle jumped beneath her left cheekbone. Brendan reads the law reports to an empty room. Tell him to buy a radio. Julian’s smile tightened into a flat line. He reached out, his manicured fingers hovering an inch from her shoulder before dropping back to his side. Evan still lives off your mother’s sympathy. He mentions the wedding occasionally. Wondering if you ever found your spine in London. Silence swallowed the hum of the neon sign outside. Silas stopped wiping the glass. He leaned his hip against the back bar, his right hand resting casually near the brass service bell, though his hazel eyes hardened into flint. The girl takes her orders from the kitchen across the street, not from men who wander into private establishments uninvited. Julian turned his head slowly, fixing Silas with a cold, superior look. He did not acknowledge the grey-streaked hair or the slight hitch in the bartender's posture. This concerns family matters. Stay behind your taps, old man. Silas didn't blink. The silver signet ring caught the amber light as he curled his fingers into a fist. This door opens to the public, but it closes on trespassers. Aurora stared at the grain of the wooden counter, her reflection warped in the dark varnish. The distance between the girl who fled Cardiff and the woman standing in Soho stretched across the floorboards like a chasm. She left Cardiff with a bruised jaw and a suitcase packed in the dark. Eva bought the ticket. Silas gave her the flat upstairs three months later when the money ran out and the deliveries started. Julian stepped closer, invading her space with the suffocating scent of his cologne. Come back before the winter breaks. Brendan’s health fails him. You owe them that much at least. Aurora lifted her chin. The bright blue of her eyes burned into his. I owe Cardiff nothing. Julian let out a dry, breathy laugh. He turned on his heel, his overcoat swirling around his shins. The door chimed once as he pushed back out into the damp street. The neon sign buzzed louder, rattling its housing against the brick. Silas poured two fingers of amber whiskey into a short glass and slid it across the wood without a word. Aurora looked down at the liquor. She didn't touch it. Her fingers returned to the crescent scar on her wrist, pressing until the pain cut through the cold numbness in her chest.
created_at"2026-07-25T14:49:25.085Z" 7/25/2026, 2:49:25 PM
model"google/gemini-3.5-flash-lite-20260721"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency301
moderation_latency(null)
generation_time6070
tokens_prompt1063
tokens_completion1287
native_tokens_prompt1032
native_tokens_completion1097
native_tokens_completion_images0
native_tokens_reasoning0
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"STOP"
service_tier"default"
usage0.0030521
router(null)
provider_responses
0
endpoint_id"6bd8f433-79e1-416c-b407-1772eb796c9a"
id"9cxkas6DD6zi_uMP5OfjkAE"
is_byokfalse
latency301
model_permaslug"google/gemini-3.5-flash-lite-20260721"
provider_name"Google AI Studio"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1784990965-DEUx4BhLuzXg90FEnoSs"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784990965-bAVRAaxJSYq03DrCmt7H"
upstream_id"9cxkas6DD6zi_uMP5OfjkAE"
total_cost0.0030521
cache_discount(null)
upstream_inference_cost0
provider_name"Google AI Studio"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags0
82.35% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount850
totalAiIsmAdverbs3
found
0
adverb"sharply"
count2
1
adverb"slowly"
count1
highlights
0"sharply"
1"slowly"
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)
58.82% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount850
totalAiIsms7
found
0
word"gloom"
count1
1
word"weight"
count1
2
word"scanned"
count1
3
word"traced"
count1
4
word"scanning"
count1
5
word"chill"
count1
6
word"silence"
count1
highlights
0"gloom"
1"weight"
2"scanned"
3"traced"
4"scanning"
5"chill"
6"silence"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences83
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences83
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences83
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen25
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords850
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
97.06% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions41
wordCount850
uniqueNames12
maxNameDensity1.06
worstName"Aurora"
maxWindowNameDensity2
worstWindowName"Aurora"
discoveredNames
Soho2
Raven1
Nest1
Oxford2
Circus1
Thai1
London2
Aurora9
Silas8
Cardiff4
You3
Julian7
persons
0"Aurora"
1"Silas"
2"You"
3"Julian"
places
0"Soho"
1"Raven"
2"Oxford"
3"London"
4"Cardiff"
globalScore0.971
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences67
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount850
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences83
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs39
mean21.79
std12.78
cv0.587
sampleLengths
038
135
245
317
421
516
636
78
835
95
1055
111
1228
1334
142
1513
167
1727
1816
1910
2015
2125
2221
2339
2420
2527
2610
2719
2811
2937
3036
3113
3217
3313
344
3531
3611
3720
3832
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences83
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs128
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences83
ratio0
matches(empty)
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount855
adjectiveStacks1
stackExamples
0"small crescent-shaped scar"
adverbCount16
adverbRatio0.01871345029239766
lyAdverbCount8
lyAdverbRatio0.00935672514619883
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences83
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences83
mean10.24
std5.26
cv0.513
sampleLengths
08
113
217
39
417
59
610
711
812
912
106
1111
125
136
1410
159
167
178
1814
1914
208
2116
2219
235
2420
2517
268
2710
281
299
306
3113
327
3318
349
352
364
379
387
3914
4013
415
4211
433
447
459
466
477
4818
497
71.08% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.43373493975903615
totalSentences83
uniqueOpeners36
41.15% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences81
matches
0"Bright blue eyes scanned the"
ratio0.012
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount22
totalSentences81
matches
0"His left leg dragged three"
1"She unzipped the canvas delivery"
2"He set the tumbler beside"
3"You trade pre-law textbooks for"
4"Her left thumb traced the"
5"He paused, scanning the dim"
6"Her hand froze over her"
7"His gaze locked onto Aurora,"
8"Her fingers curled into the"
9"You lost your address six"
10"He shed no coat, carrying"
11"Your father still asks if"
12"He reached out, his manicured"
13"He mentions the wedding occasionally."
14"He leaned his hip against"
15"He did not acknowledge the"
16"She left Cardiff with a"
17"You owe them that much"
18"I owe Cardiff nothing."
19"He turned on his heel,"
ratio0.272
27.90% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount70
totalSentences81
matches
0"Maps crinkled behind glass frames"
1"Silas wiped a tumbler with"
2"His left leg dragged three"
3"A silver signet ring tapped"
4"Aurora pushed through the door,"
5"She unzipped the canvas delivery"
6"The delivery route ran late"
7"Traffic stalled near Oxford Circus,"
8"Glass squeaked under the linen."
9"Silas did not look up"
10"He set the tumbler beside"
11"Yu-Fei expects the receipt back"
12"Silas rested his palms on"
13"Hazel eyes narrowed past the"
14"You trade pre-law textbooks for"
15"Aurora pulled a crumpled slip"
16"Her left thumb traced the"
17"Cardiff courtrooms lost their appeal."
18"A heavy oak door swung"
19"The man wore a sharply"
ratio0.864
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences81
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences38
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
89.0791%