Run: 2026-02-25-01KJBJRYA8M69B4J8CHJXF6KTB

Run Details

Duration:
54.2s
Cost:
$0.010903
Provider:
Alibaba

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
The rain in Soho had a way of turning the pavement into a black mirror, reflecting the neon bleed of the city. Aurora pulled her collar up against the damp chill, the weight of the delivery bag still heavy on her shoulder from the last drop at the Golden Empress. She didn't want to go up to the flat yet. The silence of the room above the bar was too loud after the noise of the streets. Instead, she pushed through the heavy wooden door of The Raven's Nest. The air inside was thick with the smell of old wood, polished brass, and gin. It was a sanctuary of shadows, illuminated only by the amber glow of low-hanging lamps and the distinctive green neon sign that buzzed softly above the entrance, casting a sickly emerald tint over the bar top. The walls were a collage of her landlord’s past, covered with old maps and black-and-white photographs of places she had only ever seen in textbooks. Prague. Berlin. Cairo. Places where Silas had bled before he retired to this corner of London. She moved toward the bar, her boots clicking softly on the floorboards. She was twenty-five, but the line of her jaw felt harder than it had in Cardiff. Her straight shoulder-length black hair was tucked behind her ears, framing a face that had learned to keep its expressions neutral. As she reached the counter, she caught her reflection in the polished mirror behind the bottles. The small crescent-shaped scar on her left wrist stood out against her pale skin, a white reminder of a childhood accident that felt trivial compared to the things she had survived since. Then she saw him. He was sitting at a small table near the back, half-hidden by the shadows of a potted fern. He was wearing a suit that cost more than her annual salary, but it hung on him like a shroud. It was Julian. They had sat in the same Pre-Law lectures at Cardiff University, sharing notes and cheap wine, dreaming of the Bar. He had been the one who told her she was too sharp for the courtroom, too volatile for the system. He had been the one who stayed. Julian looked up as the door opened, and his eyes widened. He looked older than his thirty years. The dark circles under his eyes were bruised purple, and his hair, once thick and chestnut, was thinning at the temples. He had changed significantly. The ambition that used to burn in his posture was gone, replaced by a hollow exhaustion. Aurora hesitated, her hand resting on the scarred wrist. She could walk away. She could go upstairs and lock the door. But she stepped forward, the movement fluid and quiet. Julian stood up too quickly, knocking his elbow against the table. A glass clinked. Rory, he said. The name sounded foreign in his mouth. He hadn't called her that since she left. Julian, she replied. Her voice was steady, cool-headed, the way she had to be. Silas emerged from behind the bar, his slight limp in his left leg barely noticeable as he moved with a predator’s grace. He was a mountain of a man, his grey-streaked auburn beard neatly trimmed, his hazel eyes scanning the room with the practiced vigilance of a former field agent. He paused when he saw the two of them. He knew better than to interrupt the gravity of a reunion, but he placed a bottle of whiskey and two glasses on the bar, his silver signet ring catching the light on his right hand. Aurora nodded at him, a silent acknowledgment of the space he provided. Silas gave a barely perceptible dip of his head and retreated to the shadows of the back room, leaving them alone in the amber light. Julian sat back down, pulling a handkerchief from his pocket to wipe the condensation from his glass. I heard you were in London, he said. I didn't know you were... here. Delivery driver, Aurora said. She didn't offer more. It was the truth, and it was enough. He laughed, a dry, brittle sound. I remember you talking about the Bar. About making a name. Names don't pay the rent, she said. She pulled out the stool opposite him. The wood was worn smooth by decades of elbows. I made a name, Julian said. He gestured vaguely at his suit. I'm a senior associate at a firm in the City. But the name... it doesn't mean anything when you're sitting in a room like this at midnight. Aurora watched him. The tension in his shoulders was a physical weight. He looked like a man who had won the battle but lost the war. She thought of the flat above the bar, the silence, the freedom. She thought of Evan, and the way she had fled to London to escape the suffocation of a life that wasn't hers. She had lost her path, yes, but she had kept her breath. You look tired, Julian. I am. They sat in silence for a long moment. The hum of the neon sign filled the gap between them. On the wall behind him, a map of Prague was pinned next to a photograph of a bombed-out street. Silas’s life was written in ink and blood on those walls, a testament to the cost of duty. Julian’s life was written in contracts and bills, a testament to the cost of ambition. I should have called, Julian said finally. When you left. You didn't know where I was. I should have found you. Aurora looked down at her left wrist, tracing the curve of the scar with her thumb. She thought about the unspoken regret that hung in the air, heavier than the smoke that used to linger in this bar before they banned it. They were ghosts of who they used to be, haunting the space between the past and the present. I'm okay, Julian. She looked up, her bright blue eyes locking onto his. Really. He searched her face, looking for the girl who used to argue about case law until dawn. He didn't find her. He found a woman who had survived. I'm not, he whispered. Aurora reached for her glass. The whiskey burned as it went down, a familiar heat that settled in her chest. She knew she couldn't fix him. She knew she couldn't fix the time they had lost. But she could sit with him in the dim light of The Raven's Nest, in the quiet sanctuary Silas had built for broken people. Well, she said softly. You're not alone tonight. Julian nodded, the tension in his jaw easing just a fraction. He raised his glass. To the past. To the present, Aurora corrected. They drank. Outside, the rain continued to fall on Soho, washing the streets clean, while inside the bar, the old maps on the wall watched silently, keeping their secrets safe.
created_at"2026-02-25T23:40:00.206Z" 2/25/2026, 11:40:00 PM
model"qwen/qwen3.5-27b-20260224"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency760
moderation_latency(null)
generation_time53809
tokens_prompt867
tokens_completion4667
native_tokens_prompt865
native_tokens_completion4435
native_tokens_completion_images(null)
native_tokens_reasoning2975
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"
usage0.0109035
router(null)
provider_responses
0
endpoint_id"f3f88554-0c22-4d57-973b-0dec948808e8"
id"chatcmpl-2603703f-94de-9a46-b71d-d99238e2cb34"
is_byokfalse
latency760
model_permaslug"qwen/qwen3.5-27b-20260224"
provider_name"Alibaba"
status200
api_type"completions"
id"gen-1772062800-oZ6ptmYiHOWCN45lDstk"
upstream_id"chatcmpl-2603703f-94de-9a46-b71d-d99238e2cb34"
total_cost0.0109035
cache_discount(null)
upstream_inference_cost0
provider_name"Alibaba"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags0
78.43% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1159
totalAiIsmAdverbs5
found
0
adverb"softly"
count3
1
adverb"quickly"
count1
2
adverb"really"
count1
highlights
0"softly"
1"quickly"
2"really"
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)
22.35% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1159
totalAiIsms18
found
0
word"chill"
count1
1
word"weight"
count2
2
word"silence"
count3
3
word"sanctuary"
count2
4
word"reminder"
count1
5
word"predator"
count1
6
word"scanning"
count1
7
word"tension"
count2
8
word"testament"
count2
9
word"tracing"
count1
10
word"unspoken"
count1
11
word"familiar"
count1
highlights
0"chill"
1"weight"
2"silence"
3"sanctuary"
4"reminder"
5"predator"
6"scanning"
7"tension"
8"testament"
9"tracing"
10"unspoken"
11"familiar"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"eyes widened/narrowed"
count1
1
label"hung in the air"
count1
highlights
0"eyes widened"
1"hung in the air"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences104
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences104
filterMatches
0"look"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences104
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen37
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1159
ratio0
matches(empty)
0.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions8
matches
0"Rory, he said."
1"Julian, she replied."
2"I heard you were in London, he said."
3"Delivery driver, Aurora said."
4"I made a name, Julian said."
5"I should have called, Julian said finally."
6"Well, she said softly."
7"To the present, Aurora corrected."
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions48
wordCount1159
uniqueNames17
maxNameDensity0.95
worstName"Julian"
maxWindowNameDensity2
worstWindowName"Julian"
discoveredNames
Soho2
Golden1
Empress1
Raven2
Nest2
Silas5
London3
Cardiff2
Julian11
Pre-Law1
University1
Bar2
Aurora8
City1
Evan1
Prague2
You3
persons
0"Raven"
1"Silas"
2"Julian"
3"University"
4"Aurora"
5"Evan"
6"You"
places
0"Soho"
1"Golden"
2"London"
3"Cardiff"
4"Bar"
5"City"
6"Prague"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences72
glossingSentenceCount1
matches
0"looked like a man who had won the battle"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1159
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences104
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs33
mean35.12
std30.96
cv0.881
sampleLengths
089
192
297
34
488
559
630
714
818
914
1094
1137
1231
1316
1417
1523
1639
1772
184
192
2071
2110
226
235
2460
2514
2628
274
2860
298
3018
315
3230
88.39% Passive voice overuse
Target: ≤2% passive sentences
passiveCount5
totalSentences104
matches
0"was tucked"
1"was gone"
2"was pinned"
3"was written"
4"was written"
98.48% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs197
matches
0"was sitting"
1"was wearing"
2"was thinning"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences104
ratio0
matches(empty)
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1170
adjectiveStacks1
stackExamples
0"small crescent-shaped scar"
adverbCount31
adverbRatio0.026495726495726495
lyAdverbCount15
lyAdverbRatio0.01282051282051282
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences104
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences104
mean11.14
std8.14
cv0.73
sampleLengths
022
128
210
317
412
515
636
725
81
91
101
1113
1212
1316
1421
1516
1632
174
1818
1920
203
2120
2220
237
2411
257
2621
274
2816
299
304
318
329
3311
343
353
367
378
383
3911
4022
4128
429
4335
4412
4525
4617
478
485
491
37.50% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.2980769230769231
totalSentences104
uniqueOpeners31
68.73% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences97
matches
0"Instead, she pushed through the"
1"Then she saw him."
ratio0.021
5.57% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount52
totalSentences97
matches
0"She didn't want to go"
1"It was a sanctuary of"
2"She moved toward the bar,"
3"She was twenty-five, but the"
4"Her straight shoulder-length black hair"
5"He was sitting at a"
6"He was wearing a suit"
7"It was Julian."
8"They had sat in the"
9"He had been the one"
10"He had been the one"
11"He looked older than his"
12"He had changed significantly."
13"She could walk away."
14"She could go upstairs and"
15"He hadn't called her that"
16"Her voice was steady, cool-headed,"
17"He was a mountain of"
18"He paused when he saw"
19"He knew better than to"
ratio0.536
27.01% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount84
totalSentences97
matches
0"The rain in Soho had"
1"Aurora pulled her collar up"
2"She didn't want to go"
3"The silence of the room"
4"The air inside was thick"
5"It was a sanctuary of"
6"The walls were a collage"
7"Places where Silas had bled"
8"She moved toward the bar,"
9"She was twenty-five, but the"
10"Her straight shoulder-length black hair"
11"The small crescent-shaped scar on"
12"He was sitting at a"
13"He was wearing a suit"
14"It was Julian."
15"They had sat in the"
16"He had been the one"
17"He had been the one"
18"Julian looked up as the"
19"He looked older than his"
ratio0.866
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences97
matches
0"To the past."
1"To the present, Aurora corrected."
ratio0.021
99.13% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences49
technicalSentenceCount3
matches
0"It was a sanctuary of shadows, illuminated only by the amber glow of low-hanging lamps and the distinctive green neon sign that buzzed softly above the entrance…"
1"Her straight shoulder-length black hair was tucked behind her ears, framing a face that had learned to keep its expressions neutral."
2"The small crescent-shaped scar on her left wrist stood out against her pale skin, a white reminder of a childhood accident that felt trivial compared to the thi…"
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
82.8749%