Run: 2026-02-25-01KJBKRR18JA2HZ6XD4A1XR646

Run Details

Duration:
1m 51s
Cost:
$0.003187
Provider:
Alibaba

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
Rain hammered the pavement outside, blurring the distinctive green neon sign above the entrance into the Raven’s Nest. Inside, the air smelled of stale ale, polished oak, and old paper maps. Silas stood behind the bar with a rag in hand, wiping a glass he’d washed three minutes ago. His left leg dragged slightly, a ghost of a limp from the Prague operation ten years back. He paused, watching the condensation slide down the bottle in his hand. The bell above the door chimed. Silence filled the room, heavy and immediate. Even the low buzz of the fridge seemed to drop a decibel. Silas didn’t look up. He finished the wipe and set the glass down. “Rory,” he said. His voice was a low rumble, gravelly with age. “I didn’t think you’d be back yet.” Aurora pulled her wet coat tighter around her shoulders. She stood in the doorway, rain dripping from the hem onto the scuffed floorboards. Her hair, straight and shoulder-length black, was damp and stuck to her cheeks. Her bright blue eyes scanned the dim room, landing finally on him. She looked older. Thinner. “I wasn’t sure I’d have to be,” she replied. Her voice held an edge she hadn’t used when she arrived in London four years ago. She stepped further in, water leaving tracks on the floorboards that led to the bar. Silas nodded toward the stool near the back. The stool was the one he’d saved for her, even though she hadn’t sat on it in three years. She climbed it, the wood creaking under her weight. “You’ve got a scar,” Silas said. He pointed a calloused finger at her left wrist. Aurora raised her arm, turning the pale skin to the light. A crescent mark, white against blue vein. “Childhood accident. I cut it deep.” Silas stopped wiping. He looked at the wrist, then her face. “You don’t look like a student anymore.” “Pre-law is a memory. I haven’t worn a blazer in a year.” She rested her forearms on the bar, her head resting in her palms. The neon sign reflected in her eyes, casting a green shadow over her dark features. “How long has the sign been flickering?” “Since the fuse blew in June. I keep meaning to get to it.” He moved to the side, reaching for a fresh towel. His knee clicked audibly. “Why Cardiff? We talked about London only. You ran here.” “I ran back.” She lifted her head. The corners of her mouth twitched, a failed attempt at a smile. “I needed to see the ground where the roots were before I could cut them up here.” Silas leaned against the counter. He didn’t pour a drink. He couldn’t stop thinking about the papers she’d left behind, the ones hidden under the floorboards of her flat three stories above. He walked to the shelf behind him. Maps covered the wall, pins marking locations that didn’t exist on civilian charts. He picked up a bottle of whiskey, the amber liquid catching the dim light. “Drinking already?” “I’m not drinking. I’m smelling it.” She sniffed the air over the glass he poured, filling it halfway. She didn’t drink. “Evan found you eventually?” “No.” Her jaw tightened. “He died.” Silas froze. The bottle remained in his hand. “How?” “Cancer. Stomach.” She watched him over the rim of the glass. “Not the way I left it.” Silas placed the bottle down on the counter with a solid thud. The liquid inside disturbed the residue of foam. “You didn’t come to mourn.” “No. I came to hide.” She pushed the glass toward him, sliding it back with the tip of her finger. “There’s nowhere to run anymore.” The silence stretched between them, measuring the distance of years. The air in the bar felt thick, loaded with the weight of everything they hadn’t said. Silas looked at Aurora, really looked at her. He saw the way her black hair fell over one shoulder, the way her shoulders hunched slightly to the right, not from fear but from weight. She was carrying things he couldn’t see. “Brendan’s dead too.” Aurora winced. She gripped the edge of the bar until her knuckles turned white. Her father. The Irish barrister who always pushed her toward the law. “Jennifer is in the nursing home,” she whispered. Silas nodded. He knew the rhythm of her family, the cadence of their tragedies. He stepped out from behind the bar, the slight limp in his leg becoming more pronounced as he moved. He walked around the front counter, his hazel eyes fixed on the small scar on her wrist. “Why here?” he asked. He stood close enough that she could smell the tobacco on his coat. “You live upstairs.” “I *lived* upstairs. I moved out. Three months ago.” She looked down at the bar top. “I thought if I kept walking, it wouldn’t catch me. But the stairs were the limit. The flat was empty now.” Silas placed a hand on the bar beside her head, blocking her path. “You want a room?” “No. I want a bed. Somewhere I don’t have to explain.” He watched her. She was the kid who stole his wine glasses, who asked too many questions about his old cases. She was the student who refused to be told what to do. Now she was a woman with nothing left to steal. “Yu-Fei Cheung needs a runner. The delivery job is available if you want it.” He paused. “I don’t ask anything about the job.” She didn’t answer immediately. She stared at the green sign outside, where the rain blurred the letters until they looked almost like tears. “No. I need a place, Silas. Just tonight. The rain... it stops.” Silas nodded. He turned back to the bar and reached under the counter. He produced a heavy iron key, the teeth worn smooth from years of use. He dropped it onto the blotter paper in front of her. “The flat above is yours for as long as you need it. If you leave, leave the key.” She grabbed the key. Her fingers trembled slightly before she stilled them. She tucked it into her pocket. “I’ll fix the fuse.” “I’ll fix the fuse myself. You just sleep.” He walked back around the bar, turning his attention to the whiskey bottle again. “Don’t wake me at 4 AM.” Aurora pushed the glass away. It clinked against the wood. “I’m not the one who stays up, Silas. I know that.” “I know.” He didn’t turn around. He watched his own hand steady the bottle. “Drink the whiskey.” She didn’t drink. She just watched the liquid sit there, still and dark. Her eyes were bright blue, reflecting the neon light one last time before she turned away from him.
created_at"2026-02-25T23:58:09.657Z" 2/25/2026, 11:58:09 PM
model"qwen/qwen3.5-flash-20260224"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency478
moderation_latency(null)
generation_time63697
tokens_prompt1094
tokens_completion7884
native_tokens_prompt1061
native_tokens_completion7702
native_tokens_completion_images(null)
native_tokens_reasoning6185
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"
usage0.0031869
router(null)
provider_responses
0
endpoint_id"5f6b71b5-8672-4b27-8b2d-f674429f9e63"
id"chatcmpl-a6890278-ba2f-99a2-820b-b01b72baa203"
is_byokfalse
latency478
model_permaslug"qwen/qwen3.5-flash-20260224"
provider_name"Alibaba"
status200
api_type"completions"
id"gen-1772063889-zo8jN85CGy6b2H4Zo0sV"
upstream_id"chatcmpl-a6890278-ba2f-99a2-820b-b01b72baa203"
total_cost0.0031869
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
totalTags16
adverbTagCount1
adverbTags
0"He walked back [back]"
dialogueSentences41
tagDensity0.39
leniency0.78
rawRatio0.063
effectiveRatio0.049
82.30% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1130
totalAiIsmAdverbs4
found
0
adverb"slightly"
count3
1
adverb"really"
count1
highlights
0"slightly"
1"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)
64.60% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1130
totalAiIsms8
found
0
word"silence"
count2
1
word"scanned"
count1
2
word"weight"
count3
3
word"stomach"
count1
4
word"trembled"
count1
highlights
0"silence"
1"scanned"
2"weight"
3"stomach"
4"trembled"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"knuckles turned white"
count1
highlights
0"knuckles turned white"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences91
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences91
filterMatches(empty)
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences116
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen26
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords1130
ratio0.001
matches
0"lived"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions10
unquotedAttributions0
matches(empty)
79.66% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions22
wordCount853
uniqueNames7
maxNameDensity1.41
worstName"Silas"
maxWindowNameDensity2.5
worstWindowName"Silas"
discoveredNames
Raven1
Nest1
Prague1
London1
Silas12
Aurora5
Irish1
persons
0"Silas"
1"Aurora"
places
0"Raven"
1"Prague"
2"London"
globalScore0.797
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences63
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.885
wordCount1130
matches
0"not from fear but from weight"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences116
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs42
mean26.9
std17.55
cv0.652
sampleLengths
078
125
213
319
452
525
651
715
824
918
1047
1137
1236
1366
142
1521
164
176
189
1917
2025
2125
2267
233
2426
258
2650
2720
2837
2917
3011
3143
3223
3323
3412
3538
3618
3722
3828
3921
4017
4131
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences91
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs155
matches
0"was carrying"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences116
ratio0
matches(empty)
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount854
adjectiveStacks1
stackExamples
0"white against blue vein."
adverbCount27
adverbRatio0.03161592505854801
lyAdverbCount9
lyAdverbRatio0.01053864168618267
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences116
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences116
mean9.74
std5.89
cv0.604
sampleLengths
018
113
218
317
412
56
67
712
84
99
103
119
127
139
1414
1513
1612
173
181
199
2016
2115
228
2319
249
256
269
2711
287
296
303
318
327
3325
3415
357
3623
374
3810
397
4012
4117
425
435
4422
457
4613
4714
482
4918
38.22% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats14
diversityRatio0.3017241379310345
totalSentences116
uniqueOpeners35
42.19% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences79
matches
0"Even the low buzz of"
ratio0.013
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount52
totalSentences79
matches
0"His left leg dragged slightly,"
1"He paused, watching the condensation"
2"He finished the wipe and"
3"His voice was a low"
4"She stood in the doorway,"
5"Her hair, straight and shoulder-length"
6"Her bright blue eyes scanned"
7"She looked older."
8"Her voice held an edge"
9"She stepped further in, water"
10"She climbed it, the wood"
11"He pointed a calloused finger"
12"He looked at the wrist,"
13"She rested her forearms on"
14"He moved to the side,"
15"His knee clicked audibly."
16"She lifted her head"
17"He didn’t pour a drink."
18"He couldn’t stop thinking about"
19"He walked to the shelf"
ratio0.658
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount75
totalSentences79
matches
0"Silas stood behind the bar"
1"His left leg dragged slightly,"
2"He paused, watching the condensation"
3"The bell above the door"
4"Silence filled the room, heavy"
5"Silas didn’t look up."
6"He finished the wipe and"
7"His voice was a low"
8"Aurora pulled her wet coat"
9"She stood in the doorway,"
10"Her hair, straight and shoulder-length"
11"Her bright blue eyes scanned"
12"She looked older."
13"Her voice held an edge"
14"She stepped further in, water"
15"Silas nodded toward the stool"
16"The stool was the one"
17"She climbed it, the wood"
18"He pointed a calloused finger"
19"Aurora raised her arm, turning"
ratio0.949
63.29% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences79
matches
0"Now she was a woman"
ratio0.013
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences38
technicalSentenceCount2
matches
0"Maps covered the wall, pins marking locations that didn’t exist on civilian charts."
1"She was the kid who stole his wine glasses, who asked too many questions about his old cases."
93.75% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags16
uselessAdditionCount1
matches
0"She rested, her head resting in her palms"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags6
fancyCount2
fancyTags
0"She sniffed (sniff)"
1"she whispered (whisper)"
dialogueSentences41
tagDensity0.146
leniency0.293
rawRatio0.333
effectiveRatio0.098
85.2672%