Run: 2026-02-25-01KJBKDQ40JD5Z3SS0051T1MEM

Run Details

Duration:
4m 50s
Cost:
$0.104088
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
The green neon sign buzzed overhead, casting a sickly glow on the wet pavement of Soho. Rain slicked the cobblestones, reflecting the red and white lights of passing taxis. Aurora pushed the heavy oak door open and stepped inside. The air smelled of stale beer, lemon polish, and old paper. Maps covered the walls, pinned with black-and-white photographs of men in suits and women in hats. The bar was empty save for the man behind the counter. Silas stood with his back to the entrance, polishing a glass. His grey-streaked auburn hair caught the dim light. He wore a dark vest over a white shirt, the sleeves rolled up to reveal forearms thick with muscle and old scars. He set the glass down on the mahogany counter and turned. His hazel eyes locked onto hers. The limp in his left leg was more pronounced tonight, a slight drag as he shifted his weight. Aurora stopped. Her hand tightened on the strap of her bag. The scar on her left wrist, a small crescent shape, throbbed under the sleeve of her coat. She had not expected to see him here. She had not expected to see him at all. Silas leaned against the counter. He did not smile. You look older. Aurora pulled her coat tighter around her shoulders. The warmth of the bar hit her skin, raising goosebumps. So do you. Silas reached for a bottle of whiskey. He poured two fingers into a tumbler and pushed it toward her. Sit. Aurora moved to the stool closest to the end. She sat. Her boots clicked against the floorboards. She stared at the glass. The amber liquid swirled as the bar settled around them. I thought you left London. I did. When? Five years. Aurora lifted the glass. She took a sip. The burn went down her throat, settling in her chest. I heard you sold the place. I bought it back. She set the glass down. Her fingers traced the rim. Why? Silas picked up a rag and wiped a spot on the counter that was already clean. It pays the bills. You used to do more than that. Silas stopped wiping. He looked at her. His gaze was heavy, weighing her up and down. He saw the dark circles under her eyes. He saw the way she held herself, shoulders hunched, ready to run. And you? What brings you back to the Nest? I live above. Silas raised an eyebrow. He poured himself a drink. Since when? Since last month. He took a drink. The glass clinked against the counter. You didn't knock on the door. I didn't know you were here. Silas laughed. It was a dry sound, like leaves crunching underfoot. You live above me and you didn't know I was here? I didn't come down. Why? Aurora looked at the maps on the wall. A map of Prague hung near the ceiling. She remembered the stories he told her years ago. Stories about agents and dead drops and things that never made the news. I had things to deal with. Silas nodded. He set his glass down. He walked around the counter. His limp was visible now, a slight hitch in his step. He stopped in front of her. He looked at her left wrist. The scar was visible where her sleeve had pulled back. Evan? Aurora pulled her sleeve down. No. Then what? Silas waited. He did not press. He stood there, a solid wall of grey hair and quiet authority. It doesn't matter. It matters. Aurora stood up. She picked up her bag. The leather creaked in her hand. I just wanted a drink. Silas reached out. His hand hovered over hers. He did not touch her. You can stay. I can't. Why? Because I'm not ready. Silas stepped back. He nodded. Take your time. Aurora turned to the door. She pushed it open. The rain hit her face. The neon sign buzzed above her head. She stepped out into the night. Silas watched her go. He picked up the glass she had left behind. He set it in the sink. He turned off the lights. The bar went dark. The maps on the wall faded into the shadows. He walked to the back room. He opened the bookshelf. He stepped inside. He closed the door. The silence returned. The bar waited. The rain continued to fall.
created_at"2026-02-25T23:51:20.969Z" 2/25/2026, 11:51:20 PM
model"qwen/qwen3.5-122b-a10b-20260224"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency557
moderation_latency(null)
generation_time290029
tokens_prompt1094
tokens_completion28345
native_tokens_prompt1061
native_tokens_completion32395
native_tokens_completion_images(null)
native_tokens_reasoning31394
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"
usage0.1040884
router(null)
provider_responses
0
endpoint_id"33d466d1-d2f7-45ed-8ff3-fda7d2e32351"
id"chatcmpl-f299088e-0db7-9e27-ae9f-5bc27dd3ff1b"
is_byokfalse
latency556
model_permaslug"qwen/qwen3.5-122b-a10b-20260224"
provider_name"Alibaba"
status200
api_type"completions"
id"gen-1772063480-ObmClYXw7vO075xstyhX"
upstream_id"chatcmpl-f299088e-0db7-9e27-ae9f-5bc27dd3ff1b"
total_cost0.1040884
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
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount733
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)
59.07% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount733
totalAiIsms6
found
0
word"weight"
count1
1
word"throbbed"
count1
2
word"warmth"
count1
3
word"traced"
count1
4
word"eyebrow"
count1
5
word"silence"
count1
highlights
0"weight"
1"throbbed"
2"warmth"
3"traced"
4"eyebrow"
5"silence"
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
emotionTells0
narrationSentences120
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences120
filterMatches
0"look"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences120
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen22
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords733
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
68.14% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions30
wordCount733
uniqueNames7
maxNameDensity1.64
worstName"Silas"
maxWindowNameDensity2.5
worstWindowName"Silas"
discoveredNames
Soho1
London1
Nest1
Prague1
Aurora9
Silas12
You5
persons
0"Aurora"
1"Silas"
2"You"
places
0"Soho"
1"London"
2"Nest"
3"Prague"
globalScore0.681
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences53
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount733
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences120
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs55
mean13.33
std19.68
cv1.477
sampleLengths
077
176
245
39
43
518
63
719
81
932
105
112
121
132
1418
156
164
1710
181
1916
204
217
2236
239
243
259
262
273
2810
296
306
3111
3211
334
341
3538
366
3745
381
395
401
412
4218
433
442
4514
465
4713
483
492
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences120
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs147
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences120
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount736
adjectiveStacks0
stackExamples(empty)
adverbCount10
adverbRatio0.01358695652173913
lyAdverbCount1
lyAdverbRatio0.001358695652173913
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences120
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences120
mean6.11
std4.03
cv0.659
sampleLengths
016
113
210
311
416
511
611
78
822
911
106
1118
122
139
1417
158
169
175
184
193
208
2110
223
237
2412
251
269
272
286
295
3010
315
322
331
342
354
364
3710
386
394
405
415
421
4316
444
457
463
474
489
498
34.17% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats19
diversityRatio0.225
totalSentences120
uniqueOpeners27
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences100
matches(empty)
ratio0
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount56
totalSentences100
matches
0"His grey-streaked auburn hair caught"
1"He wore a dark vest"
2"He set the glass down"
3"His hazel eyes locked onto"
4"Her hand tightened on the"
5"She had not expected to"
6"She had not expected to"
7"He did not smile."
8"You look older."
9"He poured two fingers into"
10"Her boots clicked against the"
11"She stared at the glass."
12"I thought you left London."
13"She took a sip."
14"I heard you sold the"
15"I bought it back."
16"She set the glass down."
17"Her fingers traced the rim."
18"It pays the bills."
19"You used to do more"
ratio0.56
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount95
totalSentences100
matches
0"The green neon sign buzzed"
1"Rain slicked the cobblestones, reflecting"
2"Aurora pushed the heavy oak"
3"The air smelled of stale"
4"Maps covered the walls, pinned"
5"The bar was empty save"
6"Silas stood with his back"
7"His grey-streaked auburn hair caught"
8"He wore a dark vest"
9"He set the glass down"
10"His hazel eyes locked onto"
11"The limp in his left"
12"Her hand tightened on the"
13"The scar on her left"
14"She had not expected to"
15"She had not expected to"
16"Silas leaned against the counter."
17"He did not smile."
18"You look older."
19"Aurora pulled her coat tighter"
ratio0.95
50.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences100
matches
0"Because I'm not ready."
ratio0.01
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences22
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
83.7128%