Run: 2026-04-27-01KQ77N7M9WPXZW1WE2X9MH6QW

Run Details

Duration:
43.7s
Cost:
$0.010185
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 against the wet pavement outside, painting the Soho street in a fractured blue-green. Aurora shouldered through the heavy oak door. The brass bell clanged. Cold air fled as humid warmth rushed to meet her. She shed her coat. Rainwater dripped from her straight black hair onto her collar. Her bright blue eyes cut through the dim room, tracking the shadows until they caught on the high table by the rear bookshelf. The leather jacket on the chair held his shape. The silver signet ring gleamed on his right hand. He sat alone, hazel eyes fixed on the wood grain, a half-finished tumbler resting near his elbow. Years of static collapsed into the sharpness of recognition. She pushed off the doorframe and crossed the floor. The boards groaned under her boots. He did not look up until she stopped beside his table. His head lifted. A slow blink cleared the distance from his gaze. He exhaled through his nose. A faint limp shifted his weight against the table leg as he straightened. You look terrible. Her voice cut through the jukebox. You look like you survived something. He reached for the bottle, poured two fingers of amber liquid, and set the glass down with a soft click. His knuckles bore deep calluses. A thin scar traced his left temple. He slid the fresh glass toward her. Drink. It has been too long. She wrapped her fingers around the rim. Heat seeped into her skin. Her left wrist ached where the crescent scar lived beneath her sleeve. Two years. Maybe three. She stared at the ice fracturing inside the crystal. I did not think you would still be running this place. Never left. Just stopped shouting orders from embassy basements. He tapped the table twice. The wood vibrated. I prefer the quiet. The drinks stay here. The problems stay out. A dry laugh rattled in his chest. You always did see right through the architecture. I see a lot of things now. She took a sip. The burn traveled down her throat. Cardiff feels like a different era. Evan’s shadow followed me to London. I kept my head down. I worked the deliveries. I dropped bags at the back door while the city rushed past. He shook his head. His grey-streaked auburn hair fell over his forehead. I heard whispers. Fleeing an abusive marriage. Changing your routes. The legal world swallowed you whole. Then you vanished. The law was a cage I did not know I had walked into. She set the glass down. My fingers still cramp when I see a statute book. I left. Eva pulled me through the door. She put me on the roof. This place. I work part-time now. I sleep above the bar. I learn which customers tip and which ones lie. He leaned back. The chair creaked. You still wear that ring. He pointed to her plain silver band. I never took it off. After everything, some anchors keep you from drifting. Anchors drag you under. Her knuckles whitened. I watch the couriers burn out by forty. I watch the regulars fade into the walls. I learned to read faces the way you used to read dead drops. You taught me that. Or I just learned to listen. He picked up his own glass. Ice clinked against crystal. I spent a decade walking through foreign capitals. I memorized exits. I trusted the wrong people. I watched good men turn to ghosts I could not save. I came back with a ruined knee and a head full of static. The Nest became a vault I furnished with maps and photographs. I did not know about you. I thought you had vanished into the system. I did. She traced the rim of her glass with her thumb. Pre-Law lectures. Late nights arguing about contract breach. Then the phone calls stopped. The texts turned to voicemail. You were off the grid for eighteen months. Then the silence became permanent. He set his glass down. His hands trembled sometimes. He kept the phone switched off. Too dangerous. The agency burns loose ends. He did not want her breathing the same air as the wreckage. She stared at him. The neon light painted his face in sharp relief. You let us think you were dead. Safer that way. His jaw tightened. He wrote letters he never sent. He stacked them in a locked drawer. He thought she had moved on. He thought she had built a life that did not need a missing man’s name hanging over it. She leaned forward. The wood table bit into her elbows. I waited for you to show up. I left messages at the embassy. I drove past your old safehouses. Empty lots. Demolition sites. I assumed you were gone because you did not want to be found. His eyes darkened. Regret carved new ridges around his mouth. You always were too stubborn to let people walk away. I told myself I was doing you a favor. I kept you clean. I was wrong. The jukebox shifted to a lower track. Bass lines thumped against the floorboards. Rain tapped against the windowpanes. She watched his reflection in the glass. The boy who handed her library books and debated constitutional law dissolved into the man guarding a Soho backroom. The weight of it settled in her ribs. We counted years like currency. We swapped plans for futures that never materialized. I imagined you in a courtroom. Defending the accused. You imagined me on a beach somewhere. Drinking something sweet. Bored out of my mind. She laughed, a sharp, hollow sound. I sold packages of stir-fry and dumplings while you bled for secrets. We traded places without asking. He slid the bottle closer. The liquid caught the light. I watched you from a distance once. After you moved above the bar. I saw you carrying boxes. You looked thinner. Tired. You kept your head down. I wanted to step outside. I wanted to tell you I was there. The words stuck in my throat. I missed the part where you built yourself from the ground up. I stayed in the shadows while you lived in the daylight. She shook her head. The movement sent a strand of black hair across her jaw. I lived in the basement of my own making. You taught me to think around corners. I never knew how to build a door. He looked away, focusing on the tapestry of black-and-white photographs behind the bar. Faces of strangers. Faces of friends. Faces of losses. Time eroded us both. We just carved different stones. I hated you for leaving. The words left her mouth without filter. I carried that hate like gravel in my shoe. It hurt every single step. He did not flinch. He watched the condensation pool on the table. Hate stays cleaner than forgetting. It keeps the past from bleeding out completely. She set her glass down hard. Ice shattered. I remember the arguments. I remember the way you leaned in when I talked. I remember the way you caught my wrist when I paced too fast. You were supposed to be my compass. You became a blank space instead. His fingers brushed the silver ring on his right hand. I became exactly what you needed me to be. I became a warning. I became a lesson. You do not need a compass when you learn to read the night. She looked at his hands. Old injuries mapped the skin. Quiet authority remained, but it bowed under the exhaustion. We broke things while we tried to save them. He reached across the table. His calloused fingers hovered near her scar before retreating. I should have stayed. I should have fought the silence. He let the door stay shut longer than he wanted. She covered his hand with hers. Temperature differences registered instantly. Cold stone meeting dry heat. Let it stay shut. The world kept spinning. We kept turning corners. He exhaled, long and slow. The tension in his shoulders eased. We keep turning. We watch the scenery change. We learn the shapes of what we lost. She withdrew her hand. The neon sign outside flickered. Green light painted the table in pulses. I have a delivery route at dawn. He smiled, thin and genuine. I will pour you a proper glass. Not this watery regret. She laughed again. The sound felt lighter. Less like breaking. Less like holding on. He lifted his glass. To the blanks we filled. She raised hers. To the doors we left open. The crystal touched. Cold liquid stained their lips. The rain continued its steady rhythm against the glass. The bar hummed around them. Maps stretched across the walls. Photographs watched in silence. Two old friends sat in the warm dark, tracing the edges of what remained.
created_at"2026-04-27T10:27:15.729Z" 4/27/2026, 10:27:15 AM
model"qwen/qwen3.6-flash"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency807
moderation_latency(null)
generation_time43538
tokens_prompt1094
tokens_completion7285
native_tokens_prompt1060
native_tokens_completion6613
native_tokens_completion_images(null)
native_tokens_reasoning4780
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"
usage0.0101845
router(null)
provider_responses
0
endpoint_id"2435bec9-c808-4f27-9fc8-12f3460d7b66"
id"chatcmpl-c328da9e-b70c-9dc8-80d2-ef64a6048e19"
is_byokfalse
latency807
model_permaslug"qwen/qwen3.6-flash"
provider_name"Alibaba"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1777285635-2A17R5EFYFFTa248Ugtu"
session_id(null)
api_type"completions"
id"gen-1777285635-9BqkER3jzoR4rDAdoaTS"
upstream_id"chatcmpl-c328da9e-b70c-9dc8-80d2-ef64a6048e19"
total_cost0.0101845
cache_discount(null)
upstream_inference_cost0
provider_name"Alibaba"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags0
96.61% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1477
totalAiIsmAdverbs1
found
0
adverb"completely"
count1
highlights
0"completely"
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)
32.30% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1477
totalAiIsms20
found
0
word"fractured"
count1
1
word"warmth"
count1
2
word"weight"
count2
3
word"traced"
count2
4
word"crystal"
count3
5
word"vibrated"
count1
6
word"silence"
count3
7
word"trembled"
count1
8
word"tapestry"
count1
9
word"shattered"
count1
10
word"calloused fingers"
count1
11
word"tension"
count1
12
word"flickered"
count1
13
word"tracing"
count1
highlights
0"fractured"
1"warmth"
2"weight"
3"traced"
4"crystal"
5"vibrated"
6"silence"
7"trembled"
8"tapestry"
9"shattered"
10"calloused fingers"
11"tension"
12"flickered"
13"tracing"
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
narrationSentences230
matches(empty)
86.96% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount8
hedgeCount1
narrationSentences230
filterMatches
0"look"
1"see"
2"watch"
3"think"
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences230
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen23
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1477
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
99.22% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount1477
uniqueNames6
maxNameDensity1.02
worstName"You"
maxWindowNameDensity2
worstWindowName"You"
discoveredNames
Soho2
London1
Nest1
Cold3
You15
Faces3
persons
0"Nest"
1"You"
places
0"Soho"
1"London"
globalScore0.992
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences117
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1477
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences230
matches
0"carried that hate"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs14
mean105.5
std54.25
cv0.514
sampleLengths
0176
19
251
348
444
581
693
7121
897
9125
10112
11149
12167
13204
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences230
matches
0"were gone"
1"were supposed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs304
matches
0"was doing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences230
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1485
adjectiveStacks0
stackExamples(empty)
adverbCount33
adverbRatio0.022222222222222223
lyAdverbCount3
lyAdverbRatio0.00202020202020202
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences230
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences230
mean6.42
std3.49
cv0.543
sampleLengths
018
17
24
310
44
510
623
79
89
917
109
119
126
1311
143
159
165
1713
183
196
206
2120
225
237
247
251
265
277
285
2912
302
312
329
3311
342
357
365
373
384
394
404
417
428
437
444
456
466
476
485
494
33.48% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats38
diversityRatio0.25217391304347825
totalSentences230
uniqueOpeners58
61.44% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount4
totalSentences217
matches
0"Just stopped shouting orders from"
1"Then you vanished."
2"Then the phone calls stopped."
3"Then the silence became permanent."
ratio0.018
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount135
totalSentences217
matches
0"She shed her coat."
1"Her bright blue eyes cut"
2"He sat alone, hazel eyes"
3"She pushed off the doorframe"
4"He did not look up"
5"His head lifted."
6"He exhaled through his nose."
7"You look terrible."
8"Her voice cut through the"
9"You look like you survived"
10"He reached for the bottle,"
11"His knuckles bore deep calluses."
12"He slid the fresh glass"
13"It has been too long."
14"She wrapped her fingers around"
15"Her left wrist ached where"
16"She stared at the ice"
17"I did not think you"
18"He tapped the table twice."
19"I prefer the quiet."
ratio0.622
19.91% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount191
totalSentences217
matches
0"The green neon sign buzzed"
1"Aurora shouldered through the heavy"
2"The brass bell clanged."
3"She shed her coat."
4"Rainwater dripped from her straight"
5"Her bright blue eyes cut"
6"The leather jacket on the"
7"The silver signet ring gleamed"
8"He sat alone, hazel eyes"
9"Years of static collapsed into"
10"She pushed off the doorframe"
11"The boards groaned under her"
12"He did not look up"
13"His head lifted."
14"A slow blink cleared the"
15"He exhaled through his nose."
16"A faint limp shifted his"
17"You look terrible."
18"Her voice cut through the"
19"You look like you survived"
ratio0.88
46.08% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences217
matches
0"To the blanks we filled."
1"To the doors we left"
ratio0.009
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences34
technicalSentenceCount1
matches
0"The boy who handed her library books and debated constitutional law dissolved into the man guarding a Soho backroom."
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
85.8667%