Run: 2026-03-25-01KMJ92PQR2AK18ZPRP6VJ2MC3

Run Details

Duration:
1m 34s
Cost:
$0.001138
Provider:
SiliconFlow

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 green neon sign of The Raven’s Nest buzzed softly above the doorway, casting a spectral glow over the rain-slicked pavement. Inside, the bar exhaled warmth and decades—old wood, spilled gin, and the faint musk of cigar smoke embedded in the walls. The air hummed at a low frequency: a jazz trumpet winding through the crackle of vinyl, the low murmur of voices, the occasional burst of laughter that didn’t quite reach the eyes. Aurora Carter stood just inside the entrance, shaking water from her jacket. Her black hair clung damply to her neck, and she ran a hand through it, exhaling as the heat seeped into her skin. She glanced around, not quite at ease. She knew this place, knew its rhythms, but tonight she wasn’t here to unwind. She was here to ask questions—about a man who’d been asking about her. Then she saw him. Silas Blackwood sat at a corner booth, half in shadow, a tumbler of something amber in his hand. His profile was sharper than she remembered—etched with time, the grey in his auburn hair more pronounced, like frost creeping over autumn leaves. He turned his head slowly, as though sensing her gaze, and his hazel eyes locked onto hers with disconcerting precision. “Rory,” he said. Not a question. A recognition. She hesitated, then moved toward him. “Silas.” “You look like you’ve been wrestling London weather,” he said, gesturing to the seat across from him. “And losing.” She smiled, but it didn’t touch her eyes. “Just another day delivering dumplings through monsoon season.” She slipped into the booth, shrugging off her coat. The scar on her left wrist—the crescent-shaped ghost of a childhood fall—peeked out from beneath her sleeve as she folded her arms. Silas studied her. Not unkindly. But with the quiet assessment of someone who’d spent a career reading people. “You’ve changed.” “So have you,” she said lightly. “Last time I saw you, you didn’t have that limp.” He chuckled, shifting his weight slightly, one hand resting on his left knee. “Prague. 2007. I stepped on something that wasn’t supposed to be there. The knee hasn’t forgiven me.” “And you stepped back from all of it,” she said. “The spycraft. The tradecraft. The… whatever-craft.” “The curtain fell,” he said. “Sometimes the exit isn’t graceful. But it’s necessary.” She reached for the menu, more for something to do than real interest. “Still. Running a bar in Soho wasn’t exactly on my bingo card for you.” “And you,” he said, lowering his voice, “weren’t supposed to be pedaling through Camden on a delivery bike.” She stilled. Looked up. “What do you know about that?” “Word gets around,” he said. “Yu-Fei talks. And Yu-Fei trusts me.” Aurora exhaled through her nose. “Right. Of course.” A silence settled between them, thick with what wasn’t said. The jazz shifted—piano now, soft and melancholic. Outside, a bus hissed to a stop, its headlights slicing through the fogged window. “You look different,” Silas said again. “Not just older. Harder.” She tilted her chin upward. “Life’s a blunt instrument.” “I heard about Evan,” he said quietly. Her fingers tightened around the menu. “You don’t have to pretend you care.” “I don’t,” he admitted. “But I care that you went through it.” She laughed, low and bitter. “That’s new. Since when do you care about emotional fallout?” “Since I started seeing it everywhere.” He swirled his drink. “Used to think the worst damage was physical. Broken bones, bullet wounds. Now I know it’s the invisible things. The slow erosion.” She stared at him. “You sound like you’re writing your memoir.” “Maybe I am.” Silence again. The air between them felt charged, like before a storm. Then Aurora leaned forward, her bright blue eyes narrowing. “Why are you really here, Silas? This isn’t a reunion. You don’t do reunions.” He didn’t blink. “You’ve been asking questions about a man named Crowe.” Her breath hitched. Just slightly. But he saw it. Of course he did. “I’ve heard the name,” she said carefully. “That’s all.” “Aurora,” he said, and the use of her full name made her flinch, “don’t play dumb with me. You left a trail. Small, but visible. Inquiries at old phone drop boxes. Questions about encrypted burner networks. And now, Crowe.” “I didn’t even know you were watching.” “I watch the edges,” he said. “People like us—we don’t vanish. We linger at the periphery.” She looked away, out the window. Rain streaked the glass, distorting the streetlights into smears of gold. “He hurt someone,” she said, voice barely above a whisper. “A girl. Young. She didn’t know who to tell. I did.” “And you think Crowe was involved.” “She mentioned him,” Aurora said. “In passing. But the way she said it—like a name you’re afraid to breathe.” Silas sighed. Set his glass down. “Crowe was mine, once. Asset. Then liability. Then ghost. He vanished five years ago. Presumed dead. But ghosts have a habit of returning.” “Then why hasn’t anyone found him?” “Because he doesn’t want to be found. And because he was very good at disappearing.” Aurora’s fingers brushed her wrist, her thumb tracing the scar. A nervous habit she didn’t even realize she’d kept. “I used to think I was good at hiding,” she said. “But hiding and vanishing are different things.” Silas leaned forward. “You’re not thinking of chasing him, are you?” “I’m thinking someone should.” “And that someone is you?” She met his gaze. “Who else? The system failed her. Just like it failed me.” He studied her—really studied her—and for a moment, the man behind the spymaster cracked. “You were always too smart for your own good, Rory.” “And you were always too cautious.” “That caution kept me alive.” “Kept you isolated,” she shot back. “You built this place like a fortress. Even the bathrooms require three knocks and a password.” “It keeps the wrong people out.” “And the right ones?” she asked. “Do they even remember how to get in?” He didn’t answer. Aurora stood abruptly. “I didn’t come here for a lecture. Or a history lesson.” “Then what did you come for?” he asked, calm. “For the truth. About Crowe. About why you let him go. About whether you’d help me find him.” Silas looked at her—really looked—and saw the girl who’d once argued constitutional law at three a.m., who’d skipped exams to stand outside courthouses with protest signs, who’d fled her past with nothing but a backpack and a burner phone. He saw the woman who’d learned to ride the storm, to carry silence like armor. And he saw the danger in her now—not just to Crowe, but to herself. “I can’t help you,” he said. Her face hardened. “Of course not.” “But I won’t stop you,” he added. “And if you go looking, I’ll know. And if you get in over your head… I’ll be there.” She stared at him. Then, slowly, nodded. “Don’t make me regret that,” he said. She turned toward the door. Paused. “You know, when I was a kid, I used to think you were a character out of a spy novel. Cool, mysterious, always ten steps ahead.” “And now?” She glanced back, a ghost of a smile touching her lips. “Now I think you’re just a man who stayed in the shadows too long. And forgot what the light feels like.” The door closed behind her. Rain swallowed her silhouette. Silas sat in the dim light, fingers curling around his signet ring. Outside, the neon buzzed. Inside, the piano played on, slow and aching, like a memory refusing to die.
created_at"2026-03-25T10:36:39.037Z" 3/25/2026, 10:36:39 AM
model"qwen/qwen3-235b-a22b-07-25"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1536
moderation_latency(null)
generation_time94453
tokens_prompt867
tokens_completion2106
native_tokens_prompt834
native_tokens_completion1771
native_tokens_completion_images(null)
native_tokens_reasoning0
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"
usage0.00113766
router(null)
provider_responses
0
endpoint_id"ce835ea8-00c7-4686-831d-7733dac5e2d9"
id"019d24915e19d80eb1f8ec7b742e661f"
is_byokfalse
latency1536
model_permaslug"qwen/qwen3-235b-a22b-07-25"
provider_name"SiliconFlow"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.0; linux; x64))"
http_referer(null)
api_type"completions"
id"gen-1774434999-c1CFKv4qUyEy2lbJnAe3"
upstream_id"019d24915e19d80eb1f8ec7b742e661f"
total_cost0.00113766
cache_discount(null)
upstream_inference_cost0
provider_name"SiliconFlow"

Evaluation details

Result Evaluator Details Meta Data
88.89% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags24
adverbTagCount4
adverbTags
0"she said lightly [lightly]"
1"Silas said again [again]"
2"he said quietly [quietly]"
3"she said carefully [carefully]"
dialogueSentences72
tagDensity0.333
leniency0.667
rawRatio0.167
effectiveRatio0.111
52.90% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1274
totalAiIsmAdverbs12
found
0
adverb"softly"
count1
1
adverb"slowly"
count2
2
adverb"lightly"
count1
3
adverb"slightly"
count2
4
adverb"really"
count3
5
adverb"carefully"
count1
6
adverb"barely above a whisper"
count1
7
adverb"very"
count1
highlights
0"softly"
1"slowly"
2"lightly"
3"slightly"
4"really"
5"carefully"
6"barely above a whisper"
7"very"
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)
60.75% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1274
totalAiIsms10
found
0
word"spectral"
count1
1
word"warmth"
count1
2
word"etched"
count1
3
word"weight"
count1
4
word"silence"
count3
5
word"charged"
count1
6
word"whisper"
count1
7
word"tracing"
count1
highlights
0"spectral"
1"warmth"
2"etched"
3"weight"
4"silence"
5"charged"
6"whisper"
7"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
narrationSentences89
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences89
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences137
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen41
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1262
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions28
unquotedAttributions0
matches(empty)
98.60% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions18
wordCount681
uniqueNames7
maxNameDensity1.03
worstName"Silas"
maxWindowNameDensity2
worstWindowName"Aurora"
discoveredNames
Raven1
Nest1
Carter1
Blackwood1
Aurora6
Silas7
Crowe1
persons
0"Raven"
1"Nest"
2"Carter"
3"Blackwood"
4"Aurora"
5"Silas"
places
0"Crowe"
globalScore0.986
windowScore1
0.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences38
glossingSentenceCount3
matches
0"quite reach the eyes"
1"not quite at ease"
2"as though sensing her gaze, and his hazel eyes locked onto hers with disconcerting precision"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.792
wordCount1262
matches
0"not just to Crowe, but to herself"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences137
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs68
mean18.56
std15.57
cv0.839
sampleLengths
074
169
24
361
48
57
619
747
820
916
1030
1116
1213
1327
1418
1510
1611
178
1831
1910
209
217
2213
2312
2415
2532
2611
273
2835
2912
3013
319
3239
337
3416
3538
366
3719
3829
396
4015
4137
4211
434
445
4515
4624
476
485
4922
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences89
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs143
matches(empty)
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount11
semicolonCount0
flaggedSentences8
totalSentences137
ratio0.058
matches
0"Inside, the bar exhaled warmth and decades—old wood, spilled gin, and the faint musk of cigar smoke embedded in the walls."
1"She was here to ask questions—about a man who’d been asking about her."
2"His profile was sharper than she remembered—etched with time, the grey in his auburn hair more pronounced, like frost creeping over autumn leaves."
3"The scar on her left wrist—the crescent-shaped ghost of a childhood fall—peeked out from beneath her sleeve as she folded her arms."
4"The jazz shifted—piano now, soft and melancholic."
5"He studied her—really studied her—and for a moment, the man behind the spymaster cracked."
6"Silas looked at her—really looked—and saw the girl who’d once argued constitutional law at three a.m., who’d skipped exams to stand outside courthouses with protest signs, who’d fled her past with nothing but a backpack and a burner phone."
7"And he saw the danger in her now—not just to Crowe, but to herself."
88.21% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount694
adjectiveStacks0
stackExamples(empty)
adverbCount37
adverbRatio0.053314121037463975
lyAdverbCount14
lyAdverbRatio0.020172910662824207
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences137
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences137
mean9.21
std7.07
cv0.768
sampleLengths
021
121
232
312
423
57
614
713
84
918
1023
1120
123
133
142
156
161
1717
182
198
2017
2122
223
232
2413
252
266
2710
2813
2917
3010
316
325
338
3413
3514
3618
372
382
396
405
416
425
433
4410
457
4614
476
484
495
57.91% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.36496350364963503
totalSentences137
uniqueOpeners50
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount4
totalSentences69
matches
0"Then she saw him."
1"Then Aurora leaned forward, her"
2"Of course he did."
3"Then, slowly, nodded."
ratio0.058
11.30% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount36
totalSentences69
matches
0"Her black hair clung damply"
1"She glanced around, not quite"
2"She knew this place, knew"
3"She was here to ask"
4"His profile was sharper than"
5"He turned his head slowly,"
6"She hesitated, then moved toward"
7"he said, gesturing to the"
8"She smiled, but it didn’t"
9"She slipped into the booth,"
10"she said lightly"
11"He chuckled, shifting his weight"
12"She reached for the menu,"
13"he said, lowering his voice"
14"She tilted her chin upward."
15"he said quietly"
16"Her fingers tightened around the"
17"She laughed, low and bitter."
18"He swirled his drink"
19"She stared at him."
ratio0.522
54.20% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount56
totalSentences69
matches
0"The green neon sign of"
1"The air hummed at a"
2"Aurora Carter stood just inside"
3"Her black hair clung damply"
4"She glanced around, not quite"
5"She knew this place, knew"
6"She was here to ask"
7"Silas Blackwood sat at a"
8"His profile was sharper than"
9"He turned his head slowly,"
10"She hesitated, then moved toward"
11"he said, gesturing to the"
12"She smiled, but it didn’t"
13"She slipped into the booth,"
14"The scar on her left"
15"Silas studied her."
16"she said lightly"
17"He chuckled, shifting his weight"
18"She reached for the menu,"
19"he said, lowering his voice"
ratio0.812
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences69
matches(empty)
ratio0
60.44% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences26
technicalSentenceCount3
matches
0"The air hummed at a low frequency: a jazz trumpet winding through the crackle of vinyl, the low murmur of voices, the occasional burst of laughter that didn’t q…"
1"He turned his head slowly, as though sensing her gaze, and his hazel eyes locked onto hers with disconcerting precision."
2"Silas looked at her—really looked—and saw the girl who’d once argued constitutional law at three a.m., who’d skipped exams to stand outside courthouses with pro…"
83.33% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags24
uselessAdditionCount2
matches
0"she said, voice barely above a whisper"
1"he asked, calm"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags21
fancyCount2
fancyTags
0"he admitted (admit)"
1"he added (add)"
dialogueSentences72
tagDensity0.292
leniency0.583
rawRatio0.095
effectiveRatio0.056
78.5515%