Run: 2026-03-25-01KMJ8GA1M5HHP0XDSPQHAKB6V

Run Details

Duration:
1m 32s
Cost:
$0.001048
Provider:
SiliconFlow

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 of The Raven’s Nest flickered like a dying heartbeat against the Soho drizzle. Inside, the air hung thick with the scent of aged whiskey, cigar smoke, and dust-laden paperbacks. A jazz trumpet wailed low from a corner speaker, something smoky and unresolved. Silas stood behind the bar, a cloth moving in slow circles over a tumbler. His right hand, ring glinting under the amber lights, worked with the rhythm of habit. The left leg stiffened when the room cooled — the Prague winter never really left. The bell above the door jingled, sharp and out of key with the music. A figure stepped in, shaking water from a leather jacket too worn to still be fashionable. She pulled off her hood. Black hair, cut sharp at the shoulders, clung damp to her neck. Her face was leaner than it had been, angles carved deeper by something more than just time. The blue of her eyes still caught the light like shallow sea ice. Silas didn’t look up. “Back again so soon, Rory? You’ll wear out the welcome mat.” She didn’t move toward the bar. “I didn’t know it was *yours*.” That made him glance up. His cloth stilled. For a heartbeat, nothing changed. Then his fingers curled slightly around the glass. He took her in — the set of her shoulders, the unconscious way she scanned the room, the scar on her wrist just visible beneath her sleeve. He’d seen that scar split open once, bleeding into a Cardiff gutter after she fell off a bike at twelve. He’d driven her to the clinic, her father too far down a whiskey bottle to notice. “You knew,” Aurora said quietly. “You knew I was living above the bar. Eva told me.” “Eva talks too much.” His voice was gravel wrapped in velvet. He set the glass down. “But no. I didn’t know you’d walk through that door looking like you’ve outrun a war.” “I have.” She stepped forward, removed her jacket, hung it on a hook like she’d done it a hundred times. “Not your wars. Mine.” He watched her settle onto a stool. The bar groaned beneath her weight, an old sound. “You used to come in swings,” he said. “Never straight lines. Always testing the distance.” “And you used to pretend you didn’t notice.” She reached for a coaster, spun it between her fingers. “You used to give me cherry sodas in pint glasses and call it training.” A ghost of a smile tugged at his mouth. Then it faded. “That was before Prague. Before the knee. Before I decided staying alive was a quieter business.” She looked at him — really looked — for the first time since stepping inside. “You limp more.” “It remembers snow and gunfire. What about you? Eva says you deliver food now. On a motorbike.” “On a Vespa that sounds like a dying pigeon. But it pays the rent.” She tapped the scar on her wrist. “Still heals slow, huh?” Silas exhaled through his nose. “Still there.” They sat in silence while the trumpet spiraled into a solo full of bent notes. “You ever hear from him?” she asked. “Who?” “You know who.” He poured two fingers of single malt into a glass, slid it toward her. “No. He’s dead. Car crash in ’22. Drunk, headlights off. I heard through a contact in Manchester.” She didn’t touch the glass. “I dreamed about him last week. Standing in the kitchen of that flat. Smiling like he hadn’t broken my ribs.” “You never told me how bad it was.” “I told Eva. She told you.” “She left it in pieces. Like always.” “She kept me alive.” Aurora lifted the glass, sniffed it. “Peat, smoke, betrayal. Classic you.” “You haven’t changed that much.” “I have.” She met his gaze. “I used to think if I stayed quiet, stayed small, I could make it through. I stopped believing that the night I poured boiling water down his throat.” Silas didn’t react. Not a twitch. Just the slow rise and fall of his chest, measured, like during briefings when intel turned ugly. “That wasn’t self-defense,” he said. “No. It wasn’t.” She drank. Winced. “It was revenge. I held the kettle until my hand burned. He screamed. I didn’t let go.” He stared at her left hand. The scar. The nails bitten to the quick. “You were always too smart for stillness.” “And you were always too quiet for comfort. I used to think you were just brooding. Now I know you were calculating angles. Escape routes. When to cut your losses.” “I taught you that.” “No. You *are* that.” She turned the glass in her palm. “Why’d you let me live here, Silas? You knew who I was running from. You knew what I’d done to get away.” “Because Eva called. Because you were twenty-three, shaking, covered in bruises that hadn’t gone purple yet. Because you looked at me like I was the last quiet place in the world.” “And now?” “Now you look like you could kill someone with a shoelace and not blink.” A laugh escaped her, sharp and dry. “You’re not wrong.” He reached beneath the bar, pulled out a slim dossier wrapped in brown string. Set it between them. “You ever want to know how he found you that last time?” he asked. Her fingers stilled. “I blocked it. I don’t want to know.” “You should. It matters.” “It matters if I can sleep. And I can’t. Not with names. Not with details.” Silas leaned forward. “He had a burner phone. Tracked your delivery app through a fake order. Used your route data. Found the flat above the laundrette. That was close.” She closed her eyes. Opened them. “So I changed the routes. Changed my name. Changed how I walked. Changed how I ordered coffee.” “And yet here you are. In a bar owned by a man who knows too much. Living above it. Using your real name in deliveries.” “I’m not hiding anymore.” She straightened. “I’m waiting.” “For what?” She looked past him, to the bookshelf lined with Spalding Gray and Le Carré and dog-eared Kipling. “You still use the back room?” His jaw tightened. “I saw the shelf move last Tuesday,” she said. “When that man in the grey coat came in. You didn’t serve him. You took him through.” Silas said nothing. “I followed the delivery manifest. Noticed patterns. Tuesday nights. Same time. Different men. All quiet. All watched the exit.” “You shouldn’t dig,” he said. “I’m not digging. I’m seeing.” She leaned in. “You’re still in the game. Just playing it from behind a counter.” “And you’re still running.” “No.” She stood. “I’m standing. That’s different.” She reached into her jacket, pulled out an envelope. Plain. No stamp. Set it on the bar. “That’s from Yu-Fei,” she said. “He doesn’t know what’s inside. But he knew not to ask.” Silas didn’t touch it. “He said to tell you it’s a ‘delivery that didn’t go south.’ Whatever that means.” Her boots echoed as she turned. “Rory.” She paused at the door. “You don’t have to come back.” “I know.” She glanced back. “But I will.”
created_at"2026-03-25T10:26:36.215Z" 3/25/2026, 10:26:36 AM
model"qwen/qwen3-235b-a22b-07-25"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency5484
moderation_latency(null)
generation_time92169
tokens_prompt1094
tokens_completion1917
native_tokens_prompt1012
native_tokens_completion1595
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"
usage0.00104808
router(null)
provider_responses
0
endpoint_id"ce835ea8-00c7-4686-831d-7733dac5e2d9"
id"019d24883a2d312ea01c10c010b468f6"
is_byokfalse
latency5484
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-1774434396-8SY3FB1EwL7ozf0k7F62"
upstream_id"019d24883a2d312ea01c10c010b468f6"
total_cost0.00104808
cache_discount(null)
upstream_inference_cost0
provider_name"SiliconFlow"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags20
adverbTagCount2
adverbTags
0"Aurora said quietly [quietly]"
1"She glanced back [back]"
dialogueSentences70
tagDensity0.286
leniency0.571
rawRatio0.1
effectiveRatio0.057
87.44% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1194
totalAiIsmAdverbs3
found
0
adverb"really"
count2
1
adverb"slightly"
count1
highlights
0"really"
1"slightly"
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)
62.31% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1194
totalAiIsms9
found
0
word"flickered"
count1
1
word"glinting"
count1
2
word"scanned"
count1
3
word"velvet"
count1
4
word"weight"
count1
5
word"silence"
count1
6
word"measured"
count1
7
word"calculating"
count1
8
word"echoed"
count1
highlights
0"flickered"
1"glinting"
2"scanned"
3"velvet"
4"weight"
5"silence"
6"measured"
7"calculating"
8"echoed"
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
narrationSentences75
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences75
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences125
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen32
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords2
totalWords1198
ratio0.002
matches
0"yours"
1"are"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions19
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions18
wordCount566
uniqueNames12
maxNameDensity1.24
worstName"Silas"
maxWindowNameDensity2.5
worstWindowName"Silas"
discoveredNames
Raven1
Nest1
Soho1
Prague1
Cardiff1
Silas7
Winced1
Spalding1
Gray1
Le1
Carré1
Kipling1
persons
0"Raven"
1"Nest"
2"Silas"
places
0"Soho"
1"Prague"
2"Cardiff"
globalScore0.882
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences36
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1198
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences125
matches
0"seen that scar"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs69
mean17.36
std15.83
cv0.912
sampleLengths
090
114
263
315
412
58
676
716
832
924
1016
1115
1232
1328
1418
1517
1625
177
1815
197
201
213
2231
2325
248
256
267
2715
285
2934
3023
315
3223
3321
3430
354
3633
3731
382
3914
4010
4118
4214
4311
444
4515
4629
4723
4825
498
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences75
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs107
matches(empty)
74.29% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount4
semicolonCount0
flaggedSentences3
totalSentences125
ratio0.024
matches
0"The left leg stiffened when the room cooled — the Prague winter never really left."
1"He took her in — the set of her shoulders, the unconscious way she scanned the room, the scar on her wrist just visible beneath her sleeve."
2"She looked at him — really looked — for the first time since stepping inside."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount564
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.031914893617021274
lyAdverbCount5
lyAdverbRatio0.008865248226950355
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences125
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences125
mean9.58
std6.9
cv0.72
sampleLengths
017
116
213
314
415
515
614
716
85
912
1017
1113
124
1311
146
156
165
173
185
198
2027
2120
2216
235
2411
2511
265
2716
2820
294
307
319
328
337
3418
3514
369
373
3816
3915
403
4117
4221
434
445
452
4615
477
481
493
44.27% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats8
diversityRatio0.304
totalSentences125
uniqueOpeners38
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences60
matches
0"Then his fingers curled slightly"
1"Then it faded."
2"Just the slow rise and"
ratio0.05
13.33% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount31
totalSentences60
matches
0"His right hand, ring glinting"
1"She pulled off her hood."
2"Her face was leaner than"
3"She didn’t move toward the"
4"His cloth stilled."
5"He took her in —"
6"He’d seen that scar split"
7"He’d driven her to the"
8"His voice was gravel wrapped"
9"He set the glass down."
10"She stepped forward, removed her"
11"He watched her settle onto"
12"She reached for a coaster,"
13"She looked at him —"
14"She tapped the scar on"
15"They sat in silence while"
16"He poured two fingers of"
17"She didn’t touch the glass."
18"She met his gaze"
19"He stared at her left"
ratio0.517
35.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount51
totalSentences60
matches
0"The green neon sign of"
1"A jazz trumpet wailed low"
2"Silas stood behind the bar,"
3"His right hand, ring glinting"
4"The left leg stiffened when"
5"The bell above the door"
6"A figure stepped in, shaking"
7"She pulled off her hood."
8"Her face was leaner than"
9"The blue of her eyes"
10"Silas didn’t look up."
11"She didn’t move toward the"
12"That made him glance up."
13"His cloth stilled."
14"He took her in —"
15"He’d seen that scar split"
16"He’d driven her to the"
17"Aurora said quietly"
18"His voice was gravel wrapped"
19"He set the glass down."
ratio0.85
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences60
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences20
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags20
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags8
fancyCount0
fancyTags(empty)
dialogueSentences70
tagDensity0.114
leniency0.229
rawRatio0
effectiveRatio0
86.6656%