Run: 2026-02-19-01KHTX24TS8640E0WGZJPX2AS3

Run Details

Duration:
48.8s
Cost:
$0.006969
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 of the Raven’s sign bled across the wet pavement, a sickly beacon in the London drizzle. Aurora Carter pushed through the heavy wooden door, the scent of rain and exhaust fumes giving way to stale beer, wax polish, and the faint, sharp tang of lemon peel. She shook the water from her black delivery jacket, the movement stiff. A long day of navigating one-way streets and impatient cyclists had settled deep in her bones. The bar was mostly empty. A couple huddled in a back booth, their faces illuminated by the blue glow of a phone. At the far end of the long, mahogany bar, Silas Blackwood methodically wiped a tumbler with a clean white cloth. His movements were precise, economical. Each circle of the cloth was identical to the last. He didn’t look up, but she knew he was aware of her. He was always aware. The bell above the door had chimed her arrival, a small, tired sound in the quiet room. Rory slid onto a stool a few places down from him, resting her forearms on the cool, sticky wood of the bar. She didn’t speak immediately, just watched him work. The grey in his auburn hair was more pronounced than she remembered, catching the low light like silver wire. The slight limp in his left leg was almost invisible when he stood still behind the bar, but she knew it was there, a souvenir from a life he never spoke of. He finished with the glass, holding it up to the light before placing it upside down on a rack. Then he turned, his hazel eyes finding hers. No surprise. Just a calm, steady appraisal. ‘Rough night.’ ‘Rough day.’ He nodded once, a flicker of understanding in his gaze. He reached under the bar for a bottle of bourbon, the good stuff he only brought out for specific people. He didn’t need to ask what she wanted. He placed a heavy crystal tumbler on the bar in front of her and poured two fingers of amber liquid. The ice he added cracked with a sharp, satisfying sound. Rory wrapped her hands around the glass, the cold seeping into her skin. She looked down at her left wrist, at the small, white crescent scar that stood out against her flushed skin. A childhood accident, a fall from a tree in a park that now felt like it belonged to another person entirely. ‘Still delivering for Yu-Fei?’ ‘Someone’s got to keep the Soho masses in crispy duck.’ A faint smile touched his lips, gone as quickly as it appeared. He leaned against the back bar, his posture deceptively relaxed. His silver signet ring glinted as he folded his arms. ‘She asks about you. Thinks you’re working too hard.’ ‘I’m working.’ Rory took a sip of the bourbon. The burn was a welcome distraction, a fire in the damp chill of the bar. ‘It’s what people do.’ ‘Not all people.’ She didn’t answer. Her gaze drifted to the walls, covered in the old maps and black-and-white photographs he’d collected over the years. A map of post-war Berlin. A faded photo of a tram in Prague. Places with histories, with scars. She used to love looking at them, imagining the lives lived in those cities, the secrets whispered in those streets. Now they just looked like a catalogue of damage. ‘I saw your father the other day.’ Rory’s shoulders tightened. The movement was slight, but Silas saw it. Of course, he saw it. ‘Did you.’ ‘At the Old Bailey. He was arguing a case. Looked well.’ ‘He always does.’ Her voice was flat. ‘Performance is his specialty.’ Silas was silent for a long moment, studying her. He wasn’t just seeing the delivery girl, the woman with tired eyes and rain-soaked hair. He was looking for the girl who used to sit on that very stool, debating constitutional law and the finer points of classic cinema. The girl who had a whole life mapped out, a bright, clean line stretching into a future he could almost see. ‘He asked about you.’ ‘And what did you tell him?’ ‘That I hadn’t seen you.’ A bitter laugh escaped her lips, a sound sharp and unfamiliar. ‘A lie for a lie. It’s fitting.’ ‘It wasn’t a lie, Rory. I haven’t seen *you*. Not for a while.’ She finally met his eyes, and the weight of his observation settled on her. He wasn’t judging. He was just stating a fact, the way he’d state the temperature or the time. But the truth of it landed like a physical blow. He saw the guarded set of her jaw, the way her eyes, once so full of quick, bright curiosity, now scanned the room like they were searching for threats. He saw the subtle changes, the ones she tried to hide. ‘People change, Si. The city makes sure of it.’ ‘Some more than others.’ She traced the rim of her glass with a finger. The condensation was beading on the polished wood. ‘I got a postcard from Eva last week. She’s in Barcelona. Teaching English to sun-drenched Spaniards.’ Rory’s voice dropped. ‘She sent a picture. She looks… happy. Unburdened.’ ‘And you’re not.’ It wasn’t a question. She shook her head, a small, tight movement. ‘That girl, the one who came here after her tutorials, the one who could argue you into a corner about the ethics of surveillance… she wouldn’t recognise me.’ She looked at her hands again, at the worn knuckles, the faint scars from a hundred different small jobs and careless moments. ‘I don’t think I recognise me.’ Silas pushed the bottle of bourbon a little closer to her side of the bar. An invitation. Not to forget, but to endure. ‘She’s still in there, Rory. Just buried under a few new layers.’ ‘Are they? Or is this just what’s left when everything else gets scraped away?’ She looked around the bar, at the shadows clinging to the corners, at the faces in the old photographs staring out from another time. ‘This place is a museum of things that are over. Maybe I belong here after all.’ He didn’t offer platitudes. He didn’t tell her it would get better. He just stood there, a solid, unmoving presence in the dim light. His silence was a kind of shelter, a space where she didn’t have to pretend. He had seen his own share of things that were over, his own past mapped out in the lines on his face and the ache in his knee. He understood the geography of regret.
created_at"2026-02-19T12:12:42.208Z" 2/19/2026, 12:12:42 PM
model"z-ai/glm-4.6" 4/6/2001, 12:00:00 AM
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1045
moderation_latency(null)
generation_time48711
tokens_prompt1094
tokens_completion3793
native_tokens_prompt998
native_tokens_completion3463
native_tokens_completion_images(null)
native_tokens_reasoning2064
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"
usage0.00696892
router(null)
provider_responses
0
endpoint_id"2a87c474-6f6a-457f-8d8c-2afc71fb9fad"
id"019c75d114e5004431fca505b726f6a5"
is_byokfalse
latency1045
model_permaslug"z-ai/glm-4.6" 4/6/2001, 12:00:00 AM
provider_name"SiliconFlow"
status200
api_type"completions"
id"gen-1771503162-i86KwTEjNrL7NMPSEw26"
upstream_id"019c75d114e5004431fca505b726f6a5"
total_cost0.00696892
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
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences0
tagDensity1
leniency1
rawRatio0
effectiveRatio0
90.95% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1105
totalAiIsmAdverbs2
found
0
adverb"quickly"
count1
1
adverb"very"
count1
highlights
0"quickly"
1"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)
59.28% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1105
totalAiIsms9
found
0
word"beacon"
count1
1
word"navigating"
count1
2
word"flicker"
count1
3
word"crystal"
count1
4
word"chill"
count1
5
word"weight"
count1
6
word"scanned"
count1
7
word"traced"
count1
8
word"silence"
count1
highlights
0"beacon"
1"navigating"
2"flicker"
3"crystal"
4"chill"
5"weight"
6"scanned"
7"traced"
8"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
narrationSentences81
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences81
filterMatches(empty)
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences110
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen36
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords1
totalWords1098
ratio0.001
matches
0"you"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions10
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions15
wordCount882
uniqueNames10
maxNameDensity0.45
worstName"Silas"
maxWindowNameDensity1
worstWindowName"Silas"
discoveredNames
Raven1
London1
Carter1
Silas4
Blackwood1
Berlin1
Prague1
Barcelona1
English1
Rory3
persons
0"Raven"
1"Carter"
2"Silas"
3"Blackwood"
4"Rory"
places
0"London"
1"Berlin"
2"Prague"
3"Barcelona"
globalScore1
windowScore1
57.41% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences54
glossingSentenceCount2
matches
0"felt like it belonged to another person"
1"looked like a catalogue of damage"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.911
wordCount1098
matches
0"Not to forget, but to endure"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences110
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs39
mean28.15
std27.1
cv0.962
sampleLengths
077
173
217
381
434
52
62
768
854
94
1010
1132
129
1328
143
1569
167
1716
182
1911
2011
2169
224
236
245
2518
2613
2782
289
294
3018
3127
323
3312
3456
3523
3612
3754
3873
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences81
matches
0"gets scraped"
0.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs126
matches
0"was arguing"
1"was looking"
2"wasn’t judging"
3"were searching"
4"was beading"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences110
ratio0
matches(empty)
97.90% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount283
adjectiveStacks0
stackExamples(empty)
adverbCount12
adverbRatio0.04240282685512368
lyAdverbCount4
lyAdverbRatio0.014134275618374558
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences110
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences110
mean9.98
std7.64
cv0.765
sampleLengths
019
130
212
316
45
517
620
75
810
912
104
1117
1222
138
1419
1532
1619
178
182
195
202
212
2210
2320
248
2520
2610
2713
2820
2921
304
3110
3212
3310
3410
354
365
379
3815
394
403
413
4219
435
448
455
4620
479
487
493
46.06% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats16
diversityRatio0.36363636363636365
totalSentences110
uniqueOpeners40
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount5
totalSentences75
matches
0"Then he turned, his hazel"
1"Just a calm, steady appraisal."
2"Of course, he saw it."
3"Just buried under a few"
4"Maybe I belong here after"
ratio0.067
28.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount36
totalSentences75
matches
0"She shook the water from"
1"His movements were precise, economical."
2"He didn’t look up, but"
3"He was always aware."
4"She didn’t speak immediately, just"
5"He finished with the glass,"
6"He nodded once, a flicker"
7"He reached under the bar"
8"He didn’t need to ask"
9"He placed a heavy crystal"
10"She looked down at her"
11"He leaned against the back"
12"His silver signet ring glinted"
13"She didn’t answer."
14"Her gaze drifted to the"
15"She used to love looking"
16"He was arguing a case."
17"He wasn’t just seeing the"
18"He was looking for the"
19"I haven’t seen *you*."
ratio0.48
53.33% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount61
totalSentences75
matches
0"The green neon of the"
1"Aurora Carter pushed through the"
2"She shook the water from"
3"A long day of navigating"
4"The bar was mostly empty."
5"A couple huddled in a"
6"His movements were precise, economical."
7"Each circle of the cloth"
8"He didn’t look up, but"
9"He was always aware."
10"The bell above the door"
11"Rory slid onto a stool"
12"She didn’t speak immediately, just"
13"The grey in his auburn"
14"The slight limp in his"
15"He finished with the glass,"
16"He nodded once, a flicker"
17"He reached under the bar"
18"He didn’t need to ask"
19"He placed a heavy crystal"
ratio0.813
66.67% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences75
matches
0"Now they just looked like"
ratio0.013
71.43% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences40
technicalSentenceCount4
matches
0"She looked down at her left wrist, at the small, white crescent scar that stood out against her flushed skin."
1"He was looking for the girl who used to sit on that very stool, debating constitutional law and the finer points of classic cinema."
2"The girl who had a whole life mapped out, a bright, clean line stretching into a future he could almost see."
3"He had seen his own share of things that were over, his own past mapped out in the lines on his face and the ache in his knee."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
85.7007%