Run: 2026-05-29-01KSSJWMXXX1AA1T1D08PTZDQ9

Run Details

Duration:
39.7s
Cost:
$0.059340
Provider:
Anthropic

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 buzzed overhead, casting a sickly wash across the rain-slicked pavement, and when Aurora pushed through the door of The Raven's Nest she shook the wet from her shoulders and didn't see him at first. The bar was nearly empty. A Tuesday in February did that, scared off the tourists and left only the regulars and the ghosts. She unzipped her delivery jacket, balanced the insulated bag against her hip, and waited at the counter for Silas to surface from the cellar with the night's stock. That was when the man at the far end lifted his head. "Rory?" She knew the voice before she placed the face. It came up through years of sediment, surfaced whole and intact, and she found her hand tightening on the strap of the bag. "It's me." He half-rose from the stool, then thought better of it and settled back down. "Tom. Tom Brennan. Cardiff. God, you don't recognise me." She recognised him. That was the trouble. Underneath the weight he'd put on, beneath the receding line of his hair and the beard that hadn't been there when they were nineteen, she found the boy who'd shared her cigarettes outside the law library at two in the morning, who'd quoted contract precedent at her like it was poetry and meant it. "Tom." The name came out flat. "What are you doing in London?" "Conference. Insolvency law, if you can believe anyone sits through that." He laughed, and the laugh was the same, that quick nervous bark she'd forgotten she'd known. "Came in for a drink and I've been the only one here for an hour. What about you? You live round here?" She set the bag down on the stool beside her. "Upstairs." "You live above a bar." He took this in. "That's—that's very you, actually. I'd have guessed something like that." "Would you." Silas came up from the cellar then, a crate of bottles balanced against his bad leg, and he read the room the way he read everything, in one slow pass. He set the crate down and slid two glasses across without being asked. "On the house," he murmured to her, and to Tom he said nothing, just poured and withdrew to the other end of the bar where the maps curled at their edges and the dead men in the photographs kept their counsel. Tom watched him go. "Friend of yours?" "My landlord." "You collect interesting people. You always did." He turned the glass in his hands without drinking. "I looked for you, you know. After. Nobody knew where you'd gone. Eva wouldn't say. Your mum just—she went quiet whenever I rang." "My mum had her reasons." "I'm not saying she didn't." He held up a hand. "I'm just saying it was strange. One term you were there, top of the seminar, arguing the examiner into the ground, and the next you'd vanished. People said all sorts." "People always do." She picked up the whisky, smelled the peat of it, set it down again. "What did people say, Tom?" He had the grace to look at the bar top. "That you'd had a breakdown. That you'd run off with someone. That you'd—" He stopped. "It doesn't matter what they said. I didn't believe most of it." "But you believed some." "I didn't know what to believe. You didn't give me anything to work with." There it was, the old grievance, polished smooth by however many years he'd carried it. Six. Seven. She did the arithmetic and it frightened her how it added up. They had been children when they last sat like this. They had thought they understood the shape of their own lives. "I left because I had to leave," she said. "That's the whole of it." "Because of Evan." The name landed in the quiet between them and she felt her jaw set. So he knew that much. Of course he did. There was no version of the past that stayed buried where you'd put it. "You knew Evan was bad news," Tom went on, quieter now, leaning in. "We all knew. I should've—I think about it, Rory. I think about how I sat there and watched him put you down in front of everyone and I made jokes to smooth it over because that was easier than saying something. I was a coward about it. I've been a coward about it for years." "You were twenty." "That's not an excuse." "No," she agreed. "But it's a reason." She finally drank, a small swallow that burned a clean line down through her chest. "You think you could've saved me a few bruises if you'd been braver. You couldn't. I'd have stayed regardless. That's how it works. You don't leave when your clever friend tells you to. You leave when there's nothing left of you to lose." He stared at her. The man he'd become wanted to argue the point, she could see it, the lawyer in him reaching for the rebuttal. The boy he'd been just sat there gutted. "You talk about it like it happened to someone else," he said. "It did, in a way." She turned the glass. "I'm not her anymore. The girl you knew. She wanted to be a barrister like her dad and she folded herself smaller every year to fit the shape someone else cut for her. She's gone. You're mourning a stranger." "You're not a stranger to me." "I am, though." She said it gently, which was worse than if she'd said it hard. "Look at you. You finished. You've got a practice, a conference badge in your pocket, a wedding ring—" she nodded at his hand, "—a whole life that ran on without me in it. And here I am delivering noodles in the rain. We're not the people who sat outside that library, Tom. Those two thought they had all the time in the world to become whatever they wanted. They were wrong." He looked down at the ring, twisting it. "Sarah," he offered, as if the name might bridge something. "We've a little girl. Maeve. She's two." "That's good. That's really good." And she meant it, which surprised her, the meaning of it rising up clean past all the rest. "You did the thing. You built something." "And you?" He searched her face. "Are you happy, Rory? I'm not asking to be cruel. I'm asking because I spent years not knowing if you were even alive, and now you're here and you won't tell me anything." Down the bar, Silas wiped a glass that was already clean and pretended not to listen, which was its own kind of listening. Aurora considered the question. The honest weight of it. "I'm here," she said at last. "Some days that's the whole answer. Some days it's enough."
created_at"2026-05-29T10:01:16.484Z" 5/29/2026, 10:01:16 AM
model"anthropic/claude-4.8-opus-20260528"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1129
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generation_time39497
tokens_prompt1094
tokens_completion1619
native_tokens_prompt1548
native_tokens_completion2064
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)
num_fetches(null)
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origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"end_turn"
service_tier"default"
usage0.05934
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provider_responses
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Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags19
adverbTagCount0
adverbTags(empty)
dialogueSentences49
tagDensity0.388
leniency0.776
rawRatio0
effectiveRatio0
86.87% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1142
totalAiIsmAdverbs3
found
0
adverb"very"
count1
1
adverb"gently"
count1
2
adverb"really"
count1
highlights
0"very"
1"gently"
2"really"
80.00% AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0"Blackwood"
found
0"Sarah"
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
91.24% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1142
totalAiIsms2
found
0
word"weight"
count2
highlights
0"weight"
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
narrationSentences53
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences53
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences81
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen72
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1138
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions17
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions13
wordCount659
uniqueNames7
maxNameDensity0.61
worstName"Tom"
maxWindowNameDensity1.5
worstWindowName"Tom"
discoveredNames
Aurora2
Raven1
Nest1
Tuesday1
February1
Silas3
Tom4
persons
0"Aurora"
1"Raven"
2"Silas"
3"Tom"
places(empty)
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences32
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1138
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences81
matches
0"knew that much"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs42
mean27.1
std21.21
cv0.783
sampleLengths
060
128
212
31
432
525
661
712
849
911
1019
112
1243
1341
147
152
1639
175
1840
1922
2037
214
2214
2350
2414
253
2637
2768
283
294
3065
3133
3212
3348
346
3587
3625
3730
3839
3923
409
4116
92.02% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences53
matches
0"being asked"
1"been children"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs124
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount0
flaggedSentences1
totalSentences81
ratio0.012
matches
0"\"Look at you. You finished. You've got a practice, a conference badge in your pocket, a wedding ring—\" she nodded at his hand, \"—a whole life that ran on without me in it. And here I am delivering noodles in the rain. We're not the people who sat outside that library, Tom. Those two thought they had all the time in the world to become whatever they wanted. They were wrong.\""
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount639
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.02190923317683881
lyAdverbCount6
lyAdverbRatio0.009389671361502348
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences81
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences81
mean14.05
std13.38
cv0.952
sampleLengths
037
15
218
328
412
51
69
723
816
99
103
114
1254
136
146
1527
1622
1710
181
199
2010
212
2230
2313
2441
254
263
272
2816
2923
305
3110
3230
3317
345
3510
3615
3712
384
3914
4015
411
421
4312
4410
4511
469
475
483
4914
72.02% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats5
diversityRatio0.4691358024691358
totalSentences81
uniqueOpeners38
70.92% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences47
matches
0"Of course he did."
ratio0.021
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount26
totalSentences47
matches
0"She unzipped her delivery jacket,"
1"She knew the voice before"
2"It came up through years"
3"He half-rose from the stool,"
4"She recognised him."
5"He laughed, and the laugh"
6"She set the bag down"
7"He took this in"
8"He set the crate down"
9"he murmured to her, and"
10"He turned the glass in"
11"He held up a hand"
12"She picked up the whisky,"
13"He had the grace to"
14"She did the arithmetic and"
15"They had been children when"
16"They had thought they understood"
17"She finally drank, a small"
18"He stared at her."
19"She turned the glass"
ratio0.553
34.47% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount40
totalSentences47
matches
0"The green neon buzzed overhead,"
1"The bar was nearly empty."
2"A Tuesday in February did"
3"She unzipped her delivery jacket,"
4"That was when the man"
5"She knew the voice before"
6"It came up through years"
7"He half-rose from the stool,"
8"She recognised him."
9"That was the trouble."
10"The name came out flat"
11"He laughed, and the laugh"
12"She set the bag down"
13"He took this in"
14"Silas came up from the"
15"He set the crate down"
16"he murmured to her, and"
17"Tom watched him go."
18"He turned the glass in"
19"He held up a hand"
ratio0.851
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences47
matches(empty)
ratio0
63.49% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences18
technicalSentenceCount2
matches
0"Underneath the weight he'd put on, beneath the receding line of his hair and the beard that hadn't been there when they were nineteen, she found the boy who'd s…"
1"Down the bar, Silas wiped a glass that was already clean and pretended not to listen, which was its own kind of listening."
72.37% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags19
uselessAdditionCount2
matches
0"He laughed, and the laugh was the same, that quick nervous bark she'd forgotten she'd known"
1"he offered, as if the name might bridge something"
88.78% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags7
fancyCount3
fancyTags
0"He laughed (laugh)"
1"he murmured (murmur)"
2"she agreed (agree)"
dialogueSentences49
tagDensity0.143
leniency0.286
rawRatio0.429
effectiveRatio0.122
85.0725%