Run: 2026-05-31-01KSYXQ516FS27EHM3H4FDTGPA

Run Details

Duration:
40.0s
Cost:
$0.060515
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 hummed above the door of the Raven's Nest, throwing watery light across the wet pavement. Inside, the air held the smell of old whiskey and older wood. Aurora shook the rain from her jacket and ducked into the dim, half-hoping the place was empty enough that she could nurse one drink in peace before the long walk back upstairs. A man at the far end of the bar turned at the sound of the door. He went still in a way that made her stop too. "Rory." The voice landed somewhere beneath her ribs. She knew it before she placed the face, and when she placed the face it didn't fit. The boy she'd known had been all sharp angles and nervous energy, hair flopping into his eyes, sleeves too long. This man sat squared and heavy, a beard going to seed along his jaw, eyes that had gone flat at the centre. "Daniel." She said it carefully, like setting down something fragile. "God. Daniel Frost." "In the flesh." He lifted his glass an inch. "Or what's left of it." She crossed the floor because there was no graceful way not to. The stool beside him scraped when she pulled it out. Silas worked the other end, polishing a tumbler that didn't need polishing, his hazel eyes flicking over the pair of them once before he gave them the privacy of his back. "How long has it been?" She didn't mean to ask. The question came out anyway, the obvious one, the one that opened the door she should have left shut. "Eleven years." He turned his glass a slow quarter-turn on the bar. "Cardiff. The Mackintosh. You were doing that thing where you argued both sides of everything just to win." "I was studying law." "You were torturing the rest of us." His mouth moved, not quite a smile. "How'd that go, by the way. The law." "It didn't." She caught Silas's eye and tapped the bar. He poured her something amber without asking what. "I deliver dumplings now. For a woman called Yu-Fei. Best food in three postcodes and I get to ride a bicycle in the rain." "From barrister to bicycle." Daniel exhaled through his nose. "That's a hell of a fall, Rory." "Or a hell of an escape." She wrapped both hands around the glass. "Depends which day you ask." He didn't laugh. The old Daniel would have laughed; he'd laughed at everything, even the things that should have broken him, the dead father, the mother who drank, the flat with the boiler that never worked. He'd made jokes in the cold like jokes were the only heat available. This man simply drank, and the silence sat between them with the weight of a third body on a too-small stool. "You went quiet on us," she said. "After uni. Eva tried to find you. We both did." "I didn't want finding." "That much was clear." She studied his profile, the new lines, the way his knuckles had thickened. "What happened to you, Dan?" "What happens to anyone." He shrugged, and the shrug cost him something. "Time. Decisions. I went into finance, if you can believe that. The boy who couldn't afford a kebab, moving other people's money around. Made a lot of it for a while. Lost the rest of myself doing it." "And now?" "Now I'm in a bar in Soho at half four on a Tuesday, talking to a ghost." He finally looked at her, properly, and something in his face cracked open for just a second. "You look exactly the same. That's the thing that's getting me. You walk in dripping and twenty-five again and I'm sitting here feeling every year I spent not being a person." She turned away from that, because it was too much and not enough at once. Outside a taxi hissed past through the standing water. "You weren't a bad person, Daniel." "I didn't say bad. I said not a person." He pressed his thumb into the wood grain. "There's a difference. Bad people feel things. I optimised feeling out of the budget a long time ago." A pause. "I missed your wedding, you know." "I'm not married." "The one I assumed you'd have. The one in my head where you married some clever solicitor and I sent a card." He shook his head slowly. "I built whole lives for you and Eva. Easier than answering the phone." She wanted to be angry. The anger was there, eleven years of it, the unreturned messages, the funeral of his mother where neither she nor Eva could find an address to send flowers. But anger needed a target with edges, and the man beside her had been sanded down to something she didn't recognise. "Eva's in Lisbon now," she offered instead. "Two kids. She'd want to know you're alive." "Would she." "She would." Aurora turned her glass. "She kept your number in her phone for years. Changed handsets three times and copied it over each time. I watched her do it once and asked why, and she said—" Her throat tightened around it. "She said, in case he ever wants to come back." Daniel went very still. For a long moment the only sound was the low murmur of the radio behind the bar and the rain finding the gutters. "That's a cruel thing to tell a man," he managed. "It's a true thing." "Same difference, sometimes." He drained the last of his drink and set the glass down with exaggerated care, the way men did when they'd had more than this. "You know what the worst part is, Rory? I keep thinking I'll fix it. The not-being-a-person. I'll wake up one morning and ring the people I left and say sorry, I went somewhere for eleven years, I'm back now. And then the morning comes and I don't, because what do you even say. There's no card for it. Sorry I missed your entire life." "You start with hello." She nudged his empty glass an inch toward him. "You seem to have managed that part already." Silas drifted back down the bar, and without a word poured them both another, his signet ring catching the lamplight. He retreated again before either could thank him. "You haven't asked what I'm running from," she said. "Didn't think it was my business." Daniel looked at her sidelong. "Are you running from something?" "Everyone in this bar is running from something. It's why it's this dim." She lifted her glass and held it there between them, an offering, a truce. "To the people we were." He didn't drink right away. His eyes had gone bright and unsteady at the edges. "They were better than us," he said quietly. "They were younger than us." She clinked her glass against his before he could argue it. "That's not the same thing, no matter how much you've decided it is."
created_at"2026-05-31T11:46:42.867Z" 5/31/2026, 11:46:42 AM
model"anthropic/claude-4.8-opus-20260528"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1120
moderation_latency(null)
generation_time39965
tokens_prompt1094
tokens_completion1647
native_tokens_prompt1548
native_tokens_completion2111
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)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"end_turn"
service_tier"default"
usage0.060515
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provider_responses
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is_byokfalse
latency1120
model_permaslug"anthropic/claude-4.8-opus-20260528"
provider_name"Anthropic"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.16.0; linux; x64))"
http_referer(null)
request_id"req-1780228002-GThoG8tQ4yn8GHn9q4LY"
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api_type"completions"
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provider_name"Anthropic"
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Evaluation details

Result Evaluator Details Meta Data
88.89% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags24
adverbTagCount3
adverbTags
0"she offered instead [instead]"
1"Her throat tightened around [around]"
2"he said quietly [quietly]"
dialogueSentences54
tagDensity0.444
leniency0.889
rawRatio0.125
effectiveRatio0.111
87.04% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1157
totalAiIsmAdverbs3
found
0
adverb"carefully"
count1
1
adverb"slowly"
count1
2
adverb"very"
count1
highlights
0"carefully"
1"slowly"
2"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)
91.36% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1157
totalAiIsms2
found
0
word"silence"
count1
1
word"weight"
count1
highlights
0"silence"
1"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
narrationSentences55
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences55
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences83
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen68
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1157
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
totalMentions12
wordCount648
uniqueNames6
maxNameDensity0.62
worstName"Daniel"
maxWindowNameDensity1
worstWindowName"Silas"
discoveredNames
Raven1
Nest1
Silas3
Daniel4
Eva1
Aurora2
persons
0"Raven"
1"Nest"
2"Silas"
3"Daniel"
4"Eva"
5"Aurora"
places(empty)
globalScore1
windowScore1
85.90% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences39
glossingSentenceCount1
matches
0"not quite a smile"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.864
wordCount1157
matches
0"neither she nor"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences83
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs42
mean27.55
std21.92
cv0.796
sampleLengths
062
127
21
366
413
514
653
729
830
94
1022
1142
1216
1318
1470
1517
164
1722
1850
192
2065
2124
226
2343
243
2540
2654
2715
282
2952
3027
3110
324
3392
3421
3528
369
3716
3832
3915
408
4129
98.88% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences55
matches
0"been sanded"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs106
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences83
ratio0.012
matches
0"The old Daniel would have laughed; he'd laughed at everything, even the things that should have broken him, the dead father, the mother who drank, the flat with the boiler that never worked."
96.02% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount651
adjectiveStacks0
stackExamples(empty)
adverbCount29
adverbRatio0.0445468509984639
lyAdverbCount8
lyAdverbRatio0.01228878648233487
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences83
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences83
mean13.94
std10.5
cv0.753
sampleLengths
018
112
232
316
411
51
67
717
820
922
1010
113
129
135
1412
1510
1631
1710
1819
1912
2018
214
2214
238
2410
258
2624
279
287
2913
305
313
3233
3313
3421
357
3610
374
3817
395
4012
4138
422
4334
4431
4515
469
476
4817
4920
73.90% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.4939759036144578
totalSentences83
uniqueOpeners41
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences51
matches(empty)
ratio0
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount30
totalSentences51
matches
0"He went still in a"
1"She knew it before she"
2"She said it carefully, like"
3"He lifted his glass an"
4"She crossed the floor because"
5"She didn't mean to ask"
6"He turned his glass a"
7"His mouth moved, not quite"
8"She caught Silas's eye and"
9"He poured her something amber"
10"She wrapped both hands around"
11"He didn't laugh."
12"He'd made jokes in the"
13"She studied his profile, the"
14"He shrugged, and the shrug"
15"He finally looked at her,"
16"She turned away from that,"
17"He pressed his thumb into"
18"He shook his head slowly"
19"She wanted to be angry."
ratio0.588
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount47
totalSentences51
matches
0"The green neon hummed above"
1"Aurora shook the rain from"
2"A man at the far"
3"He went still in a"
4"The voice landed somewhere beneath"
5"She knew it before she"
6"The boy she'd known had"
7"This man sat squared and"
8"She said it carefully, like"
9"He lifted his glass an"
10"She crossed the floor because"
11"The stool beside him scraped"
12"Silas worked the other end,"
13"She didn't mean to ask"
14"The question came out anyway,"
15"He turned his glass a"
16"His mouth moved, not quite"
17"She caught Silas's eye and"
18"He poured her something amber"
19"Daniel exhaled through his nose"
ratio0.922
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences51
matches(empty)
ratio0
74.83% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences21
technicalSentenceCount2
matches
0"Silas worked the other end, polishing a tumbler that didn't need polishing, his hazel eyes flicking over the pair of them once before he gave them the privacy o…"
1"The old Daniel would have laughed; he'd laughed at everything, even the things that should have broken him, the dead father, the mother who drank, the flat with…"
83.33% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags24
uselessAdditionCount2
matches
0"His mouth moved, not quite a smile"
1"She lifted, an offering, a truce"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount1
fancyTags
0"He pressed (press)"
dialogueSentences54
tagDensity0.093
leniency0.185
rawRatio0.2
effectiveRatio0.037
82.6714%