Run: 2026-06-01-01KT1GC6HJFZH2PM61KN8FHNEQ

Run Details

Duration:
40.4s
Cost:
$0.063415
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 a sickly wash across the wet pavement. Aurora ducked inside, shaking rain from her jacket, the dregs of a delivery shift still clinging to her in the smell of fried garlic and cardboard. She wanted one drink. One drink and the stairs to her flat above. She didn't notice the woman at the end of the bar until she'd already sat down. "Rory?" The voice did something to the back of her neck before her brain caught up. She turned. The woman two stools down had her hand wrapped around a glass of something amber, untouched, the ice gone to slivers. Cropped blonde hair now, where there'd been a long brown plait. A tailored coat. Lines around the mouth that hadn't been there at twenty. "Eva." "God." Eva laughed, and the laugh broke halfway. "I wasn't sure. You've gone dark." "Dyed it." Aurora touched her own hair as if checking it was still attached. "Years ago." Silas drifted over with the slow, deliberate weight of a man who heard everything and acknowledged nothing. He set a glass in front of Aurora without asking. House red. He'd learned her order in the first week and never once got it wrong. "You two know each other," he said. Not a question. "From a long time ago." Eva's eyes hadn't left Aurora's face. "Cardiff." Silas nodded once and withdrew to the far end, polishing a glass that didn't need it, close enough to pour, far enough to pretend he wasn't listening. Aurora wrapped both hands around the wine. "You look different." "So do you. You look—" Eva stopped, started again. "You look like you've been somewhere." "I've been here. London. Soho." She gestured at the bar, the maps yellowing on the walls, the dim brass lamps. "For a while now." "I wrote to you. After you left." Eva turned her glass a quarter-turn on the bar. "After Cardiff. I didn't have an address, just the old email. It bounced back." "I closed it." "You closed everything." There it was. The thing under the surface, breaking through fast, the way it always had with Eva, who'd never learned the art of letting a thing sit. Aurora drank. The wine was warm and slightly sour and exactly what she expected. "You told me to leave," Aurora said. "That's the thing people forget. You're the one who put me on the train." "I told you to leave him." Eva's voice dropped. "Evan. I didn't tell you to vanish off the face of the earth. There's a difference, Rory. I waved you off at the platform thinking I'd see you that Christmas." Aurora looked at the ranked bottles behind the bar, the way the light moved through them. Eight years compressed into a glass of cheap red and the smell of someone else's rain. "It wasn't clean," she said. "Leaving. You don't leave a man like that clean. There's a tail. You cut everything or you cut nothing." "And so you cut me." "I cut everyone." She finally turned to look at her friend properly. The girl who'd hauled her out of a flat at two in the morning with a split lip and a bag half-packed. Who'd driven her to the station with the heater broken, both of them in coats, breath fogging. "It wasn't personal. That's the awful part. There was nothing personal left in me to cut with." Eva absorbed this. She'd come up softer in some ways and harder in others; Aurora could see it in the set of her jaw, the expensive coat, the wedding band she kept turning round and round. "I got married," Eva said. "I can see." "Two kids. A house in Bristol with a garden the size of a beermat." A small laugh, this one real. "Mortgage that'll outlive me. I do marketing. Can you believe it? Me. I sit in meetings and I say words like *engagement* and *funnel* and nobody laughs because they all believe in it." "You wanted to be a journalist." "I wanted a lot of things." Eva's smile thinned. "You wanted to be a barrister." "No." Aurora shook her head. "My father wanted me to be a barrister. I wanted to be anywhere he wasn't. Turns out I got that." The silence stretched. Somewhere behind the bar Silas turned a page of the newspaper he wasn't reading. "What do you do now?" Eva asked. "If not law." "I deliver food." She watched Eva's face for the flinch and there it was, quick, suppressed, the recalibration. "Chinese. There's a restaurant down the road. Golden Empress. I take the bag, I ride the bike, I knock on doors. People don't look at you. It's restful, not being looked at." "Rory." Eva set her glass down. "You were the cleverest person I ever met. You used to take apart arguments like they were— you used to win things just by talking." "I know what I used to be." "Then what happened?" Aurora considered the question. The honest answer was a corridor of years she didn't want to walk down with the lights on. The flat in Cardiff. The slow erosion, the way Evan had taken her in pieces so small she hadn't noticed any single one going until she looked in the mirror and there was nothing recognisable left. The train. The bedsits. The slow accretion of a smaller life, built deliberately low to the ground so nothing could knock it over. "I got tired," she said. "Of being the cleverest person in the room. Clever didn't save me from anything. Clever just meant I understood exactly what was happening to me while it happened." Eva's eyes went bright. She blinked it back, hard, the way she always had. "I should have come after you," she said. "I keep thinking that. I had your sister's number for a while. I never rang it. I told myself you'd surface when you were ready, and then a year went, and then it got embarrassing, the not-ringing, and then it just became— the way things were." "You don't owe me a chase, Eva." "I owe you a Christmas. I owe you about eight of them." Aurora found, to her irritation, that her throat had closed. She drank to clear it. Silas, without looking up, slid the bottle a few inches closer along the bar, and that small mercy almost undid her more than anything Eva had said. "You found me anyway," she managed. "Quite by accident." "My train's delayed. I saw the green sign. I thought— a quiet drink." Eva laughed, wet and astonished. "Eight years. And it's a delayed train at Paddington that does it." "That's London for you." Aurora turned her stool to face her fully now, the wine warming her hands. "Tell me about the kids. The beermat garden. All of it. I've got nowhere to be and the rain's not stopping."
created_at"2026-06-01T11:51:15.767Z" 6/1/2026, 11:51:15 AM
model"anthropic/claude-4.8-opus-20260528"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1401
moderation_latency(null)
generation_time40345
tokens_prompt1094
tokens_completion1671
native_tokens_prompt1548
native_tokens_completion2227
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"
usage0.063415
router(null)
provider_responses
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is_byokfalse
latency1398
model_permaslug"anthropic/claude-4.8-opus-20260528"
provider_name"Anthropic"
status200
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http_referer(null)
request_id"req-1780314675-VIw6qz65y3fQc9JVwc1o"
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api_type"completions"
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upstream_id"msg_016yLfqdGyKBb8mV7BifTsFn"
total_cost0.063415
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provider_name"Anthropic"
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Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags21
adverbTagCount0
adverbTags(empty)
dialogueSentences56
tagDensity0.375
leniency0.75
rawRatio0
effectiveRatio0
91.36% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1158
totalAiIsmAdverbs2
found
0
adverb"slightly"
count1
1
adverb"deliberately"
count1
highlights
0"slightly"
1"deliberately"
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)
wordCount1158
totalAiIsms2
found
0
word"weight"
count1
1
word"silence"
count1
highlights
0"weight"
1"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
narrationSentences65
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences65
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences98
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen47
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords2
totalWords1158
ratio0.002
matches
0"engagement"
1"funnel"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions36
wordCount652
uniqueNames7
maxNameDensity2.3
worstName"Eva"
maxWindowNameDensity4
worstWindowName"Eva"
discoveredNames
Raven1
Nest1
Aurora13
Silas4
Eva15
Cardiff1
Evan1
persons
0"Raven"
1"Nest"
2"Aurora"
3"Silas"
4"Eva"
5"Evan"
places
0"Cardiff"
globalScore0.35
windowScore0.333
80.56% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences36
glossingSentenceCount1
matches
0"as if checking it was still attached"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1158
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences98
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs47
mean24.64
std19.65
cv0.798
sampleLengths
058
116
21
362
41
514
616
743
810
912
1027
1110
1215
1324
1430
153
163
1742
1821
1939
2032
2124
225
2368
2436
255
263
2753
286
2915
3025
3117
3210
3350
3431
357
363
3781
3833
3914
4054
417
4212
4342
449
4530
4639
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences65
matches(empty)
86.04% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs117
matches
0"wasn't listening"
1"wasn't reading"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences98
ratio0.01
matches
0"She'd come up softer in some ways and harder in others; Aurora could see it in the set of her jaw, the expensive coat, the wedding band she kept turning round and round."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount654
adjectiveStacks0
stackExamples(empty)
adverbCount23
adverbRatio0.035168195718654434
lyAdverbCount7
lyAdverbRatio0.010703363914373088
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences98
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences98
mean11.82
std9.21
cv0.779
sampleLengths
019
126
24
39
416
51
615
72
821
911
103
1110
121
138
146
1514
162
1717
1810
192
2014
217
223
2311
241
2527
267
273
289
296
3020
314
3216
3314
343
353
363
3725
382
3912
407
4114
429
4330
4416
4516
465
4719
485
4912
65.99% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.4387755102040816
totalSentences98
uniqueOpeners43
64.10% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences52
matches
0"Somewhere behind the bar Silas"
ratio0.019
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount10
totalSentences52
matches
0"She wanted one drink."
1"She didn't notice the woman"
2"He set a glass in"
3"He'd learned her order in"
4"She gestured at the bar,"
5"She finally turned to look"
6"She'd come up softer in"
7"She watched Eva's face for"
8"She blinked it back, hard,"
9"She drank to clear it."
ratio0.192
27.31% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount45
totalSentences52
matches
0"The green neon hummed above"
1"Aurora ducked inside, shaking rain"
2"She wanted one drink."
3"She didn't notice the woman"
4"The voice did something to"
5"The woman two stools down"
6"A tailored coat."
7"Lines around the mouth that"
8"Eva laughed, and the laugh"
9"Aurora touched her own hair"
10"Silas drifted over with the"
11"He set a glass in"
12"He'd learned her order in"
13"Eva's eyes hadn't left Aurora's"
14"Silas nodded once and withdrew"
15"Aurora wrapped both hands around"
16"Eva stopped, started again"
17"She gestured at the bar,"
18"Eva turned her glass a"
19"The thing under the surface,"
ratio0.865
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences52
matches(empty)
ratio0
85.71% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences25
technicalSentenceCount2
matches
0"Silas drifted over with the slow, deliberate weight of a man who heard everything and acknowledged nothing."
1"Silas nodded once and withdrew to the far end, polishing a glass that didn't need it, close enough to pour, far enough to pretend he wasn't listening."
53.57% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags21
uselessAdditionCount3
matches
0"Eva laughed, and the laugh broke halfway"
1"She gestured, the maps yellowing on the walls, the dim brass lamps"
2"Aurora turned, the wine warming her hands"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags9
fancyCount2
fancyTags
0"Eva laughed (laugh)"
1"Eva laughed (laugh)"
dialogueSentences56
tagDensity0.161
leniency0.321
rawRatio0.222
effectiveRatio0.071
85.9780%