Run: 2026-10-08-01M4DA03Z9V3FGPNXA5NK8TC4E

Run Details

Duration:
15.7s
Cost:
$0.001270
Provider:
Claude Platform on AWS

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
The green neon above the door of the Raven's Nest stuttered as Aurora pushed through, the way it always did in the damp, and for a moment its light lay across the floor like something spilled. She shook the rain from her hair and looked for a place at the bar where she could be left alone. Silas glanced up from the taps, lifted two fingers in greeting, and went back to pulling a pint. He did not ask. He never did. She had her back to the room when she heard her name, though not the name anyone in London used. "Rory Carter. God help me, it is you." She turned slowly. The man on the stool beside the window had a glass of whisky sitting untouched in front of him, and it took her a second to fit the face to the boy she remembered. Owen Pryce had been all elbows and cheap cologne at sixteen, a boy who laughed too loudly on the back wall of the comprehensive in Grangetown and who once walked her home in a thunderstorm, soaked to the skin, pretending he wasn't frightened of the dark. The man in front of her had the same eyes, pale and quick, but the rest had been pressed into something harder. The suit was good. The hands were thinner. There was a grey thread at his temple that had no business being there at thirty. "Owen," she said. "Hello." "Hello." He smiled, and the smile was the first thing that felt true. "I heard you'd gone to London. Your mam said. I never thought I'd see you in a place like this, though. You always said bars were where people went to lie to themselves." "I still think that. I just pay rent in them now." She slid onto the stool next to him without being invited, because she was tired and because there was an old familiarity she couldn't quite refuse. "What are you doing in Soho?" "Work. Sort of." He turned the glass a quarter turn on its mat. "I'm a solicitor in Canary Wharf. Commercial litigation. I bill more in a day than my dad earned in a month, and I hate it, and I'm very good at it." "That sounds like a sentence someone practised." "It was." He laughed, but it came out short. "You're supposed to be the one who finished the degree. Pre-law, wasn't it? You were going to be the barrister in the family. Brendan's clever girl." The old wound was there, small and familiar, a splinter she'd long stopped noticing until someone pressed on it. "I left the course. Dad didn't speak to me for a year. Mam pretended he wasn't being unreasonable." "I'm sorry." "Don't be. I don't think I'd have liked who I'd have become if I'd stayed." She heard how that sounded and tried to soften it. "I deliver food now. Mostly for a Chinese place on Frith Street. The owner calls me the only honest person in Soho because I always return the change." He studied her with an attention that made her want to look away. She didn't. Instead she noticed what she had not let herself notice in the first minute: the way his right hand kept drifting toward his jacket pocket, as if reaching for something that was no longer there, and the faint tremor when he set the glass down. "Owen," she said quietly. "What happened?" For a while he didn't answer. Behind them someone laughed at a table of students, and Silas set a fresh bottle on the shelf with a soft clink. Rain ticked on the window. "Nothing that makes a good story," he said finally. "I drank for two years after my divorce. Then I drank for a bit longer because I was too proud to admit I'd started again. Then my sister found me on the floor of my flat and had me admitted. I've got eleven months. Eleven months and nine days, if you're counting, and I am." She reached out before she decided to, and her hand settled over his on the bar. His skin was cold. He did not pull away. "I'm glad you're counting," she said. "You were the one who always told me to stop bloody apologising." He looked at their hands, then at her face, and something in his expression cracked open. "I should have written. After the trial. After you left Cardiff so suddenly. I thought about it every week. I kept thinking I'd have something better to say when I had myself sorted, and then years went by and I didn't know how to start." The sentence was simple, but she heard the whole of it underneath: the letter he never sent, the phone number he didn't dial, the friendship they had allowed to thin until it was only a memory of a storm and a borrowed umbrella. She had let it happen too. She had been running from so much that she had not noticed what she was leaving behind. "You could start now," she said. "Could I?" She thought of Eva, of the flat above the bar, of the way she had learned to be a different person in a city that didn't know the old one. She thought of the crescent-shaped scar on her wrist, which she sometimes touched without meaning to, the way Owen was touching the edge of his glass. "We both could," she said. "We're not who we were. Maybe that's allowed to be the thing we start with." He nodded slowly, and when he smiled again it was smaller and more careful and entirely his own. Across the room Silas lifted an eyebrow in silent question. She shook her head and turned back to her old friend, the neon light flickering over them both, and for the first time in a long while she did not feel the need to leave before the night was finished.
created_at"2026-10-08T08:27:39.889Z" 10/8/2026, 8:27:39 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2231
moderation_latency(null)
generation_time15706
tokens_prompt846
tokens_completion1454
native_tokens_prompt1240
native_tokens_completion2291
native_tokens_completion_images(null)
native_tokens_reasoning581
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"
usage0.0012695
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448059-F8gApOzg1QBSWP8MmZFQ"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448059-cawwajC0a3Cn4eGNbTIG"
upstream_id"msg_011CfpTFt52VqSGfDV9y3SUy"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpTFt52VqSGfDV9y3SUy"
is_byokfalse
latency693
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0012695
cache_discount(null)
upstream_inference_cost0
provider_name"Claude Platform on AWS"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
51.85% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags12
adverbTagCount2
adverbTags
0"she said quietly [quietly]"
1"he said finally [finally]"
dialogueSentences27
tagDensity0.444
leniency0.889
rawRatio0.167
effectiveRatio0.148
79.90% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount995
totalAiIsmAdverbs4
found
0
adverb"slowly"
count2
1
adverb"very"
count1
2
adverb"suddenly"
count1
highlights
0"slowly"
1"very"
2"suddenly"
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)
89.95% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount995
totalAiIsms2
found
0
word"familiar"
count1
1
word"eyebrow"
count1
highlights
0"familiar"
1"eyebrow"
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
narrationSentences43
matches(empty)
43.19% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount2
narrationSentences43
filterMatches
0"notice"
hedgeMatches
0"tried to"
1"happen to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences58
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen55
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords995
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions18
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions12
wordCount653
uniqueNames9
maxNameDensity0.46
worstName"Silas"
maxWindowNameDensity0.5
worstWindowName"Silas"
discoveredNames
Raven1
Nest1
Aurora1
London1
Pryce1
Grangetown1
Silas3
Eva1
Owen2
persons
0"Raven"
1"Nest"
2"Aurora"
3"Pryce"
4"Silas"
5"Eva"
6"Owen"
places
0"London"
1"Grangetown"
globalScore1
windowScore1
0.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences28
glossingSentenceCount2
matches
0"quite refuse"
1"as if reaching for something that was no longer there, and the faint tremor when he set the glass down"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount995
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences58
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs26
mean38.27
std30.69
cv0.802
sampleLengths
082
120
28
3129
44
546
643
744
87
935
1037
112
1253
1360
146
1533
1664
1725
186
1973
2066
216
222
2356
2420
2568
97.10% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences43
matches
0"been pressed"
86.04% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs117
matches
0"was leaving"
1"was touching"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences58
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount654
adjectiveStacks0
stackExamples(empty)
adverbCount24
adverbRatio0.03669724770642202
lyAdverbCount7
lyAdverbRatio0.010703363914373088
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences58
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences58
mean17.16
std13.97
cv0.814
sampleLengths
036
121
218
34
43
520
68
73
834
946
1022
114
124
1316
143
151
1613
1733
1837
196
2013
2131
227
239
2426
2519
2618
272
2825
2928
3013
312
3245
334
342
356
3622
375
389
3955
4016
414
425
436
4428
4545
4643
476
4817
496
53.45% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.41379310344827586
totalSentences58
uniqueOpeners24
87.72% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences38
matches
0"Instead she noticed what she"
ratio0.026
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount23
totalSentences38
matches
0"She shook the rain from"
1"He did not ask."
2"He never did."
3"She had her back to"
4"She turned slowly."
5"He smiled, and the smile"
6"She slid onto the stool"
7"He turned the glass a"
8"He laughed, but it came"
9"She heard how that sounded"
10"He studied her with an"
11"she said quietly"
12"he said finally"
13"She reached out before she"
14"His skin was cold."
15"He did not pull away."
16"He looked at their hands,"
17"She had let it happen"
18"She had been running from"
19"She thought of Eva, of"
ratio0.605
25.79% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount33
totalSentences38
matches
0"The green neon above the"
1"She shook the rain from"
2"Silas glanced up from the"
3"He did not ask."
4"He never did."
5"She had her back to"
6"She turned slowly."
7"The man on the stool"
8"Owen Pryce had been all"
9"The man in front of"
10"The suit was good."
11"The hands were thinner."
12"He smiled, and the smile"
13"She slid onto the stool"
14"He turned the glass a"
15"He laughed, but it came"
16"The old wound was there,"
17"She heard how that sounded"
18"He studied her with an"
19"she said quietly"
ratio0.868
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences38
matches(empty)
ratio0
35.71% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences20
technicalSentenceCount3
matches
0"Owen Pryce had been all elbows and cheap cologne at sixteen, a boy who laughed too loudly on the back wall of the comprehensive in Grangetown and who once walke…"
1"Instead she noticed what she had not let herself notice in the first minute: the way his right hand kept drifting toward his jacket pocket, as if reaching for s…"
2"She thought of Eva, of the flat above the bar, of the way she had learned to be a different person in a city that didn't know the old one."
83.33% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags12
uselessAdditionCount1
matches
0"He smiled, and the smile was the first thing that felt true"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags7
fancyCount1
fancyTags
0"He laughed (laugh)"
dialogueSentences27
tagDensity0.259
leniency0.519
rawRatio0.143
effectiveRatio0.074
77.8013%