Run: 2026-07-25-01KYCPWQ6R01AA7DPDF2ZNT27S

Run Details

Duration:
43.8s
Cost:
$0.066715
Provider:
Amazon Bedrock

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 rain had followed Aurora down Frith Street, that fine London drizzle that doesn't fall so much as hang in the air waiting for someone to walk through it. She shouldered the door of the Nest open with her hip, both arms full of paper bags from the Golden Empress, and the green neon threw its sick underwater light across her wet shoulders. "Silas. Table four wanted extra chilli oil, and I put it in, but I'm telling you now they didn't order it, so if they complain—" "Rory." Something in the way he said it made her look up. Silas stood behind the bar with a glass in one hand and a cloth in the other, not moving, which for him was a sentence in itself. His eyes went past her, to the far corner where the old maps gave way to the black-and-white photographs, and Aurora followed the line of them. A woman sat alone at the corner table with a glass of red wine she hadn't touched. Grey wool coat, still on. Hair scraped back so tight it pulled at her temples. Fifty, maybe. Expensive shoes, and one heel tapping the floor in a rhythm that had nothing to do with the music. Aurora put the bags on the bar very carefully, like they might go off. "How long has she been here?" "Forty minutes. Asked for you by name." Silas set the glass down. "Not the name you use for deliveries." The woman looked up then. There was a half-second where nothing happened in her face at all, and then it came apart — the mouth first, then the eyes, and she pressed the back of her hand to her lips as though she'd tasted something. "Oh," she said. "Oh, God. Rory." Aurora crossed the room. Her wet trainers squeaked on the boards, and she was aware of it, and of the grease spot on her sleeve, and of the fact that her hair was flat to her skull. "Eva." "Don't." Eva laughed, and it was wrong — pitched too high, cut off too fast. "Don't say it like that. Like you're identifying a body." "I've been trying to reach you for four years." "I know." "Christmas cards. Two birthdays. I rang your mother." "She told me." Eva pushed the wine glass an inch to the left, then an inch back. "She said you sounded well. She said you sounded like you'd stopped smoking." "I have." "There you are, then." Eva gestured at the chair opposite. "She's never wrong about anything. It's insufferable." Aurora sat. Behind her she heard Silas move down the bar, further away, giving them the length of the room, and she loved him a little for it. Eva had been the loudest person Aurora had ever known. That was the thing. Eva Bekele, who at nineteen had climbed the scaffolding on the science block at three in the morning to hang a bedsheet that said SEND HELP; who'd once talked a bouncer in Splott into letting them both in free by convincing him she was a food safety inspector. She had laughed with her whole ribcage. She had never once in her life kept her coat on indoors. "You look—" Aurora started. "Careful." "Different." "That's the coward's version." Eva smiled without any teeth. "Say thinner. Everyone wants to say thinner." "I was going to say expensive." The smile went somewhere real for a moment. "Now that's better. That's the Rory I remember. Straight to the throat, and then you'd look surprised that anyone bled." "I don't do that." "You absolutely do that." Eva finally drank. She grimaced. "This wine is dreadful." "It's a Soho bar." "It's a Soho bar with maps of Bosnia on the wall and a man behind the counter who's clocked both exits three times since I sat down." Eva's eyes flicked up, quick and bright. "You've got interesting friends now." "He's my landlord." "He's your landlord." "And he makes a decent Old Fashioned, and he doesn't ask questions." Aurora leaned back. "It's a rare combination. Where do you live?" "Dubai. Two years. Before that Singapore." Eva turned her glass by the stem. "I run compliance for a bank whose name you'd recognise and whose ethics you wouldn't. Forty-one floors up. There's a woman who comes to water my plants and I have never once met her." "You hated banks." "I hated a lot of things. It was a personality." She said it flatly, the way you'd read a line from a form. "Then I got a mortgage." The rain ticked at the window. Someone put money in the jukebox and Nina Simone came on low, and Eva's heel stopped tapping for the first time. "You didn't come to the funeral," Aurora said. There it was. She hadn't planned to put it down on the table so early, but there it was, and Eva didn't flinch, which was somehow worse than if she had. "No." "He was your godfather." "He was my father's business partner who bought me a violin I didn't want." Eva looked at the wall, at a photograph of a bridge somewhere with the arch blown out of the middle of it. "I was in a hotel in Zurich. I know what floor. I know what I ordered from the room service menu. I don't know why I didn't get on the plane." "I stood in that church for an hour and a half looking at the door." "I know." "I had your coat," Aurora said. "The green one. I'd taken it back from the dry cleaners because I thought — I thought you'd come, and it'd be cold, and you never bring a coat. I sat there with a coat on my lap for an hour and a half." Her voice did something she hadn't authorised, and she stopped, and breathed. "That's the bit I can't get past. Not the funeral. The coat." Eva's hands had gone still on the table. Long fingers. A wedding band Aurora hadn't noticed, thin and worn. "I got married," Eva said. "Two years ago. In a registry office in Colombo with two witnesses we paid for." "Congratulations." "Don't." "I meant it." "That's why don't." Eva pressed her thumb hard against the base of her ring finger. "You'd have made it funny. You'd have stood up and told everyone about the scaffolding and the bedsheet and my mother would have wanted to die, and it would have been the best night of my life. I sent you an invitation. I wrote it out. I put your address on it — the old one, the one in Cardiff, which tells you how long I'd been not-thinking about you. And then I put it in a drawer." "Why?" "Because you left him." Eva's chin came up. "Because I told you to come to London, and you came, and you got out, and then every time I thought about ringing you I could hear how you sounded on the phone that night, and I could hear myself telling you to run, and I couldn't work out how a person is supposed to follow that. What comes after that? Hello, how are you, I've bought a flat with a doorman?" Aurora looked at her. Really looked — at the scraped-back hair and the coat still buttoned and the shoes that cost more than a month of deliveries. "You could have started with hello," she said. "Yes." Eva's throat moved. "Yes. I could have started there."
created_at"2026-07-25T13:19:34.623Z" 7/25/2026, 1:19:34 PM
model"anthropic/claude-opus-5-20260723"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency1641
moderation_latency(null)
generation_time43741
tokens_prompt1063
tokens_completion1718
native_tokens_prompt1548
native_tokens_completion2359
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"
usage0.066715
router(null)
provider_responses
0
endpoint_id"76cb4608-f48c-483d-8da8-9957fb44244e"
id"msg_011CdNqrKZvRKxRMr9r9Q1NR"
is_byokfalse
latency1641
model_permaslug"anthropic/claude-opus-5-20260723"
provider_name"Amazon Bedrock"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1784985574-lqI1yZrCCtTh3CzSmq6A"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784985574-oJNIcwGL77LzSC02AhV7"
upstream_id"msg_011CdNqrKZvRKxRMr9r9Q1NR"
total_cost0.066715
cache_discount(null)
upstream_inference_cost0
provider_name"Amazon Bedrock"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags20
adverbTagCount1
adverbTags
0"Aurora leaned back [back]"
dialogueSentences63
tagDensity0.317
leniency0.635
rawRatio0.05
effectiveRatio0.032
87.96% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1246
totalAiIsmAdverbs3
found
0
adverb"very"
count1
1
adverb"carefully"
count1
2
adverb"really"
count1
highlights
0"very"
1"carefully"
2"really"
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)
91.97% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1246
totalAiIsms2
found
0
word"absolutely"
count1
1
word"flicked"
count1
highlights
0"absolutely"
1"flicked"
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
narrationSentences54
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences54
filterMatches
0"look"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences96
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen78
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1251
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions19
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions42
wordCount641
uniqueNames13
maxNameDensity2.65
worstName"Eva"
maxWindowNameDensity5.5
worstWindowName"Eva"
discoveredNames
Aurora12
Frith1
Street1
London1
Nest1
Golden1
Empress1
Eva17
Silas3
Bekele1
Splott1
Nina1
Simone1
persons
0"Aurora"
1"Nest"
2"Eva"
3"Silas"
4"Bekele"
5"Nina"
6"Simone"
places
0"Frith"
1"Street"
2"London"
3"Golden"
4"Splott"
globalScore0.174
windowScore0
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
wordCount1251
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences96
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs58
mean21.57
std23.39
cv1.084
sampleLengths
063
125
21
311
453
553
614
76
819
945
106
1137
121
1325
149
152
168
1730
182
1917
2028
2181
224
231
241
2516
266
2728
284
2913
304
3139
323
333
3423
3547
363
3728
3827
398
4031
411
424
4367
4415
452
4674
4719
4820
491
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences54
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs104
matches(empty)
23.81% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount3
semicolonCount1
flaggedSentences4
totalSentences96
ratio0.042
matches
0"There was a half-second where nothing happened in her face at all, and then it came apart — the mouth first, then the eyes, and she pressed the back of her hand to her lips as though she'd tasted something."
1"\"Don't.\" Eva laughed, and it was wrong — pitched too high, cut off too fast."
2"Eva Bekele, who at nineteen had climbed the scaffolding on the science block at three in the morning to hang a bedsheet that said SEND HELP; who'd once talked a bouncer in Splott into letting them both in free by convincing him she was a food safety inspector."
3"Really looked — at the scraped-back hair and the coat still buttoned and the shoes that cost more than a month of deliveries."
95.48% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount642
adjectiveStacks0
stackExamples(empty)
adverbCount29
adverbRatio0.045171339563862926
lyAdverbCount5
lyAdverbRatio0.00778816199376947
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences96
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences96
mean13.03
std14.46
cv1.11
sampleLengths
029
134
225
31
411
527
626
717
85
910
102
1119
1214
136
1412
157
165
1740
183
193
204
2133
221
2315
2410
259
262
278
2817
2913
302
3110
327
332
3426
3510
364
3748
387
3912
404
411
421
439
447
456
468
4720
484
497
62.85% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.4583333333333333
totalSentences96
uniqueOpeners44
75.76% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences44
matches
0"Really looked — at the"
ratio0.023
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount8
totalSentences44
matches
0"She shouldered the door of"
1"His eyes went past her,"
2"Her wet trainers squeaked on"
3"She had laughed with her"
4"She had never once in"
5"She said it flatly, the"
6"She hadn't planned to put"
7"Her voice did something she"
ratio0.182
28.18% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount38
totalSentences44
matches
0"The rain had followed Aurora"
1"She shouldered the door of"
2"Something in the way he"
3"Silas stood behind the bar"
4"His eyes went past her,"
5"A woman sat alone at"
6"Hair scraped back so tight"
7"Aurora put the bags on"
8"Silas set the glass down"
9"The woman looked up then."
10"Aurora crossed the room."
11"Her wet trainers squeaked on"
12"Eva laughed, and it was"
13"Eva pushed the wine glass"
14"Eva gestured at the chair"
15"Eva had been the loudest"
16"That was the thing."
17"Eva Bekele, who at nineteen"
18"She had laughed with her"
19"She had never once in"
ratio0.864
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences44
matches(empty)
ratio0
63.49% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences18
technicalSentenceCount2
matches
0"There was a half-second where nothing happened in her face at all, and then it came apart — the mouth first, then the eyes, and she pressed the back of her hand…"
1"Eva Bekele, who at nineteen had climbed the scaffolding on the science block at three in the morning to hang a bedsheet that said SEND HELP; who'd once talked a…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags20
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags8
fancyCount2
fancyTags
0"Eva laughed (laugh)"
1"Eva pressed (press)"
dialogueSentences63
tagDensity0.127
leniency0.254
rawRatio0.25
effectiveRatio0.063
84.3166%