Run: 2026-10-09-01M4FXYJBTBME5PJNWXKBDGE2M

Run Details

Duration:
13.2s
Cost:
$0.001138
Provider:
Claude Platform on AWS

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="4415" name="Lucien Moreau" aliases="Lucien, Luc, the Frenchman" pronouns="he/him" species="Half-Demon" storyRole="Ally"> <eyeColor>heterochromatic — one amber, one black</eyeColor> <hair>slicked-back platinum blond</hair> <height>5'11"</height> <age>32</age> <cane>ivory-handled cane that conceals a thin blade</cane> <dress>tailored charcoal suits</dress> <description>An impeccably dressed fixer and information broker in London's supernatural underworld. He speaks four languages fluently.</description> <backstory>Born in Marseille to a human mother and a demon father from the realm of Avaros.</backstory> </character> <location id="858" name="Eva's Flat" aliases="Eva's place, the flat on Brick Lane" realm="Earth"> <cat>tabby cat named Ptolemy</cat> <security>three deadbolts on the front door</security> <description>A cramped one-bedroom flat above a curry house on Brick Lane, East London. Every surface is covered with books, scrolls, and research notes.</description> </location> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the romance genre. Two people who parted on complicated terms are forced together again when one shows up unannounced at the other's flat. There's history between them — attraction, hurt, and things left unsaid. Write the scene from the moment the door opens. 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 third deadbolt gave with a reluctant clack, and Aurora hauled the door open before her nerve could catch up with her hand. Lucien stood on the landing, one palm resting on the ivory knob of his cane. The stairwell light caught his hair and turned it the colour of old pennies. One eye was amber, one black, and both were fixed on her face with the patience of a man who had expected to wait longer. "Rory," he said. "You can't just turn up here." "I knocked. Twice. You are the one who took her time." Behind her, Ptolemy padded across a stack of Eva's research notes, tail high, and wound around her ankles. The cat stopped, sniffed the air toward the landing, and sat down with the air of a creature who had already decided how this would end. "Eva's not here," Aurora said. "I know. She's in Edinburgh until Thursday, reading something dull about Norse runes." He tilted his head. "I came to see you." "How did you know I'd be here?" "Because you have nowhere else to go that you would admit to, and because Silas told me you stopped sleeping above the bar after the Tuesday fire." His mouth moved into something that was not quite a smile. "He is a terrible liar when he is worried about someone." She should have shut the door. She could feel the weight of the deadbolts in her hand, the cold steel of them, and she did not move. "Silas talks too much." "Silas is a bartender. It is the job." Lucien shifted his weight, and the cane tapped once against the threshold. "May I come in, or do we conduct this conversation through a crack in a door like a pair of Victorian spinsters?" "Say what you came to say first." "I came to say I was wrong." The words landed harder than any of the ones he'd thrown at her six months ago, when he had stood in her kitchen above the bar and told her, very calmly, that the arrangement with the Vauxhall brokers could not be undone. She had asked him to pick a side. He had picked the one that paid his debts. "Wrong about what?" she said. "About letting you walk out of the room." "You didn't let me do anything. You just stopped answering the phone." Something flickered across his face, quick as a blade drawn and sheathed. "Yes. That was the cowardly part." She laughed, short and unhappy. "That's the first honest thing you've said in months." "Then let me say another." He stepped closer, close enough that she could smell him: cedar and cold rain, and underneath that the sharp metallic tang that always clung to half-demons when they were tired. "I have not slept properly since the night I left. Every time I close my eyes I am standing in that hallway with you looking at me like I am a stranger. And I deserved it." Aurora gripped the edge of the door until her knuckles ached. The small crescent scar on her left wrist pressed against her pulse, a reminder she had never asked to be carrying. "You don't get to make me the one who forgives you." "I know." "You don't get to stand there looking like that." "Like what?" "Like you're sorry and still expecting me to fix the lock on your life." He was quiet for a moment. Then, very softly: "Would it help if I said I still want you to?" The honest answer rose up in her throat, bitter and warm at the same time, and she swallowed it down. Ptolemy stretched, yawned, and padded back into the flat, leaving them on the threshold with nothing between them but the open door and the cold draught from the stairwell. "Come in," she said, stepping aside. "But you're making the tea, and you're telling me everything. Every name, every deal, every lie you told Eva about where you were that night." Lucien's eyes, one amber and one black, went dark with something she refused to name. He lifted his cane and crossed the threshold. "Every name," he agreed. "I will start with the one that matters most."
created_at"2026-10-09T08:54:49.473Z" 10/9/2026, 8:54:49 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2402
moderation_latency(null)
generation_time13217
tokens_prompt1004
tokens_completion1140
native_tokens_prompt1469
native_tokens_completion1983
native_tokens_completion_images(null)
native_tokens_reasoning714
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"
usage0.0011384
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791536089-ADmMIlq2zxb9OMdxqNbz"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791536089-hklQWBah7ulxAZFcU7IR"
upstream_id"msg_011CfrP8vKobxpaBZ75ex889"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfrP8vKobxpaBZ75ex889"
is_byokfalse
latency730
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0011384
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
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags9
adverbTagCount0
adverbTags(empty)
dialogueSentences31
tagDensity0.29
leniency0.581
rawRatio0
effectiveRatio0
78.69% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount704
totalAiIsmAdverbs3
found
0
adverb"very"
count2
1
adverb"softly"
count1
highlights
0"very"
1"softly"
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
57.39% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount704
totalAiIsms6
found
0
word"could feel"
count1
1
word"weight"
count2
2
word"flickered"
count1
3
word"pulse"
count1
4
word"reminder"
count1
highlights
0"could feel"
1"weight"
2"flickered"
3"pulse"
4"reminder"
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
narrationSentences30
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences30
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences51
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen42
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords704
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions15
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions10
wordCount406
uniqueNames5
maxNameDensity0.74
worstName"Aurora"
maxWindowNameDensity1
worstWindowName"Aurora"
discoveredNames
Aurora3
Ptolemy2
Eva1
Vauxhall1
Lucien3
persons
0"Aurora"
1"Ptolemy"
2"Eva"
3"Lucien"
places(empty)
globalScore1
windowScore1
36.36% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences22
glossingSentenceCount1
matches
0"not quite a smile"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount704
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences51
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs32
mean22
std18.95
cv0.861
sampleLengths
023
154
23
36
411
544
65
722
87
949
1027
114
1242
137
147
1559
165
178
1812
1918
2014
2171
2243
232
249
252
2614
2720
2849
2931
3023
3113
93.57% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences30
matches
0"were fixed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs66
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences51
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount407
adjectiveStacks0
stackExamples(empty)
adverbCount14
adverbRatio0.0343980343980344
lyAdverbCount2
lyAdverbRatio0.004914004914004914
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences51
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences51
mean13.8
std9.79
cv0.709
sampleLengths
023
115
214
325
43
56
611
718
826
95
1017
115
127
1338
1411
156
1621
174
1820
1922
207
217
2242
238
249
255
268
2712
2812
296
305
319
3235
3336
3411
3521
3611
372
389
392
4014
416
4214
4320
4429
456
4625
4715
488
494
80.39% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.5294117647058824
totalSentences51
uniqueOpeners27
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences26
matches
0"Then, very softly:"
ratio0.038
50.77% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount11
totalSentences26
matches
0"He tilted his head"
1"His mouth moved into something"
2"She should have shut the"
3"She could feel the weight"
4"She had asked him to"
5"He had picked the one"
6"She laughed, short and unhappy."
7"He stepped closer, close enough"
8"He was quiet for a"
9"she said, stepping aside"
10"He lifted his cane and"
ratio0.423
17.69% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount23
totalSentences26
matches
0"The third deadbolt gave with"
1"Lucien stood on the landing,"
2"The stairwell light caught his"
3"The cat stopped, sniffed the"
4"He tilted his head"
5"His mouth moved into something"
6"She should have shut the"
7"She could feel the weight"
8"Lucien shifted his weight, and"
9"The words landed harder than"
10"She had asked him to"
11"He had picked the one"
12"Something flickered across his face,"
13"She laughed, short and unhappy."
14"He stepped closer, close enough"
15"Aurora gripped the edge of"
16"The small crescent scar on"
17"He was quiet for a"
18"The honest answer rose up"
19"Ptolemy stretched, yawned, and padded"
ratio0.885
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences26
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences14
technicalSentenceCount0
matches(empty)
69.44% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount1
matches
0"Lucien shifted, and the cane tapped once against the threshold"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount1
fancyTags
0"he agreed (agree)"
dialogueSentences31
tagDensity0.161
leniency0.323
rawRatio0.2
effectiveRatio0.065
86.1436%