Run: 2026-10-08-01M4E01EE4RHCN5G0H21HY81Z7

Run Details

Duration:
16.1s
Cost:
$0.001320
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="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 above the door buzzed its usual tune, a flicker that caught on the second syllable, and Rory almost turned around. She had come in for one gin and a seat with its back to the wall. Instead, the woman at the far end of the bar lifted her head from a glass of red wine, and the whole evening tipped sideways. Eva Morgan had cut her hair. The waves that used to fall past her shoulders in Cardiff were gone, replaced by a sharp bob the colour of wet sand. She wore a camel coat folded across the next stool like a guard dog, and a thin gold band sat on her left hand where nothing had sat before. "Don't do that," Eva said. "Do what?" "The face. The one where you're working out the nearest exit." Eva slid off her stool. Her heels clicked on the old boards. "Hello, Rory." Rory crossed the room slower than she meant to. Up close, Eva smelled of cold air and something expensive. "You're in London." "I've been in London for six years. You'd know that if you'd answered a single letter." Behind the bar, Silas set down a tumbler without a sound. He took in the two of them with the same unhurried attention he gave to a drunk asking for the bathroom, then reached for the Hendrick's without being asked. "Drink's on the house, Rory. Looks like you'll need it." "Thanks, Si." "Don't thank me yet," he said, and limped off toward the cellar stairs, his bad knee taking the steps one at a time. Rory sat. Eva stayed standing for a moment, then sat too, leaving a stool's width between them. "You look good," Eva said. "I look like someone who carries cases of tonic water up a flight of stairs for a living." "You still look like you could talk your way out of a locked car." "That was once." "It was twice, and you know it." Eva turned her glass by its stem. "You rang me from a service station on the M4 at four in the morning. You were crying so hard I had to ask you three times where you were." Rory picked up the gin. The ice had started to melt into it, watering it down. "I didn't think you'd come." "I didn't come. I was already in the car. I was driving to get you when you told me not to." Eva's mouth tightened. "You said, Eva, don't you dare. Then you hung up, and I didn't hear from you for eleven months." "I was sorting myself out." "Were you?" The question sat between them. Somewhere behind the bookshelf in the back, a door opened and shut, and a murmur of voices drifted through, then faded. Rory had never once asked about that room. Silas never once offered. "I got your postcards," Rory said quietly. "Every one. I kept them in a shoebox under the bed. I read them when I couldn't sleep." "That's not the same as writing back." "No." Eva laughed, but there was no warmth in it. "Christ, Rory. You always did that. You take the thing that's true and you say it so flatly that nobody can argue, and then you expect them to just stand there." "What did you want me to say? That I was scared? That I couldn't look at a phone without seeing his name on it? That every time someone in Cardiff said my surname in the market, I went cold?" "I wanted you to say something." Eva's voice cracked and she pressed her lips together until it smoothed out again. "I stood in that flat with the bruises on your arms and I told you to pack a bag. I took you to London with nothing but the clothes on your back. And then you just... went quiet on me." Rory looked down at the scar on her left wrist, the pale crescent that had never quite faded. She turned it toward the light out of habit. "You should have let me stay in the car that night." "Don't you say that." "I'm saying it because it's true." Eva raised her hand and then let it drop onto the bar, the gold band catching the green glow. "I got married last spring. Her name's Imogen. She teaches sixth form chemistry in Islington. She knows about you. She asked me once if I missed Cardiff, and I said there's nothing there I miss except the girl who used to sit on the wall outside the library and finish my sandwiches." "Eva." "Don't Eva me. I'm not here to make you feel better." "Then why are you here?" Eva met her eyes, and for the first time since she had stood up from her stool, she looked her age. "Because I saw your name in the local paper last month. A delivery driver put out a fire in a kitchen in Chinatown. They printed your picture. You looked like someone I used to know, and I thought, if I don't go and see for myself, I'll spend the rest of my life wondering." Rory set the glass down. Above them, a floorboard creaked in the flat she rented, the one that sat above the bar, and she heard her own footsteps in it that morning, quiet and careful, the way she always walked when she wasn't sure who else was listening. "Well," she said. "Now you've seen."
created_at"2026-10-08T14:52:52.047Z" 10/8/2026, 2:52:52 PM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency16080
moderation_latency(null)
generation_time16096
tokens_prompt1063
tokens_completion1401
native_tokens_prompt1550
native_tokens_completion2330
native_tokens_completion_images(null)
native_tokens_reasoning710
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"
usage0.00132
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791471172-VUuFZhiHaKLktOTYrq1k"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791471172-zRu3N5CRYnPQwSFgDbDs"
upstream_id"msg_011Cfpxdb5pH4PAb5DHepT8b"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011Cfpxdb5pH4PAb5DHepT8b"
is_byokfalse
latency1250
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.00132
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
adverbTagCount1
adverbTags
0"Rory said quietly [quietly]"
dialogueSentences38
tagDensity0.237
leniency0.474
rawRatio0.111
effectiveRatio0.053
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount914
totalAiIsmAdverbs0
found(empty)
highlights(empty)
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)
83.59% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount914
totalAiIsms3
found
0
word"flicker"
count1
1
word"warmth"
count1
2
word"footsteps"
count1
highlights
0"flicker"
1"warmth"
2"footsteps"
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
narrationSentences35
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences35
filterMatches(empty)
hedgeMatches
0"started to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences64
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen54
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords914
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions16
unquotedAttributions0
matches(empty)
13.64% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions25
wordCount440
uniqueNames6
maxNameDensity2.73
worstName"Eva"
maxWindowNameDensity4.5
worstWindowName"Eva"
discoveredNames
Rory8
Morgan1
Cardiff1
Eva12
Silas2
Hendrick1
persons
0"Rory"
1"Morgan"
2"Eva"
3"Silas"
4"Hendrick"
places
0"Cardiff"
globalScore0.136
windowScore0.167
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences24
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount914
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences64
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs36
mean25.39
std22.01
cv0.867
sampleLengths
064
158
25
32
425
522
616
750
82
923
1022
1118
1214
133
1444
1521
1643
175
182
1938
2025
217
221
2340
2439
2560
2638
274
286
2971
301
3111
325
3375
3448
356
85.21% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences35
matches
0"were gone"
1"being asked"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs76
matches
0"was listening"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences64
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount440
adjectiveStacks0
stackExamples(empty)
adverbCount16
adverbRatio0.03636363636363636
lyAdverbCount1
lyAdverbRatio0.0022727272727272726
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences64
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences64
mean14.28
std12.33
cv0.863
sampleLengths
023
116
225
36
423
529
65
72
816
97
102
119
1210
133
1416
1511
1629
1710
182
1923
202
2115
225
2318
2414
253
2614
2730
285
2911
305
3124
3219
335
342
355
3621
378
384
397
4018
417
421
439
4431
4539
4620
4740
4818
499
75.00% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.46875
totalSentences64
uniqueOpeners30
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences31
matches
0"Instead, the woman at the"
1"Somewhere behind the bookshelf in"
ratio0.065
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount6
totalSentences31
matches
0"She had come in for"
1"She wore a camel coat"
2"Her heels clicked on the"
3"He took in the two"
4"he said, and limped off"
5"She turned it toward the"
ratio0.194
40.65% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount26
totalSentences31
matches
0"The green neon above the"
1"She had come in for"
2"Eva Morgan had cut her"
3"The waves that used to"
4"She wore a camel coat"
5"Eva slid off her stool"
6"Her heels clicked on the"
7"Rory crossed the room slower"
8"He took in the two"
9"he said, and limped off"
10"Eva stayed standing for a"
11"Eva turned her glass by"
12"Rory picked up the gin."
13"The ice had started to"
14"Eva's mouth tightened"
15"The question sat between them."
16"Rory had never once asked"
17"Silas never once offered."
18"Rory said quietly"
19"Eva laughed, but there was"
ratio0.839
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences31
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences15
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences38
tagDensity0.132
leniency0.263
rawRatio0
effectiveRatio0
89.9361%