Run: 2026-10-27-01M5YJJ0SV1HYVBPGRDQ77EP04

Run Details

Duration:
52.2s
Cost:
$0.018927
Provider:
OpenAI

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 thinned to a mist when the woman came into the Raven’s Nest. She shook out her umbrella over the mat, folded it with care and hooked it over her wrist. Silas stood behind the bar, rubbing a glass with a cloth. She looked past him at the pumps. “Half of the bitter, please. And where’s your loo?” “Down the passage, second door on the left.” She placed a pound coin on the counter beside a damp tissue. “For the drink, not the directions.” Silas took the coin. The woman had a narrow face, a pale seam through one eyebrow and silver hair cut close around her ears. Her coat hung open over a dark suit. When she turned towards the passage, he saw a small blue stain on the back of her hand, where ink had settled in a crease. “Ruth?” She stopped. Her hand went to the wall, not for support but as though she had meant to touch it all along. He put the glass down. “Ruth Hales.” She faced him again. Her mouth opened, then shut. She glanced at the door and back at his face. “Silas?” He came around the end of the bar, his left leg stiff after an afternoon on his feet. She watched the movement. Then she lifted both hands, palms towards him. “Don’t. I still need the loo.” When she came back, her beer waited on the counter beside her change. She sat on a stool and peeled the tissue off the pound coin. “You didn’t take enough.” “The prices are on the board.” “That’s a two, not a one.” She pointed at the chalk writing. “Your handwriting hasn’t improved.” He took another coin from her. She drank a mouthful and set the glass down on its mat. “You own this place?” “For eleven years.” “In Soho.” “There’s a sign outside.” “I saw the sign. I didn’t see your name on it.” “No reason you would have.” She turned the glass a quarter turn. The wet ring on the mat widened. Silas picked up the cloth again. He had seen her last at a station, though for a moment he could not remember which one. She had worn a red coat and carried a plant in a plastic bag, its leaves pressed against her chest in the crowd. Bristol. She had insisted on buying him a sandwich for the train, then argued with the man at the kiosk because the bread had curled at the edges. “What brought you here?” he asked. “I had a meeting near Tottenham Court Road. The person I was meeting chose a café with six seats and a queue at the door. We stood outside with our coffees, so I wanted a chair.” “You could have come through the door and found me at any point in eleven years.” “You could have put your name on the sign.” He smiled, and she gave him a short smile in return. He recognised that part of her: the quick answer, the refusal to surrender even a small point. But she had once spoken with her whole body, leaning over tables, catching strangers by the sleeve. Now she kept her elbows close and her coat on. “What happened to your hair?” “I had it cut.” “It was halfway down your back.” “That was seventeen years ago.” “Was it?” “You were forty-one. You complained about it all through lunch.” “I don’t remember complaining.” “You wanted me to tell you that you looked thirty.” “I looked thirty-five.” “You looked tired. You still do.” He went to the mirror behind the bottles and examined himself. The grey in his beard had spread since his last trim. He tucked the cloth under the counter. “What kind of meeting?” “Housing.” “You still work for the council?” “I work for a different council. I’m head of temporary accommodation.” He rested his hands on the bar. His signet ring clicked against the wood. “You used to break into empty flats.” “One flat.” “Three.” “Two. You only counted the third because we couldn’t get the window open.” “The woman on the ground floor called the police.” “You told her we were measuring for curtains.” “She believed me.” “She asked for a quote. We had to leave.” Ruth drank again. The memory had loosened something in her face, but she kept her gaze on the glass. “I remember the family,” she said. “The ones we got into the second flat. The little boy had a red scarf.” “He left it behind.” “No. Your mother washed it for him.” Silas reached for the bowl of crisps and set it between them. Ruth took one, then brushed salt from her fingertips onto the mat. “What does a head of temporary accommodation do?” he asked. “Finds rooms. Signs contracts. Listens to people explain why the room they’ve been given won’t do.” “And when it won’t?” “I find another one, if there is one.” “That sounds straightforward.” “It isn’t. I had a woman this morning whose son’s school was an hour and a half from the hotel we offered her. She works nights. She couldn’t get him there and get to bed before her next shift.” “What did you do?” “Found her a room nearer the school. It had a broken window, but the landlord promised to fix it by Friday.” “You believed him?” “I put it in writing. I’ll call on Friday.” He pushed the bowl closer. She took another crisp. “You’d have marched on the town hall once,” he said. “I did. We marched on it together. Your mother came out on her lunch break and brought us biscuits.” “She brought you biscuits. I got half of one.” “You’d already eaten.” “She didn’t know that.” “She knew you.” Ruth took off her coat and folded it over the stool beside her. Her jacket had a loose thread at the cuff, which she twisted around her finger and broke. “I’ve marched on the town hall since,” she said. “They still haven’t built enough places to put people. I got tired of shouting through the windows.” “And now you’re inside.” “Yes. It’s warmer.” A couple came in, carrying the smell of rain with them. Silas served them at the other end of the bar. They asked about the photographs on the wall, and he told them the black-and-white street scene showed Soho in the fifties. He had told that to customers for years, though a man who knew the area had once insisted it was Camden. When he returned, Ruth had her phone in her hand. She tapped out a message, then put it face down. “Your daughter?” he asked. She looked up. “I didn’t know you knew about her.” “Your mother sent me a Christmas card. Years back. She put a photograph inside.” “Which photograph?” “You and a little girl on a beach. She had a bucket on her head.” “That was a washing-up bowl.” “I wondered about the handles.” “Leah’s twenty-six now.” He pictured the child in the photograph and failed to make an adult of her. “What does she do?” “She teaches music at a primary school.” “You used to say you’d never have children.” “I used to say I’d never wear a suit.” “You’ve kept one promise, then.” Ruth glanced down at the jacket. “I bought three of them. The other two are blue.” He poured himself a small measure of whisky and left the bottle on the counter. “Did Leah get your singing voice?” “She got one that works. Mine went strange after I had an operation on my thyroid.” Ruth touched the base of her throat. “It’s fine for talking. Singing’s another matter.” “You sang at every party we went to.” “I sang at parties you went to. There were others.” “You sang over a man playing the piano once.” “He was playing the wrong song.” “He was playing his own song.” “He shouldn’t have done it at a party.” Silas laughed. She smiled into her drink, then looked towards the maps and photographs on the wall behind him. “I went back to your mother’s house last year,” she said. He put down his glass. “Why?” “I was in Bristol for work. I took a walk after the meeting.” “Did you go in?” “No. A family live there. They’ve painted the door yellow.” “She’d have hated that.” “She might have liked it. She wanted a yellow door for years.” “She told me the opposite.” “She told you it would show the dirt. She told me she was saving for the paint.” He rubbed his thumb over the face of his ring. His mother had died fourteen years ago. He had arrived in Bristol two days after the funeral, with his left leg in a brace and a bag small enough to carry on a train. Ruth had already given the house keys to the solicitor. “You cleared the kitchen,” he said. “Some of it.” “The solicitor told me.” “He made it sound like an achievement. I put tins in bags and wiped the shelves.” “You paid the milk bill.” “That was six pounds.” “You could have sent it to me.” “I didn’t know where to send it.” “You had my number.” “I had a number. I left messages.” “I know.” She looked at him. Her hand stayed around the glass, though she had finished the beer. “I heard them when I got back,” he said. “How long after?” “Three weeks.” “I left five. I counted them because I thought I ought to tell the hospital how often I’d called.” He turned his glass on the counter. A drop of whisky ran over his finger. “I was out of the country.” “I know that much.” “There was an accident. I couldn’t call.” “You could have called before you went.” He started to answer. Ruth lifted her hand. “She had a cough, Si. Nobody knew what it was when I rang you the first time. I wasn’t asking you to catch a plane that afternoon. I wanted you to know she’d gone to the doctor.” “I’d spoken to her the week before.” “She told you she was all right.” “She sounded all right.” “She sounded all right to me too. She made me take my shoes off in the hall because I’d stepped in something.” Ruth looked down at her own shoes. “I’d only stepped on a wet leaf.” Silas fetched her another half without asking. He set it beside the empty glass. “She didn’t want me making a fuss,” he said. “No. She didn’t. She also wanted you home.” He pulled the empty glass away and rinsed it beneath the tap. Water splashed his shirt. He dried his hands and found Ruth watching the movement of his left leg. “That happened in the accident?” “Yes.” “Did she know?” “No.” “She would have made a fuss about that.” “She would have told me not to run.” “You never listened.” “She never stopped telling me.” Ruth picked up the fresh glass. “There was a cardigan in the kitchen when I went through it. Green, with a button missing. She’d put it over the back of a chair.” “I remember it.” “I washed it and put it in a bag for the charity shop. Then I took it out again.” “Why?” “I thought you might want it.” He waited. “I put it in the airing cupboard with some other things. The solicitor was supposed to tell you.” “He did. I didn’t go through them.” “What happened to them?” “I told him to give them away.” Ruth nodded. She lifted her beer but did not drink. “I should have looked,” Silas said. “You had a lot to do.” “I had a box to open.” The couple at the far end asked for another round. Silas filled their glasses, carried them over and returned with their money. Ruth had taken her phone out again. She held it under the light, moving her finger across the screen. “Leah sent me these last month,” she said. “She found them in a drawer.” She passed the phone across the counter. The photograph showed four people at a table in a garden. Silas recognised the garden wall, his mother’s checked tablecloth and Ruth, young enough that her hair fell past her shoulders. She had her arm stretched towards the camera. His mother sat beside her with a cigarette between two fingers. Silas stood at the back, holding a plate over the head of a boy he did not recognise. “Who’s that?” he asked. “Martin Briggs. He lived next door.” “I was about to put the plate on his head.” “You did put it on his head. It had trifle on it.” “Why?” “He’d eaten your share.” Silas enlarged the photograph. The image broke into squares, but he could see his mother’s face, turned towards him. Her mouth was open. Ruth leaned across the bar to look. “She was telling you off,” Ruth said. “She was laughing.” “She did both. There’s another one after that.” She reached for the phone, and he handed it back.
created_at"2026-10-27T11:40:02.251Z" 10/27/2026, 11:40:02 AM
model"openai/gpt-6.1-terra-20261026"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency14776
moderation_latency(null)
generation_time52185
tokens_prompt1063
tokens_completion3323
native_tokens_prompt982
native_tokens_completion3589
native_tokens_completion_images0
native_tokens_reasoning905
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"completed"
service_tier"default"
usage0.018927
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.22.1; linux; x64))"
http_referer(null)
request_id"req-1793101202-FaNRQed47wSFfYdQQmzi"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1793101202-mG57VLYU1HQ3PXJkTNku"
upstream_id"resp_015754decaac4c28016ae08d92709087d1840b539d6a5ee2cf"
provider_responses
0
endpoint_id"2d2ad10f-098e-4bbf-aa95-11f705b2b9a2"
id"resp_015754decaac4c28016ae08d92709087d1840b539d6a5ee2cf"
is_byokfalse
latency301
model_permaslug"openai/gpt-6.1-terra-20261026"
provider_name"OpenAI"
status200
total_cost0.018927
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"
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
totalTags17
adverbTagCount0
adverbTags(empty)
dialogueSentences157
tagDensity0.108
leniency0.217
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount2180
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)
97.71% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount2180
totalAiIsms1
found
0
word"eyebrow"
count1
highlights
0"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
narrationSentences110
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences110
filterMatches(empty)
hedgeMatches
0"started to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences250
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen40
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords2180
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions41
unquotedAttributions0
matches(empty)
33.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions34
wordCount1014
uniqueNames7
maxNameDensity1.58
worstName"Ruth"
maxWindowNameDensity4
worstWindowName"Ruth"
discoveredNames
Raven1
Nest1
Silas12
Ruth16
Soho1
Camden1
Bristol2
persons
0"Silas"
1"Ruth"
places
0"Raven"
1"Soho"
2"Bristol"
globalScore0.711
windowScore0.333
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences75
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches1
per1kWords0.459
wordCount2180
matches
0"not for support but as though she had meant to touch it all along"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences250
matches
0"recognised that part"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs189
mean11.53
std12.64
cv1.096
sampleLengths
033
118
29
38
412
56
657
71
822
95
102
1119
121
1330
146
1526
164
176
1816
1918
204
213
222
234
2411
255
2614
2775
286
2936
3016
319
3255
335
344
356
365
372
3810
394
4010
413
426
4329
444
451
466
4711
4814
497
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences110
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs177
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences250
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1016
adjectiveStacks0
stackExamples(empty)
adverbCount21
adverbRatio0.02066929133858268
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences250
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences250
mean8.72
std6.38
cv0.731
sampleLengths
015
118
211
37
49
58
612
76
84
920
108
1125
121
132
1420
155
162
174
185
1910
201
2118
224
238
246
2513
2613
274
286
2912
304
316
3212
334
343
352
364
3711
385
397
407
416
4218
4323
441
4527
466
4736
4816
499
42.40% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats19
diversityRatio0.18
totalSentences250
uniqueOpeners45
36.63% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences91
matches
0"Then she lifted both hands,"
ratio0.011
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount53
totalSentences91
matches
0"She shook out her umbrella"
1"She looked past him at"
2"She placed a pound coin"
3"Her coat hung open over"
4"Her hand went to the"
5"He put the glass down."
6"She faced him again."
7"Her mouth opened, then shut."
8"She glanced at the door"
9"He came around the end"
10"She watched the movement."
11"She sat on a stool"
12"She pointed at the chalk"
13"He took another coin from"
14"She drank a mouthful and"
15"She turned the glass a"
16"He had seen her last"
17"She had worn a red"
18"She had insisted on buying"
19"He smiled, and she gave"
ratio0.582
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount85
totalSentences91
matches
0"The rain had thinned to"
1"She shook out her umbrella"
2"Silas stood behind the bar,"
3"She looked past him at"
4"She placed a pound coin"
5"Silas took the coin."
6"The woman had a narrow"
7"Her coat hung open over"
8"Her hand went to the"
9"He put the glass down."
10"She faced him again."
11"Her mouth opened, then shut."
12"She glanced at the door"
13"He came around the end"
14"She watched the movement."
15"She sat on a stool"
16"She pointed at the chalk"
17"He took another coin from"
18"She drank a mouthful and"
19"She turned the glass a"
ratio0.934
54.95% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences91
matches
0"Now she kept her elbows"
ratio0.011
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences50
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags17
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags14
fancyCount0
fancyTags(empty)
dialogueSentences157
tagDensity0.089
leniency0.178
rawRatio0
effectiveRatio0
85.5005%