Run: 2026-09-23-01M37HAEZ2X40JPB36M4RNQ8ND

Run Details

Duration:
1m 3s
Cost:
$0.036664
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
Rory came into the Raven’s Nest with rain in the seam of her jacket and the smell of sesame oil caught in her hair. The last delivery of the night had gone to a man who opened his door with a headset on, took his food and continued arguing with somebody Rory couldn’t hear. She had ridden back through Soho picturing the bowl of chips Silas kept under the counter for her. Silas stood on a crate beneath one of the old maps, replacing a bulb. His left knee had forced him to brace a hand against the wall. “Chips,” Rory called across the bar. “Your concern for my safety touched me.” “You’re standing on the crate with the split corner.” “Then make yourself useful.” She crossed to hold it steady. As she passed a table by the window, a woman looked up from a glass of water. Rory stopped. The crate scraped beneath Silas’s shoe. The woman had cropped her hair close to her head. Her coat lay folded across the chair beside her, its sleeves tucked in, and a paper file sat square beneath the glass. She watched Rory’s face with the strained patience of someone waiting for a name to come back. “Eva?” Eva’s mouth opened. For an instant Rory saw the girl who had once stood on a Cardiff bus shelter roof, calling down instructions to the boys who had dared her to climb it. Then Eva pressed her lips together, and the glimpse went. “You still shorten it.” “What else would I call you?” “Evelyn, at work.” Silas climbed down from the crate. He looked from one of them to the other, then carried the bulb and its packaging behind the bar. Rory pulled out the chair opposite Eva. She did not sit. “You’re here.” “I had an appointment around the corner. The rain made the decision for me.” Eva glanced at Rory’s red delivery jacket. “I didn’t know you still worked for the restaurant.” “Yu-Fei gives me shifts I can fit round everything else.” “What’s everything else?” Rory slid into the chair. “At the moment? Holding up a crate.” Eva touched the rim of her glass. Her nails were bare and cut short. At nineteen she had painted each one a different colour and left fingerprints on every mug in Rory’s mother’s kitchen. Now even the ends of her fingers looked unfamiliar. “Silas told me he knew you,” Eva said. “I thought he meant you came in sometimes.” “I live upstairs.” “You stayed?” “It was a decent room.” “I remember that room. The radiator used to knock all night.” “It still does.” Silas brought over a bowl of chips and set it between them. His signet ring caught the light as he withdrew his hand. “Kitchen closes in ten minutes,” he told Rory. “Eat them before I change my mind.” Eva followed him with her eyes. “He let you stay?” “He charged rent.” “That wasn’t what I meant.” “I know.” Rory took a chip. Eva lifted her glass, then put it down without drinking. The bar filled around their silence. A man near the door shook water from an umbrella despite the bucket Silas had placed beside him. Two women at the counter argued over a photograph on the wall: one insisted the bridge stood in Prague, the other pointed at the caption beneath it. Rory had listened to versions of that argument for three years. Eva had not known which room she slept in. “You look different,” Rory said. “So do you.” “You saw the jacket. That doesn’t count.” Eva turned her head towards the window. In the glass, her reflection held Rory’s gaze. “I used to cut my hair in the bathroom and leave it for the landlord to find in the sink. My mother hated that.” She rubbed a thumb over the close crop above her ear. “I pay someone now.” “Your mum hated the hair in the sink. She liked the hair.” “She liked having an argument she could win.” Rory reached for another chip, then drew her hand back. Eva’s mother had made hot chocolate in a saucepan when they came home soaked from school. She had also counted out bus fare on the kitchen table when the electricity bill arrived. “I was sorry,” Rory said. “I got your card.” “I should’ve come.” Eva opened the file, though she kept her eyes on Rory. A printed page showed a block of numbered paragraphs. She closed it again. “It was a Tuesday. You were working then, weren’t you?” “I could’ve taken the day off.” “Yes.” Rory looked towards the counter. Silas stacked glasses beneath the shelves and left them to their table. “I couldn’t face Cardiff,” Rory said. “I knew I’d see people. They’d ask where I’d been, and I couldn’t stand there outside the church and explain.” “You wouldn’t have had to explain anything.” “I didn’t know that.” Eva drew her coat closer when it slipped from the spare chair. The old Eva would have left it on the floor. She used to abandon gloves on buses and walk home with her hands under Rory’s arms. “Evan wasn’t going to be there,” Eva said. “I didn’t know that either.” “You could have asked me.” Rory’s fingers found the small crescent scar on her left wrist. She covered it with her cuff. “I couldn’t even ask you how she was.” “She asked about you.” Rory stared at the file. “Don’t give me what she said because you think I deserve to hear it.” “I wasn’t going to.” Silas passed their table on his way to the cellar and collected an empty bottle from the next one. Neither of them looked up until the door shut behind him. “When I called you that night,” Rory said, “you gave me this address.” “You needed somewhere Evan wouldn’t look.” “You knew I’d be safe here.” “Silas owed me a favour. He had a room.” “I took it. I knew it was more than you had to do.” Eva’s brow tightened. “You called me from a petrol station. I could hear him ringing your phone.” “He rang it eleven times.” “I remember.” Rory picked up a chip, broke it in half and left both pieces on the plate. “I thought you’d come the next morning.” Eva sat back. “I was in Berlin.” “I knew you were in Berlin. I still thought you’d come.” “I had work. Mum had already started missing appointments, and I’d used my leave getting back to see her.” “I know that now.” “I rang you from the airport two weeks later. You didn’t answer.” “I saw the call. I watched it stop.” Eva’s hand settled on the file. Through the sleeve of her pale shirt, Rory could see how thin her wrist had become. “I wanted you to be glad I’d got out,” Rory said. “I’d got on the train and found the room. Then I spent two days upstairs listening for his feet on the stairs. I couldn’t let you hear me like that.” “I’d heard you from the petrol station.” “That was different. I needed the address.” Eva gave a brief nod. She understood the distinction; Rory could see that she hated it. Across the room, the two women finally agreed that the photograph showed a bridge in Budapest. Silas came up from the cellar with a case of tonic balanced against his hip. Rory rose on instinct, but he shook his head and carried it behind the bar. “What do you do now?” Rory asked, looking back at Eva’s file. “Housing litigation.” “You used to paint slogans on vacant buildings.” “I know what I used to do.” “Who do you work for?” “A firm in Holborn. Property owners, mostly.” Eva slid the file from beneath her glass. Rory caught the words possession order on the top page before Eva turned it face down. “You came here from work,” Rory said. “I came here because it was raining.” Rory pushed the bowl towards her. “Have one.” Eva took a chip. She held it for a moment, then ate it. “Mum needed help with the mortgage,” she said. “I took the job they offered. I kept it after she died.” Rory watched rainwork through the green light of the sign outside. Cars drew strips of it along the street. “You could’ve told me.” “I could have told you a lot of things.” Eva wiped salt from her thumb. “I wrote out an email after the funeral. Three pages. By the end I’d written about the flowers, the boiler, somebody’s dog barking through the service. I deleted it.” “I would’ve read about the dog.” “You hadn’t answered when I rang.” “No.” Eva moved her glass off the file and opened it once more. She took out a pen, found that she was holding the wrong end, and turned it around. Rory remembered her filling the margins of schoolbooks with furious little drawings while Rory worked through pre-law reading at the kitchen table. Eva had drawn a crown on every judge. “I need to finish this before I go,” Eva said. Rory looked at the page between them. “All right.” Eva put the point of the pen beside a paragraph number. Rory drew the bowl back to her side of the table and ate a chip while Eva read.
created_at"2026-09-23T16:24:30.65Z" 9/23/2026, 4:24:30 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency30420
moderation_latency(null)
generation_time62991
tokens_prompt1063
tokens_completion2352
native_tokens_prompt982
native_tokens_completion3470
native_tokens_completion_images0
native_tokens_reasoning1552
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"
usage0.036664
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790180670-TvuZJe9yYzfESc91W39S"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790180670-KSDFqKHUbxqvFOzFOkOi"
upstream_id"resp_07a2a13b8ebad6d2016ab3fd3ee8cc87d18bfad4c26149e377"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_07a2a13b8ebad6d2016ab3fd3ee8cc87d18bfad4c26149e377"
is_byokfalse
latency457
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.036664
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
totalTags16
adverbTagCount0
adverbTags(empty)
dialogueSentences89
tagDensity0.18
leniency0.36
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1558
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)
93.58% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1558
totalAiIsms2
found
0
word"charged"
count1
1
word"silence"
count1
highlights
0"charged"
1"silence"
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
narrationSentences92
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences92
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences165
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen35
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1558
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions26
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions82
wordCount930
uniqueNames9
maxNameDensity4.09
worstName"Rory"
maxWindowNameDensity6.5
worstWindowName"Rory"
discoveredNames
Raven1
Nest1
Rory38
Soho1
Silas9
Cardiff1
Eva29
Prague1
Budapest1
persons
0"Rory"
1"Silas"
2"Eva"
places
0"Raven"
1"Soho"
2"Cardiff"
3"Prague"
4"Budapest"
globalScore0
windowScore0
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences68
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1558
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount3
totalSentences165
matches
0"see that she"
1"agreed that the"
2"found that she"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs109
mean14.29
std14.48
cv1.013
sampleLengths
072
127
26
37
49
54
623
78
849
91
1043
114
126
133
1425
1511
162
1730
1810
193
2012
2143
2216
233
242
255
2611
273
2823
2915
3010
313
325
332
3414
3571
365
373
387
3915
4039
4112
428
4342
445
454
463
4724
4810
496
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences92
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs155
matches
0"was holding"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences165
ratio0.006
matches
0"She understood the distinction; Rory could see that she hated it."
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount930
adjectiveStacks1
stackExamples
0"tonic balanced against his"
adverbCount16
adverbRatio0.017204301075268817
lyAdverbCount1
lyAdverbRatio0.001075268817204301
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences165
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences165
mean9.44
std6.42
cv0.68
sampleLengths
024
130
218
314
413
56
67
79
84
96
1017
112
126
1310
1422
1517
161
173
1830
1910
204
216
223
236
2419
257
264
272
2821
299
3010
313
325
337
347
357
3620
379
388
398
403
412
425
4311
443
4512
4611
478
487
496
38.48% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats19
diversityRatio0.2545454545454545
totalSentences165
uniqueOpeners42
41.15% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences81
matches
0"Then Eva pressed her lips"
ratio0.012
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount18
totalSentences81
matches
0"She had ridden back through"
1"His left knee had forced"
2"She crossed to hold it"
3"Her coat lay folded across"
4"She watched Rory’s face with"
5"He looked from one of"
6"She did not sit."
7"Her nails were bare and"
8"His signet ring caught the"
9"he told Rory"
10"She rubbed a thumb over"
11"She had also counted out"
12"She closed it again."
13"She used to abandon gloves"
14"She covered it with her"
15"She understood the distinction; Rory"
16"She held it for a"
17"She took out a pen,"
ratio0.222
15.56% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount72
totalSentences81
matches
0"Rory came into the Raven’s"
1"The last delivery of the"
2"She had ridden back through"
3"Silas stood on a crate"
4"His left knee had forced"
5"Rory called across the bar"
6"She crossed to hold it"
7"The crate scraped beneath Silas’s"
8"The woman had cropped her"
9"Her coat lay folded across"
10"She watched Rory’s face with"
11"Eva’s mouth opened."
12"Silas climbed down from the"
13"He looked from one of"
14"Rory pulled out the chair"
15"She did not sit."
16"Eva glanced at Rory’s red"
17"Rory slid into the chair."
18"Eva touched the rim of"
19"Her nails were bare and"
ratio0.889
61.73% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences81
matches
0"Now even the ends of"
ratio0.012
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences43
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags16
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags13
fancyCount0
fancyTags(empty)
dialogueSentences89
tagDensity0.146
leniency0.292
rawRatio0
effectiveRatio0
88.1501%