Run: 2026-09-23-01M37HMS992STVKABQ6RYK8M82

Run Details

Duration:
1m 4s
Cost:
$0.034394
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
Rain blew through the doorway of the Raven’s Nest and lifted the corners of a map pinned beside the bar. Silas looked up from the glasses he was drying. A woman stood on the threshold with a canvas bag held against her chest and water dripping from the hem of her coat. “We’re open,” he told her. “I gathered that from the lights.” She crossed to the bar. White hair had escaped its plait, and a strip of plaster covered one knuckle. Silas put down the glass. “Jo.” She stopped beneath a photograph of Soho taken before either of them had lived there. For a moment her mouth held the shape of a greeting without making one. “I didn’t know this was yours.” Silas glanced towards the green neon leaking across the wet pavement. “Neither did I, some mornings.” Jo pulled out a stool. She used to choose the seat with a view of both exits, then make a joke if anyone noticed. Tonight she sat with her back to the door and set her bag on the floor. “What can I get you?” “A tonic. No gin.” He opened a bottle and filled a glass with ice. The bottle cap slipped against his silver signet ring. Jo watched his hand rather than his face. “That ring survived.” “It’s harder to lose than a watch.” “You lost three watches in Bucharest.” “One was stolen.” “By you. From the man who’d stolen it first.” Silas pushed the glass across. Jo took a long drink. Her fingers shook against the rim, then settled. The bar had thinned out after the theatre crowd. Two men near the window argued over a crossword in low voices; from the back came the click of a radiator cooling. Silas had spent years arranging the room so customers could speak without being overheard. Jo had once taught him how. “What brought you in?” he asked. “The rain. I was at the library round the corner.” “Borrowing a book?” “Teaching a class.” Silas picked up another glass. “What kind of class?” “Forms, mostly. Reading payslips. Letters from the council. We use books when we can get everyone to agree on one.” She touched the plaster on her hand. “I sliced myself opening a box of donations. My old training would have spared me that, at least.” “You taught me to open boxes with a key.” “I taught you to check for a wire first.” He set the glass down. “You don’t work for them.” “No.” The word stayed between them. Jo reached for her bag and drew out a paperback with a torn cover. Its spine shone under fresh strips of tape. “One of the students brought this for me to mend. I’ve made a mess of the first page.” Silas recognised the book. He had read it on a train out of Vienna while Jo slept against the window, one hand inside her coat. He touched the repaired spine but left it in her grasp. “You were good at getting people to read things they didn’t want to.” “I was good at getting them to sign.” She slid the paperback back into her bag. Silas caught himself looking at the door. In Prague, Jo had never let him stand there without moving him to one side. He took a cloth to a dry patch of wood. “How long has it been?” “Twenty-one years since I last saw you.” Jo pushed an ice cube round her glass. “You left the service before I did.” “Prague was enough for me.” “Your knee?” He shifted his weight off his left leg. “That too.” Across the room, one of the men called for another pint. Silas served him, took payment and wiped the counter beneath the pump. The man complained about a missing five-letter answer. Silas gave him a word that fit. When he returned, Jo had moved his abandoned glass onto the drying rack. “You still put things where they belong,” he told her. “I’ve spent all afternoon looking for someone’s lost reading glasses.” “Did you find them?” “He wore them to ask me.” She smiled at the memory. Silas remembered a different smile, narrow and private, at the end of a successful meeting. She had worn a dark suit in those days and kept her hair short enough to cut with office scissors. Men twice her rank had offered her their chairs. She had taken their files instead. “You sent postcards,” he said. “Two.” “One from Bath.” “The other was from York.” “I know.” Jo rubbed a damp thumb against the label on the tonic bottle. “I thought you’d come if I put an address on them. Then I hoped you wouldn’t. I moved before the second one could reach you.” “It reached me.” “I know that now.” Outside, a bus hissed through standing water. Its light passed across Jo’s face and caught in the fine lines beside her eyes. Silas tried to picture her on a pavement with an armful of books, waiting for the doors to open, and found the picture easier than the one he had carried for years. “The class started with one man,” she told him. “He wanted to read the letter about his rent without his daughter beside him. He came back the following week with his neighbour. I had to find another table.” “You could always fill a room.” Jo looked down at her glass. “I used to speak for everyone in it.” Silas stopped turning the cloth in his hands. “I went back to Prague,” she said. His knee pressed against the bar’s foot rail. “When?” “Last autumn. I had a few days between classes. I went to the street.” “They knocked the building down.” “They’d taken down the flats. The bakery was still there. The woman behind the counter remembered what the street looked like before.” Jo put her glass aside. “I asked her about Irena.” Silas folded the cloth once, then again. He could still see the lift doors, dented along the bottom where someone had kicked them, and the fluorescent strip reflected in the wet floor. Irena had worn a coat too thin for March. She had given them the archive key wrapped in a tissue so its teeth would not tear the lining of her pocket. “Did the woman know her?” “No. I found her sister through a notice I’d kept.” Jo touched the plaster on her knuckle. “Irena lived another nine years.” Silas looked at her. “She got out of the building. One of the neighbours let her through the cellar. She went to Brno.” For twenty-one years he had remembered a hand striking the lift door as it closed. He had heard it each time an empty lift arrived at his floor. “Did you see her?” “No. She died before I found her sister.” The men at the window finished their crossword and called their thanks on the way out. Silas waited until the door shut before he spoke. “Why did you keep the notice?” “Because I knew her name.” “You knew it then.” “I put it in the report. I called her an incidental contact.” Jo met his eyes. “Her name was above the box where I wrote that. I read it before I signed.” Silas gripped the edge of the bar. The silver ring left a shallow mark in the wood. “I signed it too.” “You had a leg full of stitches.” “I could hold a pen.” Jo reached into her bag, but Silas lifted a hand. She left whatever she had found inside it. “Irena’s sister asked if she’d helped us,” Jo told him. “I told her about the key.” “And the lift?” “Yes.” Silas saw Jo’s hand on the button. He saw his own fingers braced against the door while she hauled him across the floor. Irena had called his name, not hers. She had known Jo for weeks and him for three days, but he was the one nearest the opening. “I took my hand away,” he said. Jo did not reach for his arm. She drew a beer mat from the stack beside the taps and placed it between them, its white back facing up. Silas picked up a pen from beside the till. He wrote Irena’s name, then stopped with the pen still against the card. Jo moved her tonic out of his way.
created_at"2026-09-23T16:30:08.689Z" 9/23/2026, 4:30:08 PM
model"openai/gpt-6-sol-20260922"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency32367
moderation_latency(null)
generation_time64202
tokens_prompt1063
tokens_completion2043
native_tokens_prompt982
native_tokens_completion3243
native_tokens_completion_images0
native_tokens_reasoning1538
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"
usage0.034394
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790181008-FnKDuOthuT5KO43XXQop"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790181008-2c5lMT77zvrHuWIIDNHi"
upstream_id"resp_0d143041acb13694016ab3fe90d00487d19e2a4692cdf158f4"
provider_responses
0
endpoint_id"1cfc7d9d-4404-4b8e-9ee4-58ae45c9dcd4"
id"resp_0d143041acb13694016ab3fe90d00487d19e2a4692cdf158f4"
is_byokfalse
latency1072
model_permaslug"openai/gpt-6-sol-20260922"
provider_name"OpenAI"
status200
total_cost0.034394
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
totalTags13
adverbTagCount0
adverbTags(empty)
dialogueSentences73
tagDensity0.178
leniency0.356
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1396
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)
96.42% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1396
totalAiIsms1
found
0
word"weight"
count1
highlights
0"weight"
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
narrationSentences87
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences87
filterMatches(empty)
hedgeMatches
0"tried to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences147
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen32
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1396
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions15
unquotedAttributions0
matches(empty)
30.68% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions50
wordCount880
uniqueNames9
maxNameDensity2.39
worstName"Jo"
maxWindowNameDensity3.5
worstWindowName"Silas"
discoveredNames
Raven1
Nest1
Soho1
Silas20
Vienna1
Jo21
Prague1
March1
Irena3
persons
0"Raven"
1"Silas"
2"Jo"
3"Irena"
places
0"Soho"
1"Vienna"
2"Prague"
globalScore0.307
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences66
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1396
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences147
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs89
mean15.69
std15.79
cv1.007
sampleLengths
052
15
26
324
41
529
66
716
840
95
104
1127
123
137
146
153
169
1718
1851
196
2010
213
223
239
2445
259
269
2710
281
2927
3018
3136
3213
338
3440
355
3622
375
382
3910
4051
4110
4210
434
446
4555
465
471
483
495
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences87
matches
0"being overheard"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs146
matches
0"was drying"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount1
flaggedSentences1
totalSentences147
ratio0.007
matches
0"Two men near the window argued over a crossword in low voices; from the back came the click of a radiator cooling."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount882
adjectiveStacks0
stackExamples(empty)
adverbCount15
adverbRatio0.017006802721088437
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences147
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences147
mean9.5
std6.29
cv0.662
sampleLengths
020
19
223
35
46
55
614
75
81
915
1014
116
1211
135
145
1519
1616
175
184
1910
209
218
223
237
246
253
269
275
285
298
309
3122
3214
336
346
3510
363
373
385
394
4027
4118
429
439
445
455
461
475
4814
498
48.64% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.29931972789115646
totalSentences147
uniqueOpeners44
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences83
matches(empty)
ratio0
80.24% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences83
matches
0"he told her"
1"She crossed to the bar."
2"She stopped beneath a photograph"
3"She used to choose the"
4"He opened a bottle and"
5"Her fingers shook against the"
6"She touched the plaster on"
7"He set the glass down."
8"Its spine shone under fresh"
9"He had read it on"
10"He touched the repaired spine"
11"She slid the paperback back"
12"He took a cloth to"
13"He shifted his weight off"
14"he told her"
15"She smiled at the memory."
16"She had worn a dark"
17"She had taken their files"
18"Its light passed across Jo’s"
19"she told him"
ratio0.349
8.19% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount75
totalSentences83
matches
0"Rain blew through the doorway"
1"Silas looked up from the"
2"A woman stood on the"
3"he told her"
4"She crossed to the bar."
5"Silas put down the glass."
6"She stopped beneath a photograph"
7"Silas glanced towards the green"
8"Jo pulled out a stool."
9"She used to choose the"
10"Tonight she sat with her"
11"He opened a bottle and"
12"The bottle cap slipped against"
13"Jo watched his hand rather"
14"Silas pushed the glass across."
15"Jo took a long drink."
16"Her fingers shook against the"
17"The bar had thinned out"
18"Silas had spent years arranging"
19"Jo had once taught him"
ratio0.904
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences83
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences35
technicalSentenceCount0
matches(empty)
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags13
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags8
fancyCount0
fancyTags(empty)
dialogueSentences73
tagDensity0.11
leniency0.219
rawRatio0
effectiveRatio0
85.4724%