Run: 2026-02-19-01KHTRM8ZNH3E9RGGAJG0PTBMQ

Run Details

Duration:
52.1s
Cost:
$0.026204
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
Aurora pushed open the door. A bell above the frame sang a single note. She stepped inside. Rows of bottles glowed like distant windows in a city that never slept. Neon green light spilled through the front windows, painting the scuffed floorboards with an unearthly hue. She drew in a breath. The faint hiss of condensation. Silence. Silas scrubbed a glass behind the counter. He crooked a glance toward the door, then froze. The glass hovered in his hand. He knelt to rest his weight on that injured knee, then rose, face drawn tight. Beard trimmed. Hair streaked through with grey. Time stilled. She crossed the distance in three long strides. Her hand landed on the bar, fingertips pressing into the worn wood. She let her eyes roam over every bottle, every photograph on the wall—old maps of Europe, a black-and-white snapshot of two friends slung across a motorbike. “How long?” she asked. “Years,” he answered, voice low. She turned her head, searching his face. “Since Cardiff.” He laid the glass down. Limped two steps toward her. “Since Prague,” he corrected. She swallowed. “You were gone by the time I reached London.” He narrowed his eyes. “Your flat above the Nest. I passed by every night. Never saw you.” She let her fingers trail along the edge of the counter. “I stayed hidden.” He set another glass beside the first. “You look different.” She raised her chin. Black hair fell in a straight line to her shoulders. Shoulders squared, posture carved from steel. “Time taught me how.” He examined the small crescent scar at her wrist. Faded but still there. He traced it with a fingertip. “You still carry that?” She closed her hand around her wrist and shrugged. “Old ghost. Doesn’t bite anymore.” He reached under the bar for a clean coaster. Placed it in front of her. “Order?” She glanced at the chalkboard above his head—whiskies, beers, a single cocktail named The Raven’s Shadow. “Whisky. Neat.” He poured amber liquid. The glass sang against the counter as he set it down. She wrapped her fingers around it, watching the light fracture inside. “I never thought you’d open a bar,” she said. He lifted the glass to his lips. Foam kissed his mustache. He wiped it away. “I never thought I’d stop chasing ghosts.” She sipped, eyes still on him. “Ghosts find you anyway.” He settled onto a stool across from her. Wrist brushed ring. “You chased law instead of phantoms.” She let the glass hover under her mouth. “Learned the rules. Found them worse than any ghost.” He nodded, slow. Limp tapped once. “Better a broken rule than a broken spirit.” Silence gathered between them. Then she spoke again. “Why didn’t you come for me?” He looked away, toward the darkened tables. “I tried. Prague went south. My world collapsed.” She closed her eyes. “I had my own collapse. Left Cardiff on nothing but fear.” He met her gaze. “He followed you.” She flinched. “Evan.” “He hurt you,” he said, blunt. She clenched her teeth. “He tried.” He dropped his hand to the counter. “Why’d you stay? Why hide?” She shook her head. “Needed space. Needed to breathe.” He rubbed his beard. “Silence can kill.” Her eyes snapped open. “I know.” They sat in the hum of neon, two figures carved from past mistakes. The maps on the wall seemed to shift under their weight. “I ran deliveries for Golden Empress,” she said. “Better miles than courtrooms.” He smiled, slow. “At least you moved.” She set her glass down, still half-full. “I wanted to disappear.” He nodded. “I wanted to forget.” Her scar glinted under the light. “Too many scars to ignore.” He touched his signet ring, silver gleaming. “That ring meant something once.” She studied it. “An old promise?” He traced the crest. “I wore it in Prague. Should’ve given it to you.” She followed his finger. “Some promises break better than people.” He looked at her without blinking. “You never broke.” She swallowed around a lump. “I bent.” He exhaled. “Bending keeps you alive.” She rose from the stool. Chairs scraped. She walked behind the bar, fingertips grazing bottle labels. “So what now?” He stood, limp carrying him forward. “Now? We sit. We talk. We try again.” She stared at him. The bar’s green glow played across her cheekbones. “I’m not the same girl you knew.” He lifted a brow. “Neither am I.” She turned back to the patronless room. “We lost years.” He joined her, standing close but not touching. “We can’t get them back.” She closed her eyes. “I have regrets.” He whispered, “Me too.” She cracked an eye open. “You think ghosts forgive springing locks, ignoring calls?” He pressed palm to the counter, leaning in. “Some ghosts forgive.” She held his gaze. “Then maybe I’ll stay.” He tipped his head. “Until closing?” She nodded. “Until closing.” He slipped behind the bar. Dug out a battered notebook and placed it before her. “I kept track of you.” She picked it up, weight in her hands. Crack of worn leather. “You charted my life?” He tapped a page. Handwriting looping, years of notes. “Every time I thought you slipped from sight.” She traced a line of dates. “You watched.” He met her eyes. “I waited.” She brushed hair from her face. “Shouldn’t we have met sooner?” He folded arms on the bar. “We met when it mattered.” She opened the notebook to a blank page. “What matters now?” He leaned forward, voice low. “We keep writing.” She closed the book. Whispered, “Together.” He cracked a grin that creased the corners of his eyes. “First round’s on me.” She settled onto the stool again, placing the notebook beside her glass. “Make it a good one.” He reached for a bottle. Poured. The amber liquid caught the neon light and fractured into shards of green and gold. She lifted her glass. He clinked his against hers. Silence. Then she said, “To second chances.” He drank deep. Foam caught his breath. He wiped mouth with the back of his hand. “To old ghosts.” She returned the glass to the bar. “Let’s hope they’re kinder this time.”
created_at"2026-02-19T10:55:13.402Z" 2/19/2026, 10:55:13 AM
model"openai/o4-mini-high-2025-04-16"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency17099
moderation_latency(null)
generation_time51719
tokens_prompt1094
tokens_completion2169
native_tokens_prompt982
native_tokens_completion5710
native_tokens_completion_images0
native_tokens_reasoning4288
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"completed"
usage0.0262042
router(null)
provider_responses
0
endpoint_id"60020533-2fb2-4aa1-9454-181029fd52de"
id"resp_0e6e1215f85aa240016996ec1178f081908a2718fdd6b49721"
is_byokfalse
latency14
model_permaslug"openai/o4-mini-high-2025-04-16"
provider_name"OpenAI"
status200
api_type"completions"
id"gen-1771498513-NJczc3tU0f8sENuJehuy"
upstream_id"resp_0e6e1215f85aa240016996ec1178f081908a2718fdd6b49721"
total_cost0.0262042
cache_discount(null)
upstream_inference_cost0
provider_name"OpenAI"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags9
adverbTagCount0
adverbTags(empty)
dialogueSentences71
tagDensity0.127
leniency0.254
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1033
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)
41.92% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1033
totalAiIsms12
found
0
word"silence"
count4
1
word"weight"
count3
2
word"traced"
count3
3
word"gleaming"
count1
4
word"fractured"
count1
highlights
0"silence"
1"weight"
2"traced"
3"gleaming"
4"fractured"
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
narrationSentences120
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount1
narrationSentences120
filterMatches(empty)
hedgeMatches
0"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences182
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen29
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1028
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions6
wordCount715
uniqueNames4
maxNameDensity0.42
worstName"Silence"
maxWindowNameDensity0.5
worstWindowName"Silence"
discoveredNames
Europe1
Raven1
Shadow1
Silence3
persons
0"Raven"
1"Silence"
places
0"Europe"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences52
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1028
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences182
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs79
mean13.01
std8.11
cv0.623
sampleLengths
017
140
244
32
446
54
65
79
814
911
1017
1114
1210
1324
1423
1514
1616
1718
1826
199
2022
2110
2217
2317
2414
2514
2615
2715
287
293
306
316
3212
339
347
356
3624
3712
387
3911
406
4111
4212
436
4414
4510
469
477
486
4919
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences120
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs144
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences2
totalSentences182
ratio0.011
matches
0"She let her eyes roam over every bottle, every photograph on the wall—old maps of Europe, a black-and-white snapshot of two friends slung across a motorbike."
1"She glanced at the chalkboard above his head—whiskies, beers, a single cocktail named The Raven’s Shadow."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount720
adjectiveStacks0
stackExamples(empty)
adverbCount17
adverbRatio0.02361111111111111
lyAdverbCount1
lyAdverbRatio0.001388888888888889
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences182
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences182
mean5.65
std3.4
cv0.602
sampleLengths
05
19
23
313
416
55
65
71
87
99
106
1115
122
135
142
158
1612
1726
184
195
207
212
225
235
244
252
269
274
2813
2911
303
317
323
334
3410
356
364
379
384
396
404
419
425
439
446
451
4616
472
484
4911
55.68% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.34065934065934067
totalSentences182
uniqueOpeners62
64.72% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences103
matches
0"Then she spoke again."
1"Then she said,"
ratio0.019
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount76
totalSentences103
matches
0"She stepped inside."
1"She drew in a breath."
2"He crooked a glance toward"
3"He knelt to rest his"
4"She crossed the distance in"
5"Her hand landed on the"
6"She let her eyes roam"
7"he answered, voice low"
8"She turned her head, searching"
9"He laid the glass down."
10"He narrowed his eyes."
11"She let her fingers trail"
12"He set another glass beside"
13"She raised her chin."
14"He examined the small crescent"
15"He traced it with a"
16"She closed her hand around"
17"He reached under the bar"
18"She glanced at the chalkboard"
19"He poured amber liquid."
ratio0.738
3.69% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount94
totalSentences103
matches
0"Aurora pushed open the door."
1"A bell above the frame"
2"She stepped inside."
3"Rows of bottles glowed like"
4"Neon green light spilled through"
5"She drew in a breath."
6"The faint hiss of condensation."
7"Silas scrubbed a glass behind"
8"He crooked a glance toward"
9"The glass hovered in his"
10"He knelt to rest his"
11"Hair streaked through with grey."
12"She crossed the distance in"
13"Her hand landed on the"
14"She let her eyes roam"
15"he answered, voice low"
16"She turned her head, searching"
17"He laid the glass down."
18"He narrowed his eyes."
19"She let her fingers trail"
ratio0.913
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences103
matches(empty)
ratio0
98.21% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences16
technicalSentenceCount1
matches
0"He cracked a grin that creased the corners of his eyes."
13.89% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags9
uselessAdditionCount2
matches
0"he answered, voice low"
1"he said, blunt"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags9
fancyCount3
fancyTags
0"he corrected (correct)"
1"He whispered (whisper)"
2"Whispered (whisper)"
dialogueSentences71
tagDensity0.127
leniency0.254
rawRatio0.333
effectiveRatio0.085
82.6037%